Secondary Logo

Journal Logo

Review article

The concept of peri-operative medicine to prevent major adverse events and improve outcome in surgical patients

A narrative review

Bollen Pinto, Bernardo; Chew, Michelle; Lurati Buse, Giovanna; Walder, Bernhard

Author Information
European Journal of Anaesthesiology: December 2019 - Volume 36 - Issue 12 - p 889-903
doi: 10.1097/EJA.0000000000001067
  • Free



The expression ‘Peri-operative Medicine’ (POM) is used increasingly in the medical literature; however, there is no consensus regarding its definition. The aims of this narrative review are to conceptualise POM and support the practice of POM by anaesthesiologists. It summarises basic knowledge about the epidemiology, pathophysiology and risk factors associated with outcomes in surgical patients. Next, it describes interventions and components of peri-operative patient care that have been shown to change outcomes, with a focus on the reduction in the incidence and severity of major adverse events (MAEs) in high-risk patients. Based on this framework, the review discusses how individual components can be integrated into overarching conceptual models and proposes a pragmatic definition of POM. The review ends with a discussion on the implementation of POM.


Diseases treated with surgery

The burden of diseases treated by surgery continues to grow; in 2012 an estimated 312 million surgical procedures were conducted worldwide.1 Although definitions of surgery and the types of surgical procedures differ from country to country, studies suggest that this growth applies to all economic and social environments.2 Increased life expectancy is associated with higher rates of surgical interventions, with a ceiling effect reached at around 1533 operations per 100 000 people.1 Longevity is expected to increase in the near future3 and may be associated with increased frailty, comorbidities and need for surgical interventions. Therefore, more high-risk patients are expected to be exposed to surgery, anaesthesia and peri-operative care.

Outcomes after surgery

Mortality, disability and health-related quality-of-life are important patient-relevant outcomes.4,5 In Europe and high-income countries, most epidemiological data on mortality originate from national registries6,7 and large prospective studies.8–10 Crude short-term mortality rates vary widely and depend on a variety of factors such as patient's health status, type and urgency of surgery, healthcare provider density and skills, patient volume and time of follow-up. The EuSOS study documented an in-hospital mortality rate of 4% that varied widely across European countries.9 Other nation-wide or more recent studies document lower mortality rates6,8,10–12 yet the key messages from these investigations are similar: surgical populations are heterogeneous and discrete groups of high-risk patients with higher than average mortality. In one large cohort, up to 80% of peri-operative deaths occurred in 12% of patients at high-risk.11 The identification of these high-risk populations is challenging (Fig. 1). The complex interplay between patient, surgery, anaesthesia, process and infrastructural factors is commonly overlooked in peri-operative care studies.

Fig. 1:
Factors associated with peri-operative outcomes.

Although data exist regarding the long-term outcomes of discrete surgical populations (e.g. colon cancer patients), few studies describe outcomes beyond 30 days after surgery and the factors influencing them. In a landmark study, Khuri et al.13 demonstrated a 30-day mortality rate of 3% after major surgery, and a 36% mortality rate after an average follow-up period of 8 years. In a comprehensive risk-adjusted analysis the authors demonstrated that postoperative MAEs had a major impact on short-term and long-term survival. The association between postoperative MAEs and mortality is particularly relevant in the elderly.14,15 These findings triggered a turning point in peri-operative management and put focus on the prevention or early treatment of postoperative MAEs with the aim of improving survival.16

Risk factors associated with outcome

The association between several peri-operative risk factors, postoperative MAEs and patient-relevant outcomes is now established and allows the stratification of patients according to risk class. Historically, a first important step was the recognition that nonclinical, patient-independent factors such as the academic level of hospitals, nurse education, nurse-staffing, and workload have a significant impact on patient's recovery and survival after surgery17–19 (Fig. 1). A second step was the identification of a number of potentially modifiable factors such as frailty (a state of decreased physiological reserve with increased vulnerability to stressors20) associated with patient-relevant outcomes such as mortality, disability and health-related quality of life. Third, interventions targeting organ protection21 and management measures22,23 were shown to improve outcomes. A last step was the recognition that patients identified as high-risk may benefit from dedicated peri-operative care pathways.24,25 However, pathways involving increased utilisation of intensive care do not seem to have a significant impact on mortality in specific populations such as elective surgery or elderly patients.26–28

Peri-operative pathophysiology and organ injury

Triggers and phases of peri-operative stress

Peri-operative stress plays a major role in organ injury and dysfunction, which is the pathophysiological basis of postoperative MAEs, acute illness and outcome (Fig. 2). In the absence of a consensus definition, we define peri-operative stress as the collective physiological response to stimuli occurring before, during and after surgery. This response is modulated, amongst other things, by the stimuli, how they are perceived (threatening or benign), the individual's genome, previous health status (including frailty and comorbidities) and the environment. Different threats (e.g. anxiety, fasting, dehydration, surgical trauma, inflammatory substances, infection) can trigger and modulate the stress response throughout the peri-operative period. The response to stress can be divided into 3 successive phases.29 The first two, coined Alarm and Resistance,29 are characterised by the nonspecific activation of the immediate reaction systems and evoke, in most cases, a useful, localised, adaptive response to threats, crucial to the healing process after injury. However, certain individuals in the face of severe, prolonged or repeated threats, as often occurs in the peri-operative period, can enter a 3rd stage (Exhaustion) in which the response itself becomes more damaging than the threat and results in organ injury.30

Fig. 2:
Pathophysiology of postoperative major adverse events.

Immediate response to peri-operative stressors

An almost immediate reaction in response to threats is the activation of the autonomic nervous system and the hypothalamic–pituitary–adrenal axis preparing the body for the ‘fight-or-flight’ response. This reaction is mediated by endogenous catecholamines. Adrenocorticotropic hormone released by the anterior pituitary mediates the release of adrenal cortisol into circulation.31 In the short term, cortisol further stimulates the adrenal medulla to liberate adrenaline32 and stimulates gluconeogenesis and glycogen breakdown in the liver and skeletal muscle, contributing to peri-operative hyperglycemia.33 By-products of tissue damage and components of bacteria are sensed by pattern recognition receptors, notably Toll-like receptors, on the surface of cells of the innate immune system triggering local release of cytokines.34 Cytokines recruit neutrophils and activate coagulation and complement cascades contributing to limit the spread of damage.

Peri-operative stress and organ injury

During the peri-operative period prolonged and/or severe local pro-inflammatory mediators can spill over to the circulation triggering a systemic inflammatory syndrome (SIRS) and exaggerated sympathetic stimulation.30 Excessive inflammation has been directly associated with adverse effects at organ level, for example postoperative delirium,35 myocardial injury36 and acute kidney injury (AKI).37 Continuous exposure to catecholamines modulates metabolism resulting in insulin resistance and hyperglycaemia, which has been shown to directly cause cellular injury.38 Excessive catecholamines may also precipitate arrhythmia and result in increased cardiac workload that is associated with postoperative myocardial ischemia.39 Both prolonged SIRS and catecholamine exposure further modulate the immune response and stimulate bacterial growth resulting in a phenotype with increasing susceptibility to postoperative infection and sepsis.34 In the lungs, recruitment and activation of neutrophils and macrophages can result in breakdown of the alveolar-capillary membrane, capillary leakage and loss of surfactant, which contribute to postoperative pulmonary oedema and atelectasis.40 Finally, exaggerated amplification of the coagulation cascade can result in a hypercoagulable state increasing the risk of postoperative thromboembolic complications (e.g. pulmonary embolism) and organ-level injury (e.g. acute kidney or myocardial injury).40

Goals of peri-operative care

Peri-operative care and postoperative major adverse events

Historically, the first task of anaesthesia was to secure intra-operative care and avoid death during surgery. High intra-operative safety was achieved in the past decades.41 However, postoperative mortality is still not zero and is related to postoperative MAEs.10,42 There may be a causal link between postoperative MAEs and postoperative mortality in high-risk patients.13,43

Studies in the early 1990s reported an association between postoperative MAEs and unfavourable outcome. These observations led to the concept of ‘failure-to-rescue’,44 meaning that a failure to adequately identify and manage MAEs when they arise leads to death. Some frequent postoperative MAEs with high death rates are bleeding, unplanned intubation, sepsis, pneumonia, kidney failure, myocardial injury and infarction and stroke.16,43 A low failure-to-rescue rate is a key feature of high quality in peri-operative care.45

Components of peri-operative care

Key components of peri-operative care are as follows (Fig. 3):

  1. Early risk assessment with identification of high-risk patients and communication of this risk to patients, proxies, and between healthcare professionals; this may include offering alternative care strategies to the highest risk patients, based upon patient values and predefined goals of care.
  2. The application and coordination of peri-operative pathways tailored according to the risk of MAEs during critical time periods before (optimisation) and after interventions (avoidance of failure-to-rescue). Frequent risk assessment allowing patients to be transferred to a different pathway if risk prediction changes throughout the peri-operative period is essential because predictive models are imperfect.
  3. Patients with a low risk of MAEs should be identified allowing a cost-effective46,47 means to
    1. use enhanced recovery after surgery (ERAS) programmes in low or intermediate-risk patients and
    2. concentrate resources on high-risk patients.
  4. High-risk patients should benefit from
    1. optimisation of their physical and mental status to minimise risk of adverse events;
    2. peri-operative organ protection;
    3. improved peri-operative surveillance and complex care management with regular risk assessments for early recognition of adverse advents. This may include planned admission to high-intensity care units (intermediate or intensive care) and follow-up of high-risk patients on the ward by specialised teams.
Fig. 3:
Components of peri-operative care and a patient's trajectory. *Depending on local resources some patients may need to be referred to tertiary or specialised hospitals. IMC, intermediate care unit; PACU, postoperative care unit.

All these components are core competencies of anaesthesiologists.

Peri-operative interventions to improve outcomes

MAEs can occur in the pre-, intra- and post-operative periods, but a significant proportion of MAEs leading to death occur in the first 24 to 48 h after surgery.48,49 Therefore, early postoperative care is an important, logical focus for peri-operative care, and so the assessment of the effect of peri-operative interventions has been focused on postoperative events. There is good evidence suggesting that high-risk patients develop postoperative MAEs even in high performance teams and hospitals.50 Postoperative MAEs are associated with increased health costs.51 A main interest of peri-operative care is to manage these MAEs efficiently, that is with early identification and continuous optimisation, even with limited healthcare resources. Several interventions in the peri-operative period have been shown to improve outcomes of high-risk patients. Table 1 summarises a number of pre-operative,52–66 intra-operative21,64,67–71 and postoperative64,72–80 interventions that can be implemented locally.

Table 1:
Possible interventions for peri-operative optimisation

Overarching models of peri-operative care

Peri-operative Medicine

Based on the framework of peri-operative care presented so far, the following definition of POM is proposed: POM is the patient-centered and value-based multidisciplinary peri-operative care of surgical patients, with a particular focus on high-risk patients. This definition does not use the word ‘recovery’ because ‘recovery’ is not easy to define and may be an unreasonable target, particularly in patients that are unlikely to benefit from surgery. In addition, the definition is inclusive to encompass the care of patients that, despite having a medical condition that could be treated with surgery, do not actually undergo a surgical procedure and are directed to alternative pathways such as palliative care (Fig. 3). A further advantage of this definition is that it proposes a value-based approach, that is with the inclusion of patient's values as well as cost-effectiveness.81 Furthermore, it focuses on the ‘natural’ competencies of anaesthesiologists to handle high-risk patients successfully.

The goals of POM are to promote high quality recovery, and to reduce disability, MAEs and mortality after surgery, with a rational use of available resources. Although the principles of POM should apply to all surgical patients, high-risk patients are most likely to benefit from POM and its key components.82 An important added value of POM is the optimum tailoring of complex care and resource management for high-need, high-cost patients. In agreement with these aims is the avoidance of indiscriminate peri-operative testing and interventions, which is a pillar of Choosing Wisely initiatives across the globe.83

The addition of POM to anaesthesia expands the role of the anaesthesiologist and represents a focused care strategy for high-risk patients, that is those who present increased risk of MAEs, prolonged length of hospital stay, and unfavourable outcomes. A large proportion of patients submitted to nonelective surgery are high-risk patients and are of particular interest for POM.

Although individual peri-operative interventions have been shown to improve postoperative outcome, more evidence is needed to demonstrate the benefit of POM as a complex model of care with multiple components. Some existing examples are the improved survival reported after implementation of an efficient pre-operative frailty screening instrument.25 Risk-adjusted peri-operative mortality rates decreased in high-risk operations between 8 and 36% over a 10-year period;84 this decrease of fatal outcomes may potentially be related to decreased rates of postoperative major adverse cardiac events85,86 and decreased mortality after postoperative sepsis.87,88 One important study underway in the United Kingdom, the Peri-operative Medicine Service for High-risk Patients Implementation Pilot (POMSHIP),89 will evaluate the clinical effectiveness and costs of a 3-component service that includes: first, individualised pre-operative risk assessment; second, postoperative admission to a critical care unit for high-risk patients and; third, postoperative follow-up in the ward by a dedicated team.

Enhanced recovery after surgery

Different peri-operative concepts have been developed to tackle high postoperative morbidity and prolonged duration of hospitalisation; the ‘enhanced recovery after surgery’ (ERAS) multicomponent programme is one of the earliest expressions of the principles of comprehensive peri-operative care. ERAS programmes are patient-centered, adhere to the culture of quality and safety, and depend on efficient inter-professional communication to improve coordination of care and to avoid overtreatment. ERAS uses evidence-based practices to decrease the potential need for postacute care services, readmissions, disability and mortality. The unifying goals of POM and ERAS concepts are avoidance of harm and reducing variation in practices, in an effort to ensure the best possible long-lasting recovery after surgery. However, ERAS programmes focus on homogenous subgroups of low-to-moderate risk patients defined by the type of surgery. ERAS propose standardised, routine, cost-effective peri-operative pathways including ambulatory care.90 POM is a broader approach offering risk-adapted, coordinated pathways, including high intensity individualised care of hospitalised high-risk patients, that may have poor outcome without further support.11 Leadership may also be different, whereas the concept of ERAS is often surgeon driven, the concept of POM is often anaesthesia and critical care driven. These concepts are therefore complementary, and ERAS can be seen as a care pathway adequate to low-intermediate risk patients within the scope of POM.

Risk assessment in peri-operative medicine

For tailored peri-operative management, that is to concentrate preventive and therapeutic efforts on patients most likely to benefit from them, and to avoid inefficient or even detrimental resource utilisation, the estimation of a patient's risk is crucial. Early identification of high-risk patients and optimal risk stratification are cornerstones of POM. Initial pre-operative risk stratification should be questioned during the whole peri-operative period as it may need revision throughout hospitalisation. Several approaches to peri-operative risk stratification have been proposed with risk scores,91–95 biomarkers, and additional testing, for example cardiopulmonary exercise testing (CPET).96,97

Risk scores

Peri-operative risk scores can be classified according to the predicted outcome and the timing of the risk estimation (Table 2). There are scores that predict all-cause mortality,52,91,92,95,98–102 cardiac complications,95,103–106 pulmonary complications,95,107 renal complications108 or postoperative complications and death.91,109–111 Discharge scores from monitored units such as the Aldrete score112 could be useful to predict survival in non-monitored units but their prediction performance remains unclear.113

Table 2:
Peri-operative risk stratification of potential high-risk patients for noncardiac surgery

Many scores are user-friendly because they are based on simple information collected from the patient's history or basic laboratory tests. Others are complex and are more useful within the context of risk prediction in scientific investigations. External validation is a limitation of many peri-operative scores.91 While most scores allow for risk stratification that can be used for communication and care planning, individual risk estimations are seldom possible. Further, only few risk scores include pre-operative chronic treatment, which could potentially improve the performance of prediction models. Finally, specific risk scores for common MAEs such as delirium, bleeding and sepsis are still lacking. Recent predictive models based on machine learning techniques applied to large datasets from electronic healthcare records and anaesthesia information management systems,114,115 do not appear to improve discrimination over more simple validated risk stratification tools.

Despite all limitations, clinical risk scores are the basis of early identification of high-risk patients and should support decision-making within specific clinical and coordinated pathways.


Biomarkers may improve the prediction performance of risk scores. Cardiac biomarkers are particularly well established and most biomarkers with reasonable predictive performance focus on predicting cardiac adverse events (Table 2). Nevertheless, biomarkers associated with other MAEs have been identified and may be used in clinical practice to help identify high-risk patients throughout the peri-operative period. Thus, biomarkers are not only of interest for pre-operative risk stratification but also for peri-operative surveillance with sequential risk re-assessments for early recognition of adverse advents.

Troponin (and since its introduction high-sensitivity troponin)116–120 and natriuretic peptides116,118,121 have been extensively studied, whereas other markers are still insufficiently explored.122–127

The discriminative ability of pre-operative high-sensitivity-troponin to predict postoperative mortality is moderate to good (Table 2).116,118 Increased pre-operative high-sensitivity-troponin values are significantly associated with major cardiovascular events and mortality after surgery;116–120,128 however, many studies report a high prevalence of high-sensitivity-troponin exceeding the 99th upper reference percentile pre-operatively.116–120 This high-prevalence results in poor positive predictive values and risk misclassification,116–120 if pre-operative troponin is not combined with other risk stratification tools.

In the context of risk-reassessment using sequential biomarkers measurements, elevated high-sensitivity-troponin after noncardiac surgery was significantly associated with noncardiac complications,129 30-day43 and 1-year mortality119 independent of the presence of symptoms and ECG changes.

The discriminative ability of pre-operative natriuretic peptides to predict 30-day mortality and myocardial infarction (MI) was reported as moderate in a large individual patient level data meta-analysis (Table 1).121 The addition of natriuretic peptides to clinical risk scores may improve prediction for postoperative outcomes.97,121

Urinary output and serum creatinine are key parameters for the diagnosis of AKI. However, interpretation of their changes in the peri-operative period is challenging. Cystatin C, a functional biomarker, revealed good discrimination for AKI in a variety of settings.130 Several renal damage biomarkers have been proposed in the setting of cardiac surgery131: neutrophil gelatinase associated lipocalin (NGAL), for example, demonstrated moderate-to-high discrimination for AKI, yet with a high level of heterogeneity.131,132 For noncardiac surgery a prospective cohort study suggested moderate discrimination for endostatin, NGAL and cystatin C for recovery from AKI.133 Biomarkers of renal damage remain underexplored in noncardiac surgery.

A host of other biomarkers such as pre-operative albumin134,135 and haemoglobin (Hb),136–138 hyperglycaemia94–96 and C-reactive protein97,139 are associated with increased postoperative mortality and morbidity. However, whether these biomarkers are independent risk factors or provide additional value to current risk scores remains under-investigated. Similarly, postoperative biomarkers such as Hb, glucose and lactate have been shown to be associated with MAEs such as bleeding, infection and other major MAEs92,98–101 but remain inadequately studied.

Functional capacity

There are three ways of characterising functional capacity: subjective assessment of daily activities with estimation of metabolic equivalents (METs), structured questionnaires to estimative METs and CPET. Based on earlier small-scale studies, international guidelines recommended the use of METs, based on subjective reporting, as a means of identifying high-risk patients to trigger more intensive investigations before noncardiac surgery.140,141 The basic idea was that a surgical intervention is a stress and therefore, pre-operative exercise capacity estimation (a stress estimation) is associated with stress-related postoperative MAEs, in particular cardiac events. This view was recently challenged with the publication of the large international prospective METS study.97 In this METS study, subjective assessment of functional capacity with METS was not related to cardiopulmonary fitness on the CPET and was not useful to predict postoperative morbidity or mortality. Furthermore, neither peak oxygen consumption nor anaerobic threshold measured using CPET was associated with 30-day mortality or MI, and CPET did not improve prediction of these events over more simple clinical scores.97 However, CPET-derived peak oxygen consumption did improve prediction of a composite outcome of postoperative complications.97 Of note, the use of a structured questionnaire on exercise capacity, the Duke Activity Index Scale, led to a correct reclassification in 23% of the patients for the prediction of 30-day mortality or death.97 However, the optimum score necessary to appropriately discriminate between favourable and unfavourable outcomes is unknown.

Given the strong association between pre-operative frailty and postoperative outcomes142,143 it is rational that frailty-associated features could be useful risk-stratification tools. A potential postoperative risk factor could be the absence of early ambulation, which is related to prolonged hospital stay.144,145 Another potential risk factor could be the absence of early feeding, which is also related to prolonged hospital stay.146

Other variables

Despite being considered as a major health hazard,147 postoperative hypoxaemia has not been investigated as a predictor of postoperative MAEs. Fluid balance68,148 at the end of intervention or peri-operative heart rate149 may be risk factors for postoperative MAEs. Early postoperative cognitive dysfunction may be a good predictor of long-term outcomes.150–152

Management in Peri-operative Medicine

The application of research results to clinical practice directly benefiting patients may take decades to occur.153 Nonclinical aspects may contribute to a faster implementation of POM.154 POM encompasses the optimised care of the high-risk surgical patient, from contemplation of surgery to postoperative care, which may include surveillance and care after hospital discharge. This demands a wide medical repertoire and the coordination of different medical and paramedical specialists. These principles should be adaptive allowing for peri-operative pathway changes according to individual needs. Therefore, management of peri-operative care is much more than operating room planning.

The application of the principles of POM is likely to be context-specific and influenced by local infrastructure, hospital and surgical volume (high volume is more favourable), a stable peri-operative team with physician coverage and an adequate nurse-patient-ratio (higher number of nurses is more favourable), the distribution of high-risk patients over time (avoidance of peaks of high-risk patients by optimising scheduling of elective procedures) and the preparedness for emergency cases (Fig. 1). Therefore, peri-operative management should integrate local specificities (e.g. legal or cultural) and restrictions (e.g. in terms of available resources) with standardised evidence-based recommendations from National155–158 and International52,140,159–174 guidelines (Table 3). Possible interventions for quality improvement initiatives along the whole peri-operative period have been described earlier (Table 1). Potentially, multiprofessional collaborative activities may be more effective for behavioural changes of healthcare providers.175,176

Table 3:
Relevant guidelines for Peri-operative Medicine
Table 3:
(Continued) Relevant guidelines for Peri-operative Medicine

Basics of peri-operative management

Successful peri-operative management includes aspects of structure (organisation of peri-operative care), process (what, when and how it is being done) and outcomes (healthcare results).177

Structural aspects are represented by dedicated clinical pathways for high-risk patients with repeated risk assessment pre-operatively, at the end of surgery and the end of monitored postoperative care. Effective process management of high-risk patients may be performed with simple elements such as checklists, standardised procedures, ready-to-use sets and solutions, preprepared charts and defined pathways. The communication (feedback) and discussion of predefined outcomes are essential elements of permanent quality improvement and optimisation.

Critical features of peri-operative management

The focus of peri-operative management is the reduction in the incidence and severity of MAEs. Therefore, local implementation of POM should consider the development of structures and processes (Fig. 3) enabling:

  1. Accurate pre-operative identification of high-risk patients with precise risk stratification followed by allocation to specific pathways with tailored interventions, optimisation and organ protection.
  2. Frequent risk re-assessment during the entire peri-operative period, particularly during critical peri-operative checkpoints (i.e. before surgery, at the end of surgery and before discharge from monitored units to the ward), ensuring allocation to the most appropriate care pathways at each step.
  3. Early identification of adverse events and adequate communication of MAEs among healthcare providers for optimal treatment, and established communication channels with the patient and proxies.
  4. Clear task responsibilities among healthcare professionals during the whole peri-operative period.
  5. Appropriate administration of drugs, transfusions and fluids, with consideration of their potential for adverse events.
  6. A programme and measures for (hand) hygiene during the peri-operative period decreasing the rate of unplanned postoperative nosocomial infections.

These critical aspects with a high error potential, in particular in nonelective patients, may be used by clinicians and managers to build checklists and local roadmaps for local implementation of POM and for quality improvement initiatives. In addition, Table 1 summarises a number of specific pre-operative,52–63 intra-operative21,64,67–71 and postoperative64,72–80 clinical interventions that can be implemented locally for peri-operative optimisation of high-risk patients.

Regular feedback of outcome

National and local stakeholders should agree on specific outcomes that are prospectively assessed in all high-risk patients (quality indicators). The most frequently investigated patient-relevant outcome in high-risk patients is the postoperative mortality. Other relevant outcome indicators of POM are the rate of unplanned return to the operating room, unplanned ICU admission (including re-intubation and re-admission), peri-operative MAEs and failure to rescue rates.178 A critical follow-up with audit and regular feedback on these outcomes is a fundamental part of POM and quality improvement.

Local quality improvement programmes

Targeted quality improvement programmes may be particularly useful for increasing the quality of peri-operative care in situations with high error rates. This may apply to any of the peri-operative periods. For instance, if peri-operative diagnostic errors are frequent in the pre-operative consultation clinic with futile surgical interventions or underestimations of risks, then this consultation may require reorganisation. If high-risk patients are discharged early to surgical wards despite abnormal vital signs, the postanaesthesia care unit may need to implement quantitative instruments for discharge.

The implementation process of a quality improvement programme is crucial. During the planning phase, the multidisciplinary involvement of all stakeholders is essential, as well as the integration of feedback by local front-line providers.179 Experiences and results from local pilot implementation and champions (ideally volunteers) recruited from the local team with protected time for promotion and education will enhance adoption and engagement. The use of an established knowledge translation framework,180,181 a multisite project, and a reasonable, explicit timeline including actionable and quantifiable milestones have been reported to facilitate implementation.179,182 Consistent with most knowledge translation frameworks, iterative reassessment and readjustment cycles will improve the programme. The availability of local outcome data from registries will foster engagement among front-line professional and justify investments towards hospital management.179,182

Of note, in terms of risk assessment and efficient recovery, the ERAS concept has been shown to be successful in reduction of hospital length of stay for a number of procedures especially elective procedures with homogeneous patient groups. Many lessons can be learnt from such pathways and applied to all patient groups. For example, the implementation of peri-operative packages with stop-checks for the fulfilment of discrete elements of care and evidence-based care in postoperative care unit24,183 encourages a reduction in variation in healthcare delivery.


This is a narrative review aiming to help define a concept including medical and management aspects. The authors did not use a predefined search strategy and the evidence presented reflects the authors’ perspectives on POM. The review does not focus on a specific component of POM (e.g. risk assessment, pathways or definitions) and, therefore, it is not a systematic review. Specific components of POM should be investigated in regularly updated systematic reviews.184 This narrative review is an expert opinion report, and the authors are experienced senior researchers and educators in the field of POM and two of the authors are Editors of the European Journal of Anaesthesiology (MC and BW) having a broad and updated view on this topic. Some aspects related to POM are not covered in the present review, including education and training and future research.


POM is the patient-centered and value-based multidisciplinary peri-operative care of surgical patients. Frequent risk (re)-stratification during the peri-operative period using scores and biomarkers combined with allocation of patients to individualised risk-adapted predefined clinical pathways may decrease the occurrence of MAEs and improve outcomes. Peri-operative optimisation based on recent guidelines may further improve patient-relevant outcomes. Finally, regular audit and feedback are essential for assessing and adjusting performance.

Acknowledgements relating to this article

Assistance with the review: none.

Financial support and sponsorship: none.

Conflicts of interest: none.

Comment from the editor: MC is an Associate Editor of the European Journal of Anaesthesiology. BW is a Deputy Editor of the European Journal of Anaesthesiology.


1. Weiser TG, Haynes AB, Molina G, et al. Estimate of the global volume of surgery in 2012: an assessment supporting improved health outcomes. Lancet 2015; 385 (Suppl 2):S11.
2. Meara JG, Leather AJ, Hagander L, et al. Global Surgery 2030: evidence and solutions for achieving health, welfare, and economic development. Lancet 2015; 386:569–624.
3. Kontis V, Bennett JE, Mathers CD, et al. Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble. Lancet 2017; 389:1323–1335.
4. Myles PS, Hunt JO, Nightingale CE, et al. Development and psychometric testing of a quality of recovery score after general anesthesia and surgery in adults. Anesth Analg 1999; 88:83–90.
5. Shulman MA, Myles PS, Chan MT, et al. Measurement of disability-free survival after surgery. Anesthesiology 2015; 122:524–536.
6. Noordzij PG, Poldermans D, Schouten O, et al. Postoperative mortality in The Netherlands: a population-based analysis of surgery-specific risk in adults. Anesthesiology 2010; 112:1105–1115.
7. Whitlock EL, Feiner JR, Chen LL. Perioperative mortality, 2010 to 2014: a retrospective cohort study using the National Anesthesia Clinical Outcomes Registry. Anesthesiology 2015; 123:1312–1321.
8. Jawad M, Baigi A, Oldner A, et al. Swedish surgical outcomes study (SweSOS): an observational study on 30-day and 1-year mortality after surgery. Eur J Anaesthesiol 2016; 33:317–325.
9. Pearse RM, Moreno RP, Bauer P, et al. Mortality after surgery in Europe: a 7 day cohort study. Lancet 2012; 380:1059–1065.
10. International Surgical Outcomes Study Group. Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries. Br J Anaesth 2016; 117:601–609.
11. Pearse RM, Harrison DA, James P, et al. Identification and characterisation of the high-risk surgical population in the United Kingdom. Crit Care 2006; 10:R81.
12. Abbott TEF, Fowler AJ, Dobbs TD, et al. Frequency of surgical treatment and related hospital procedures in the UK: a national ecological study using hospital episode statistics. Br J Anaesth 2017; 119:249–257.
13. Khuri SF, Henderson WG, DePalma RG, et al. Determinants of long-term survival after major surgery and the adverse effect of postoperative complications. Ann Surg 2005; 242:326–341.
14. Hamel MB, Henderson WG, Khuri SF, et al. Surgical outcomes for patients aged 80 and older: morbidity and mortality from major noncardiac surgery. J Am Geriatr Soc 2005; 53:424–429.
15. Polanczyk CA, Marcantonio E, Goldman L, et al. Impact of age on perioperative complications and length of stay in patients undergoing noncardiac surgery. Ann Intern Med 2001; 134:637–643.
16. Freundlich RE, Maile MD, Sferra JJ, et al. Complications associated with mortality in the national surgical quality improvement program database. Anesth Analg 2018; 127:55–62.
17. Silber JH, Rosenbaum PR, Romano PS, et al. Hospital teaching intensity, patient race, and surgical outcomes. Arch Surg 2009; 144:113–120.
18. Aiken LH, Sloane DM, Bruyneel L, et al. Nurse staffing and education and hospital mortality in nine European countries: a retrospective observational study. Lancet 2014; 383:1824–1830.
19. Aiken LH, Clarke SP, Cheung RB, et al. Educational levels of hospital nurses and surgical patient mortality. JAMA 2003; 290:1617–1623.
20. Shah R, Attwood K, Arya S, et al. Association of frailty with failure to rescue after low-risk and high-risk inpatient surgery. JAMA Surg 2018; 153:e180214.
21. Futier E, Lefrant J-Y, Guinot P-G, et al. Effect of individualized vs standard blood pressure management strategies on postoperative organ dysfunction among high-risk patients undergoing major surgery. JAMA 2017; 318:1346–1357.
22. Pronovost PJ, Jenckes MW, Dorman T, et al. Organizational characteristics of intensive care units related to outcomes of abdominal aortic surgery. JAMA 1999; 281:1310–1317.
23. de Vries EN, Prins HA, Crolla RM, et al. Effect of a comprehensive surgical safety system on patient outcomes. N Engl J Med 2010; 363:1928–1937.
24. Eichenberger AS, Haller G, Cheseaux N, et al. A clinical pathway in a postanaesthesia care unit to reduce length of stay, mortality and unplanned intensive care unit admission. Eur J Anaesthesiol 2011; 28:859–866.
25. Hall DE, Arya S, Schmid KK, et al. Association of a frailty screening initiative with postoperative survival at 30, 180, and 365 days. JAMA Surg 2017; 152:233–240.
26. Kahan BC, Koulenti D, Arvaniti K, et al. Critical care admission following elective surgery was not associated with survival benefit: prospective analysis of data from 27 countries. Intensive Care Med 2017; 43:971–979.
27. Wunsch H, Gershengorn HB, Cooke CR, et al. Use of intensive care services for medicare beneficiaries undergoing major surgical procedures. Anesthesiology 2016; 124:899–907.
28. Guidet B, Leblanc G, Simon T, et al. Effect of systematic intensive care unit triage on long-term mortality among critically ill elderly patients in France: a randomized clinical trial. JAMA 2017; 318:1450–1459.
29. Selye H. Stress and the general adaptation syndrome. Br Med J 1950; 1:1383–1392.
30. Brame AL, Singer M. Stressing the obvious? An allostatic look at critical illness. Crit Care Med 2010; 38:S600–S607.
31. Chernow B, Alexander HR, Smallridge RC, et al. Hormonal responses to graded surgical stress. Arch Intern Med 1987; 147:1273–1278.
32. Wong DL, Tai TC, Wong-Faull DC, et al. Adrenergic responses to stress: transcriptional and posttranscriptional changes. Ann N Y Acad Sci 2008; 1148:249–256.
33. Desborough JP. The stress response to trauma and surgery. Br J Anaesth 2000; 85:109–117.
34. Alazawi W, Pirmadjid N, Lahiri R, et al. Inflammatory and immune responses to surgery and their clinical impact. Ann Surg 2016; 264:73–80.
35. Liu X, Yu Y, Zhu S. Inflammatory markers in postoperative delirium (POD) and cognitive dysfunction (POCD): a meta-analysis of observational studies. PLoS One 2018; 13:e0195659.
36. Ackland GL, Abbott TEF, Cain D, et al. Preoperative systemic inflammation and perioperative myocardial injury: prospective observational multicentre cohort study of patients undergoing noncardiac surgery. Br J Anaesth 2019; 122:180–187.
37. Goren O, Matot I. Perioperative acute kidney injury. Br J Anaesth 2015; 115 (Suppl 2):ii3–ii14.
38. Andreis DT, Singer M. Catecholamines for inflammatory shock: a Jekyll-and-Hyde conundrum. Intensive Care Med 2016; 42:1387–1397.
39. Devereaux PJ, Sessler DI. Cardiac complications in patients undergoing major noncardiac surgery. N Engl J Med 2015; 373:2258–2269.
40. Bartels K, Karhausen J, Clambey ET, et al. Perioperative organ injury. Anesthesiology 2013; 119:1474–1489.
41. Bainbridge D, Martin J, Arango M, et al. Evidence-based Peri-operative Clinical Outcomes Research G. Perioperative and anaesthetic-related mortality in developed and developing countries: a systematic review and meta-analysis. Lancet 2012; 380:1075–1081.
42. Serpa Neto A, Hemmes SN, Barbas CS, et al. Incidence of mortality and morbidity related to postoperative lung injury in patients who have undergone abdominal or thoracic surgery: a systematic review and meta-analysis. Lancet Respir Med 2014; 2:1007–1015.
43. Devereaux PJ, Biccard BM, Sigamani A, et al. Writing Committee for the VISION Study Investigators. Association of postoperative high-sensitivity troponin levels with myocardial injury and 30-day mortality among patients undergoing noncardiac surgery. JAMA 2017; 317:1642–1651.
44. Silber JH, Williams SV, Krakauer H, et al. Hospital and patient characteristics associated with death after surgery. A study of adverse occurrence and failure to rescue. Med Care 1992; 30:615–629.
45. Massarweh NN, Kougias P, Wilson MA. Complications and failure to rescue after inpatient noncardiac surgery in the veterans affairs health system. JAMA Surg 2016; 151:1157–1165.
46. Lee L, Mata J, Ghitulescu GA, et al. Cost-effectiveness of enhanced recovery versus conventional perioperative management for colorectal surgery. Ann Surg 2015; 262:1026–1033.
47. Portinari M, Ascanelli S, Targa S, et al. Impact of a colorectal enhanced recovery program implementation on clinical outcomes and institutional costs: a prospective cohort study with retrospective control. Int J Surg 2018; 53:206–213.
48. Gamil M, Fanning A. The first 24 h after surgery. A study of complications after 2153 consecutive operations. Anaesthesia 1991; 46:712–715.
49. Kim M, Li G. Postoperative complications affecting survival after cardiac arrest in general surgery patients. Anesth Analg 2018; 126:858–864.
50. Ghaferi AA, Birkmeyer JD, Dimick JB. Variation in hospital mortality associated with inpatient surgery. N Engl J Med 2009; 361:1368–1375.
51. Pradarelli JC, Healy MA, Osborne NH, et al. Variation in medicare expenditures for treating perioperative complications: the cost of rescue. JAMA Surg 2016; 151:e163340.
52. De Hert S, Staender S, Fritsch G, et al. Preoperative evaluation of adults undergoing elective noncardiac surgery: updated guideline from the European Society of Anaesthesiology. Eur J Anaesthesiol 2018; 35:407–465.
53. Pham C, Gibb C, Field J, et al. Managing high-risk surgical patients: modifiable co-morbidities matter. ANZ J Surg 2014; 84:925–931.
54. Baldini G, Ferreira V, Carli F. Preoperative preparations for enhanced recovery after surgery programs: a role for prehabilitation. Surg Clin North Am 2018; 98:1149–1169.
55. Moran J, Guinan E, McCormick P, et al. The ability of prehabilitation to influence postoperative outcome after intra-abdominal operation: a systematic review and meta-analysis. Surgery 2016; 160:1189–1201.
56. Barberan-Garcia A, Ubre M, Roca J, et al. Personalised prehabilitation in high-risk patients undergoing elective major abdominal surgery: a randomized blinded controlled trial. Ann Surg 2018; 267:50–56.
57. Feldman LS, Carli F. From preoperative assessment to preoperative optimization of frailty. JAMA Surg 2018; 153:e180213.
58. Gurlit S, Gogol M. Prehabilitation is better than cure. Curr Opin Anaesthesiol 2019; 32:108–115.
59. Milder DA, Pillinger NL, Kam PCA. The role of prehabilitation in frail surgical patients: a systematic review. Acta Anaesthesiol Scand 2018; 62:1356–1366.
60. Oshima Lee E, Emanuel EJ. Shared decision making to improve care and reduce costs. N Engl J Med 2013; 368:6–8.
61. Hoffmann TC, Del Mar C. Clinicians’ expectations of the benefits and harms of treatments, screening, and tests: a systematic review. JAMA Intern Med 2017; 177:407–419.
62. Taylor LJ, Nabozny MJ, Steffens NM, et al. A framework to improve surgeon communication in high-stakes surgical decisions: best case/worst case. JAMA Surg 2017; 152:531–538.
63. Minhas A, Jones G, Pallazola V, et al. Discordance of patient and provider perceptions of the meaning of verbal estimates of perioperative risk. Perioper Care Oper Room Manag 2018; 13:18–23.
64. Munoz M, Acheson AG, Bisbe E, et al. An international consensus statement on the management of postoperative anaemia after major surgical procedures. Anaesthesia 2018; 73:1418–1431.
65. American Society of Anesthesiologists Task Force on Perioperative Blood Management. Practice guidelines for perioperative blood management: an updated report by the American Society of Anesthesiologists Task Force on Perioperative Blood Management. Anesthesiology 2015; 122:241–275.
66. Mueller MM, Van Remoortel H, Meybohm P, et al. Patient blood management: recommendations from the 2018 Frankfurt consensus conference. JAMA 2019; 321:983–997.
67. Futier E, Constantin J-M, Paugam-Burtz C, et al. A trial of intraoperative low-tidal-volume ventilation in abdominal surgery. N Engl J Med 2013; 369:428–437.
68. Myles PS, Bellomo R, Corcoran T, et al. Restrictive versus liberal fluid therapy for major abdominal surgery. N Engl J Med 2018; 378:2263–2274.
69. Sessler DI. Perioperative thermoregulation and heat balance. Lancet 2016; 387:2655–2664.
70. Munoz-Price LS, Bowdle A, Johnston BL, et al. Infection prevention in the operating room anesthesia work area. Infect Control Hosp Epidemiol 2019; 40:1–17.
71. MacKenzie KK, Britt-Spells AM, Sands LP, et al. Processed electroencephalogram monitoring and postoperative delirium: a systematic review and meta-analysis. Anesthesiology 2018; 129:417–427.
72. Ray JJ, Degnan M, Rao KA, et al. Incidence and operative factors associated with discretional postoperative mechanical ventilation after general surgery. Anesth Analgesia 2018; 126:489–494.
73. Jaber S, Lescot T, Futier E, et al. Effect of noninvasive ventilation on tracheal reintubation among patients with hypoxemic respiratory failure following abdominal surgery. JAMA 2016; 315:1345–1353.
74. Annane D, Ouanes-Besbes L, de Backer D, et al. A global perspective on vasoactive agents in shock. Intensive Care Med 2018; 44:833–846.
75. Silversides JA, Major E, Ferguson AJ, et al. Conservative fluid management or deresuscitation for patients with sepsis or acute respiratory distress syndrome following the resuscitation phase of critical illness: a systematic review and meta-analysis. Intensive Care Med 2017; 43:155–170.
76. Weimann A, Braga M, Carli F, et al. ESPEN guideline: clinical nutrition in surgery. Clin Nutr 2017; 36:623–650.
77. Schaller SJ, Anstey M, Blobner M, et al. Early, goal-directed mobilisation in the surgical intensive care unit: a randomised controlled trial. Lancet 2016; 388:1377–1388.
78. Boden I, Skinner EH, Browning L, et al. Preoperative physiotherapy for the prevention of respiratory complications after upper abdominal surgery: pragmatic, double blinded, multicentre randomised controlled trial. BMJ 2018; 360:j5916.
79. Fields A, Huang J, Schroeder D, et al. Agitation in adults in the postanaesthesia care unit after general anaesthesia. Br J Anaesth 2018; 121:1052–1058.
80. Zhang P, Hu WL, Cheng B, et al. A systematic review and meta-analysis comparing immediate and delayed catheter removal following uncomplicated hysterectomy. Int Urogynecol J 2015; 26:665–674.
81. Porter ME. What is value in healthcare? N Engl J Med 2010; 363:2477–2481.
82. Cecconi M, Corredor C, Arulkumaran N, et al. Clinical review: goal-directed therapy-what is the evidence in surgical patients? The effect on different risk groups. Crit Care 2013; 17:209.
83. Santhirapala R, Fleisher LA, Grocott MPW. Choosing Wisely: just because we can, does it mean we should? Br J Anaesth 2019; 122:306–310.
84. Finks JF, Osborne NH, Birkmeyer JD. Trends in hospital volume and operative mortality for high-risk surgery. N Engl J Med 2011; 364:2128–2137.
85. Smilowitz NR, Gupta N, Guo Y, et al. Perioperative acute myocardial infarction associated with noncardiac surgery. Eur Heart J 2017; 38:2409–2417.
86. Smilowitz NR, Gupta N, Ramakrishna H, et al. Perioperative major adverse cardiovascular and cerebrovascular events associated with noncardiac surgery. JAMA Cardiol 2017; 2:181–182.
87. Bateman BT, Schmidt U, Berman MF, et al. Temporal trends in the epidemiology of severe postoperative sepsis after elective surgery: a large, nationwide sample. Anesthesiology 2010; 112:917–925.
88. Ou L, Chen J, Burrell T, et al. Incidence and mortality of postoperative sepsis in New South Wales, Australia, 2002–2009. Crit Care Resusc 2016; 18:9–16.
89. Walker D, Wagstaff D, McGuckin D, et al. Mixed-methods evaluation of the Perioperative Medicine Service for High-Risk Patients Implementation Pilot (POMSHIP): a study protocol. BMJ Open 2018; 8:e021647.
90. Alem N, Kain Z. Evolving healthcare delivery paradigms and the optimization of ‘value’ in anesthesiology. Curr Opin Anaesthesiol 2017; 30:223–229.
91. Moonesinghe SR, Mythen MG, Das P, et al. Risk stratification tools for predicting morbidity and mortality in adult patients undergoing major surgeryqualitative systematic review. Anesthesiology 2013; 119:959–981.
92. Le Manach Y, Collins G, Rodseth R, et al. Preoperative Score to Predict Postoperative Mortality (POSPOM): derivation and validation. Anesthesiology 2016; 124:570–579.
93. Chan DXH, Sim YE, Chan YH, et al. Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study. BMJ Open 2018; 8:e019427.
94. Protopapa KL, Simpson JC, Smith NC, et al. Development and validation of the Surgical Outcome Risk Tool (SORT). Br J Surg 2014; 101:1774–1783.
95. Bilimoria KY, Liu Y, Paruch JL, et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg 2013; 217:833–842.
96. Moran J, Wilson F, Guinan E, et al. Role of cardiopulmonary exercise testing as a risk-assessment method in patients undergoing intra-abdominal surgery: a systematic review. Br J Anaesth 2016; 116:177–191.
97. Wijeysundera DN, Pearse RM, Shulman MA, et al. Assessment of functional capacity before major noncardiac surgery: an international, prospective cohort study. Lancet 2018; 391:2631–2640.
98. Copeland CC, Young A, Grogan T, et al. Preoperative risk stratification of critically ill patients. J Clin Anesth 2017; 39:122–127.
99. Glance LG, Lustik SJ, Hannan EL, et al. The Surgical Mortality Probability Model: derivation and validation of a simple risk prediction rule for noncardiac surgery. Ann Surg 2012; 255:696–702.
100. Scott S, Lund JN, Gold S, et al. An evaluation of POSSUM and P-POSSUM scoring in predicting postoperative mortality in a level 1 critical care setting. BMC Anesthesiol 2014; 14:104.
101. Liu Y, Cohen ME, Hall BL, et al. Evaluation and enhancement of calibration in the american college of surgeons NSQIP surgical risk calculator. J Am Coll Surg 2016; 223:231–239.
102. Flaatten H, De Lange DW, Morandi A, et al. The impact of frailty on ICU and 30-day mortality and the level of care in very elderly patients (≥80 years). Intensive Care Med 2017; 43:1820–1828.
103. Ford MK, Beattie WS, Wijeysundera DN. Systematic review: prediction of perioperative cardiac complications and mortality by the revised cardiac risk index. Ann Intern Med 2010; 152:26–35.
104. Cohn SL, Fernandez Ros N. Comparison of 4 cardiac risk calculators in predicting postoperative cardiac complications after noncardiac operations. Am J Cardiol 2018; 121:125–130.
105. Glance LG, Faden E, Dutton RP, et al. Impact of the choice of risk model for identifying low-risk patients using the 2014 American College of Cardiology/American Heart Association Perioperative Guidelines. Anesthesiology 2018; 129:889–900.
106. Gupta PK, Gupta H, Sundaram A, et al. Development and validation of a risk calculator for prediction of cardiac risk after surgery. Circulation 2011; 124:381–387.
107. Canet J, Gallart L, Gomar C, et al. Prediction of postoperative pulmonary complications in a population-based surgical cohort. Anesthesiology 2010; 113:1338–1350.
108. Kheterpal S, Tremper KK, Heung M, et al. Development and validation of an acute kidney injury risk index for patients undergoing general surgery: results from a national data set. Anesthesiology 2009; 110:505–515.
109. Regenbogen SE, Ehrenfeld JM, Lipsitz SR, et al. Utility of the surgical apgar score: validation in 4119 patients. Arch Surg 2009; 144:30–36.
110. Gawande AA, Kwaan MR, Regenbogen SE, et al. An Apgar score for surgery. J Am Coll Surg 2007; 204:201–208.
111. Wanderer JP, Anderson-Dam J, Levine W, et al. Development and validation of an intraoperative predictive model for unplanned postoperative intensive care. Anesthesiology 2013; 119:516–524.
112. Aldrete JA. The postanesthesia recovery score revisited. J Clin Anesth 1995; 7:89–91.
113. Ellis SG, Shishehbor MH, Kapadia SR, et al. Enhanced prediction of mortality after percutaneous coronary intervention by consideration of general and neurological indicators. JACC Cardiovasc Interv 2011; 4:442–448.
114. Lee CK, Hofer I, Gabel E, et al. Development and validation of a deep neural network model for prediction of postoperative in-hospital mortality. Anesthesiology 2018; 129:649–662.
115. Bihorac A, Ozrazgat-Baslanti T, Ebadi A, et al. MySurgeryRisk: development and validation of a machine-learning risk algorithm for major complications and death after surgery. Ann Surg 2019; 269:652–662.
116. Weber M, Luchner A, Manfred S, et al. Incremental value of high-sensitive troponin T in addition to the revised cardiac index for peri-operative risk stratification in noncardiac surgery. Eur Heart J 2013; 34:853–862.
117. Nagele P, Brown F, Gage BF, et al. High-sensitivity cardiac troponin T in prediction and diagnosis of myocardial infarction and long-term mortality after noncardiac surgery. Am Heart J 2013; 166:325–332.
118. Kopec M, Duma A, Helwani MA, et al. Improving prediction of postoperative myocardial infarction with high-sensitivity cardiac troponin T and NT-proBNP. Anesth Analg 2017; 124:398–405.
119. Puelacher C, Lurati Buse G, Seeberger D, et al. Perioperative myocardial injury after noncardiac surgery: incidence, mortality, and characterization. Circulation 2018; 137:1221–1232.
120. Gillmann HJ, Meinders A, Grohennig A, et al. Perioperative levels and changes of high-sensitivity troponin T are associated with cardiovascular events in vascular surgery patients. Crit Care Med 2014; 42:1498–1506.
121. Rodseth RN, Biccard BM, Le Manach Y, et al. The prognostic value of preoperative and postoperative B-type natriuretic peptides in patients undergoing noncardiac surgery: B-type natriuretic peptide and N-terminal fragment of pro-B-type natriuretic peptide: a systematic review and individual patient data meta-analysis. J Am Coll Cardiol 2014; 63:170–180.
122. Schrimpf C, Gillmann HJ, Sahlmann B, et al. Renal function interferes with copeptin in prediction of major adverse cardiac events in patients undergoing vascular surgery. PLoS One 2015; 10:e0123093.
123. Mauermann E, Bolliger D, Seeberger E, et al. Incremental value of preoperative copeptin for predicting myocardial injury. Anesth Analg 2016; 123:1363–1371.
124. Kamber F, Mauermann E, Seeberger E, et al. Peri-operative copeptin concentrations and their association with myocardial injury after vascular surgery: a prospective observational cohort study. Eur J Anaesthesiol 2018; 35:682–690.
125. Jarai R, Mahla E, Perkmann T, et al. Usefulness of preoperative copeptin concentrations to predict postoperative outcome after major vascular surgery. Am J Cardiol 2011; 108:1188–1195.
126. Yang HS, Hur M, Yi A, et al. Prognostic role of high-sensitivity cardiac troponin I and soluble suppression of tumorigenicity-2 in surgical intensive care unit patients undergoing noncardiac surgery. Ann Lab Med 2018; 38:204–211.
127. Handke J, Scholz AS, Gillmann HJ, et al. Elevated presepsin is associated with perioperative major adverse cardiovascular and cerebrovascular complications in elevated-risk patients undergoing noncardiac surgery: the leukocytes and cardiovascular perioperative events study. Anesth Analg 2019; 128:1344–1353.
128. Shen JT, Xu M, Wu Y, et al. Association of preoperative troponin levels with major adverse cardiac events and mortality after noncardiac surgery: a systematic review and meta-analysis. Eur J Anaesthesiol 2018; 35:815–824.
129. Noordzij PG, van Geffen O, Dijkstra IM, et al. High-sensitive cardiac troponin T measurements in prediction of noncardiac complications after major abdominal surgery. Br J Anaesth 2015; 114:909–918.
130. Zhang Z, Lu B, Sheng X, et al. Cystatin C in prediction of acute kidney injury: a systemic review and meta-analysis. Am J Kidney Dis 2011; 58:356–365.
131. Ho J, Tangri N, Komenda P, et al. Urinary, plasma, and serum biomarkers’ utility for predicting acute kidney injury associated with cardiac surgery in adults: a meta-analysis. Am J Kidney Dis 2015; 66:993–1005.
132. Zhou F, Luo Q, Wang L, et al. Diagnostic value of neutrophil gelatinase-associated lipocalin for early diagnosis of cardiac surgery-associated acute kidney injury: a meta-analysis. Eur J Cardiothorac Surg 2016; 49:746–755.
133. Jia HM, Zheng Y, Huang LF, et al. Derivation and validation of plasma endostatin for predicting renal recovery from acute kidney injury: a prospective validation study. Crit Care 2018; 22:305.
134. Meyer CP, Rios-Diaz AJ, Dalela D, et al. The association of hypoalbuminemia with early perioperative outcomes – a comprehensive assessment across 16 major procedures. Am J Surg 2017; 214:871–883.
135. Gibbs J, Cull W, Henderson W, et al. Preoperative serum albumin level as a predictor of operative mortality and morbidity: results from the National VA Surgical Risk Study. Arch Surg 1999; 134:36–42.
136. Wu WC, Schifftner TL, Henderson WG, et al. Preoperative hematocrit levels and postoperative outcomes in older patients undergoing noncardiac surgery. JAMA 2007; 297:2481–2488.
137. Fowler AJ, Ahmad T, Abbott TEF, et al. Association of preoperative anaemia with postoperative morbidity and mortality: an observational cohort study in low-, middle-, and high-income countries. Br J Anaesth 2018; 121:1227–1235.
138. Musallam KM, Tamim HM, Richards T, et al. Preoperative anaemia and postoperative outcomes in noncardiac surgery: a retrospective cohort study. Lancet 2011; 378:1396–1407.
139. Straatman J, Harmsen AM, Cuesta MA, et al. Predictive value of C-reactive protein for major complications after major abdominal surgery: a systematic review and pooled-analysis. PLoS One 2015; 10:e0132995.
140. Kristensen SD, Knuuti J, Saraste A, et al. 2014 ESC/ESA Guidelines on noncardiac surgery: cardiovascular assessment and management: the Joint Task Force on noncardiac surgery: cardiovascular assessment and management of the European Society of Cardiology (ESC) and the European Society of Anaesthesiology (ESA). Eur J Anaesthesiol 2014; 31:517–573.
141. Fleisher LA, Fleischmann KE, Auerbach AD, et al. 2014 ACC/AHA Guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation 2014; 130:e278–e333.
142. Makary MA, Segev DL, Pronovost PJ, et al. Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg 2010; 210:901–908.
143. McIsaac DI, Taljaard M, Bryson GL. Frailty as a predictor of death or new disability after surgery: a prospective cohort study. Ann Surgery 2018; [Epub ahead of print].
144. Pua YH, Ong PH. Association of early ambulation with length of stay and costs in total knee arthroplasty: retrospective cohort study. Am J Phys Med Rehabil 2014; 93:962–970.
145. Foss NB, Kristensen MT, Kehlet H. Prediction of postoperative morbidity, mortality and rehabilitation in hip fracture patients: the cumulated ambulation score. Clin Rehabil 2006; 20:701–708.
146. Rees J, Bobridge K, Cash C, et al. Delayed postoperative diet is associated with a greater incidence of prolonged postoperative ileus and longer stay in hospital for patients undergoing gastrointestinal surgery. Nutr Diet 2018; 75:24–29.
147. Sun Z, Sessler DI, Dalton JE, et al. Postoperative hypoxemia is common and persistent: a prospective blinded observational study. Anesth Analg 2015; 121:709–715.
148. Shin CH, Long DR, McLean D, et al. Effects of intraoperative fluid management on postoperative outcomes. Ann Surg 2018; 267:1084–1092.
149. Pinto BB, Walder B. Heart rate as a predictor and a therapeutic target of cardiac ischemic complications after noncardiac surgery. A narrative review. Trends Anaesth Crit Care 2018; 22:26–32.
150. Steinmetz J, Christensen KB, Lund T, et al. Group I. Long-term consequences of postoperative cognitive dysfunction. Anesthesiology 2009; 110:548–555.
151. Sprung J, Roberts RO, Weingarten TN, et al. Postoperative delirium in elderly patients is associated with subsequent cognitive impairment. Br J Anaesth 2017; 119:316–323.
152. Hamilton GM, Wheeler K, Di Michele J, et al. A systematic review and meta-analysis examining the impact of incident postoperative delirium on mortality. Anesthesiology 2017; 127:78–88.
153. Morris ZS, Wooding S, Grant J. The answer is 17 years, what is the question: understanding time lags in translational research. J R Soc Med 2011; 104:510–520.
154. Lane-Fall MB, Cobb BT, Cene CW, et al. Implementation science in perioperative care. Anesthesiol Clin 2018; 36:1–15.
155. Royal College of Anaesthetists. Guidelines for the provision of anaesthetic services (GPAS). 2019. [Accessed 19 March 2019].
156. National Institute for Health and Care Excellence (NICE). NICE guidance. [Accessed 19 March 2019].
157. Smarter medicine – choosing wisely Switzerland. «Smarter medicine»: la liste «Top-5» de la SSAR. Bulletin des Médecins Suisses 2018;99:1574–1575.
158. Ichai C, Vinsonneau C, Souweine B, et al. Acute kidney injury in the perioperative period and in intensive care units (excluding renal replacement therapies). Anaesth Crit Care Pain Med 2016; 35:151–165.
159. Thygesen K, Alpert JS, Jaffe AS, et al. Fourth universal definition of myocardial infarction. Eur Heart J 2019; 40:237–269.
160. Roffi M, Patrono C, Collet J-P, et al. 2015 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J 2016; 37:267–315.
161. Duceppe E, Parlow J, MacDonald P, et al. Canadian cardiovascular society guidelines on perioperative cardiac risk assessment and management for patients who undergo noncardiac surgery. Can J Cardiol 2017; 33:17–32.
162. Rhodes A, Evans LE, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock: 2016. Intensive Care Med 2017; 43:304–377.
163. Mohanty S, Rosenthal RA, Russell MM, et al. Optimal perioperative management of the geriatric patient: a best practices guideline from the American College of Surgeons NSQIP and the American Geriatrics Society. J Am Coll Surg 2016; 222:930–947.
164. Aldecoa C, Bettelli G, Bilotta F, et al. European Society of Anaesthesiology evidence-based and consensus-based guideline on postoperative delirium. Eur J Anaesthesiol 2017; 34:192–214.
165. Eckstein HH. European Society for Vascular Surgery guidelines on the management of atherosclerotic carotid and vertebral artery disease. Eur J Vasc Endovasc Surg 2018; 55:1–2.
166. Torres A, Niederman MS, Chastre J, et al. International ERS/ESICM/ESCMID/ALAT guidelines for the management of hospital-acquired pneumonia and ventilator-associated pneumonia: guidelines for the management of hospital-acquired pneumonia (HAP)/ventilator-associated pneumonia (VAP) of the European Respiratory Society (ERS), European Society of Intensive Care Medicine (ESICM), European Society of Clinical Microbiology and Infectious Diseases (ESCMID) and Asociacion Latinoamericana del Torax (ALAT). Eur Respir J 2017; 50:1700582.
167. Wedzicha JA, Calverley PMA, Albert RK, et al. Prevention of COPD exacerbations: a European Respiratory Society/American Thoracic Society guideline. Eur Respir J 2017; 50:1602265.
168. Siemieniuk RAC, Chu DK, Kim LH, et al. Oxygen therapy for acutely ill medical patients: a clinical practice guideline. BMJ 2018; 363:k4169.
169. O’Driscoll BR, Howard LS, Earis J, et al. British Thoracic Society Emergency Oxygen Guideline Group; BTS Emergency Oxygen Guideline Development Group. BTS guideline for oxygen use in adults in healthcare and emergency settings. Thorax 2017; 72:ii1–ii90.
170. Rochwerg B, Brochard L, Elliott MW, et al. Official ERS/ATS clinical practice guidelines: noninvasive ventilation for acute respiratory failure. Eur Respir J 2017; 50:1602426.
171. Kozek-Langenecker SA, Ahmed AB, Afshari A, et al. Management of severe perioperative bleeding: guidelines from the European Society of Anaesthesiology: first update 2016. Eur J Anaesthesiol 2017; 34:332–395.
172. Kozek-Langenecker SA, Afshari A, Albaladejo P, et al. Management of severe perioperative bleeding: guidelines from the European Society of Anaesthesiology. Eur J Anaesthesiol 2013; 30:270–382.
173. Duranteau J, Taccone FS, Verhamme P, et al. European guidelines on perioperative venous thromboembolism prophylaxis: intensive care. Eur J Anaesthesiol 2018; 35:142–146.
174. Ahmed A, Kozek-Langenecker S, Mullier F, et al. ESA VTE Guidelines Task Force. European guidelines on perioperative venous thromboembolism prophylaxis: patients with preexisting coagulation disorders and after severe perioperative bleeding. Eur J Anaesthesiol 2018; 35:96–107.
175. Ament SMC, Gillissen F, Moser A, et al. Factors associated with sustainability of 2 quality improvement programs after achieving early implementation success. A qualitative case study. J Eval Clin Pract 2017; 23:1135–1143.
176. Hulscher ME, Schouten LM, Grol RP, et al. Determinants of success of quality improvement collaboratives: what does the literature show? BMJ Qual Saf 2013; 22:19–31.
177. Donabedian A. Evaluating the quality of medical care. Milbank Mem Fund Q 1966; 44:166–206.
178. Walder B. Improvement of perioperative care for better outcomes after surgery. Eur J Anaesthesiol 2011; 28:7–9.
179. Stone AB, Yuan CT, Rosen MA, et al. Barriers to and facilitators of implementing enhanced recovery pathways using an implementation framework: a systematic review. JAMA Surg 2018; 153:270–279.
180. Tabak RG, Khoong EC, Chambers DA, et al. Bridging research and practice: models for dissemination and implementation research. Am J Prev Med 2012; 43:337–350.
181. Field B, Booth A, Ilott I, et al. Using the Knowledge to Action Framework in practice: a citation analysis and systematic review. Implement Sci 2014; 9:172.
182. Ljungqvist O, Scott M, Fearon KC. Enhanced recovery after surgery: a review. JAMA Surg 2017; 152:292–298.
183. Simpson JC, Moonesinghe SR. Introduction to the postanaesthetic care unit. Perioper Med 2013; 2:5.
184. Nijbroek SG, Schultz MJ, Hemmes SNT. Prediction of postoperative pulmonary complications. Curr Opin Anaesthesiol 2019; 32:443–451.
© 2019 European Society of Anaesthesiology