Introduction
Depression is a common psychiatric condition in patients with medical illnesses. Prevalence rates of clinically significant depressive states are up to four times higher in people with diverse medical conditions than in general population samples, and, depending on severity and chronicity of the medical disease, frequency of depression ranges between 15 and 50%.1–5 Recent studies found that depression worsens the prognosis of medical illness and has an impact on outcomes in surgical patients.2,4,6–9 However, little is known about the relationship between preoperative depression and other health risk factors that have proven clinically relevant in anaesthesiology. In order to provide effective treatment options for depression, both anaesthesiologists and psychotherapists need to gather more detailed information about how depression is associated with essential anaesthesiological health risk factors, above all hazardous alcohol consumption and tobacco smoking,10–12 as well as indicators of preoperative physical health status such as obesity,13 physical exercise14 and the ASA (American Society of Anesthesiologists) physical status classification system as an overall indicator for physical health.15 An examination of preoperative depressive states in surgical patients needs also to clarify the role of both risk factors and protective factors that have shown to be associated with depression in the general population. These factors include sex,16 age,17 specific sociodemographic characteristics (e.g. partnership status, education, employment status),18 sleep disturbances,19 subjective experience of health as one component of health-related quality of life,20,21 as well as the personality disposition ‘sense of coherence’. This construct was repeatedly found to be highly correlated with depression and describes the extent to which people experience that they are capable of understanding, managing and finding a meaning in what happens around them.22,23 Finally, in order to make an estimate of the relationship of depression and surgical recovery and healthcare use, it is important to examine to which extent preoperative depressive states have an influence on outcomes in surgical patients.8
This study investigated the frequency of depression, its association with essential health risk factors and its clinical relevance in preoperative anaesthesiological assessment by using a computerised self-assessment of patients’ lifestyle risks.
The primary objectives of the study were to investigate the frequency of depressive states by using the short depression screening tool WHO-5 (World Health Organization 5-item Well-Being Index24 ) in preoperative anaesthesiological assessment and to show its clinical impact with regard to hospital length of stay (LOS). The secondary objectives were to examine whether patients scoring high vs. low on the WHO-5 differ with regard to sex, age, partnership, education, employment status, alcohol use disorders, tobacco smoking, BMI, physical exercise, ASA classification, surgical field, severity of sleeping disturbance, the patients’ experience of subjective health, and sense of coherence and to determine which of these risk or protective factors show a statistically significant, independent impact for the prediction of depression when entered simultaneously into a logistic regression model of depression.
Patients and methods
Setting
The study was conducted in the preoperative assessment clinics of the Charité – University Medicine Berlin, Campus Charité Mitte and Campus Virchow Klinikum, Berlin, Germany, between February 2006 and December 2007. The Charité – University Medicine is one of the largest hospitals in Europe performing approximately 65 000 general anaesthesias per year. Each patient undergoing elective surgery is examined by an anaesthetist implying two principal goals: clarification of anaesthesia-related risks of the intended surgery and the evaluation of the patient's individual level of risk. A total of 43 604 patients were seen in the preoperative assessment clinic during the study period.
Patients and study design
The present study was designed as a prospective observational study. After the approval of the institutional review board (application number EA1/23/2004) and after having given written informed consent, 5429 consecutive patients were enrolled in the study (Fig. 1 ).
Fig. 1: no caption available.
During the study period, a total of 16 687 patients were assessed for eligibility, with 3912 refusing to participate and 7067 not being eligible according to inclusion/exclusion criteria. Inclusion criteria are as follows: age at least 18 years, written informed consent, sufficient knowledge of the German language and willing/capable of using a computer. Exclusion criteria are as follows: participation in another clinical trial, members of the hospital staff, admitted in police custody, relatives of the study team, surgery with an emergency or urgent indication. Patients who had not been seen in the preoperative assessment clinic but had been seen and examined by an anaesthetist on the ward were not recruited. Data were excluded from analyses (n = 279) in cases where patients had not completed the electronic questionnaire or had provided insufficient data. Complete data were available for 5429 participants from all surgical fields (see Fig. 1 for details of the inclusion process).
Measurements
Upon receipt of written informed consent, the patients completed a computer-based self-assessment of lifestyle risks as reported previously.25–28 All items were multiple choice questions that could be answered by mouse only technique, so that keyboard typing was not required. The assessment covered the following domains.
Sociodemographic information includes sex, age, partnership status, level of education and current status of employment. Physical characteristics include body weight, height and taking regular physical exercise. Substance use includes tobacco smoking, computerised version of the AUDIT, a standardised screening instrument for excessive alcohol consumption (Alcohol Use Disorder Identification Test29 ). Depression-related factors include sleeping disturbances, current subjective health status (visual analogue scale of the European Quality of Life Questionnaire (EuroQOL30 ) and computerised version of the BASOC (Brief Assessment of Sense of Coherence31 ). Depression includes computerised version of the WHO-5.24,32 This short depression screening instrument has shown high reliability and validity in several recent studies.32–34 The five items of the WHO-5 measure self-report of psychological well-being during the past 2 weeks and cover mood, interests, energy, sleep and psychomotor functioning. Responses are rated on a 6-point Likert scale from 0 to 5 with sum scores ranging from 0 to 25, and higher scores indicating better well-being. A sum score of 13 or less indicates poor well-being24 and can be interpreted as a clinically relevant depressive state including the whole spectrum of depressive affect ranging from transient mood disturbance to full-blown depressive disorders. A detailed description of the computer-based self-assessment including all standardised measurements used in this study can be found in Supplemental Digital Content 1, measurements, https://links.lww.com/EJA/A21 .
The evaluation of patients’ perioperative risk according to the ASA physical status classification system was performed by the anaesthesiologists who did the preoperative assessment. Information on the surgical field was obtained from the electronic patient management system of the Charité Universitätsmedizin Berlin and consisted of the categories abdominothoracic surgery, peripheral surgery and neuro, head and neck surgery.
Outcome
As an indicator of physical recovery and healthcare use, hospital LOS was obtained from the electronic patient management system of the Charité Universitätsmedizin Berlin. LOS was measured in days and calculated by subtracting the date of admission to hospital from the date of discharge from hospital.
Statistical analysis
After testing the distribution of the observations for normality, results were expressed as mean ± standard deviation (SD) or median with interquartile range for metric data, as well as relative frequencies in percentage for qualitative data. Because distributions were skewed, group differences regarding metric data were tested with the non-parametric Mann–Whitney test. Frequencies were tested with the (exact) χ 2 test in contingency tables.
The primary objectives of this study were to determine how many patients score low (≤13) versus high (>13) on the WHO-5 and to examine whether these two groups with or without a clinically significant depressive state differ with regard to the outcome parameter hospital LOS. Therefore, patients were divided into two groups according to the WHO-5 cut-off: group 1 scoring 13 or less (‘patients with a clinically significant depressive state’) and group 2 scoring more than 13 (‘patients without a clinically significant depressive state’). In the next step, patients with a clinically significant depressive state and patients without a clinically significant depressive state were compared with regard to LOS using the Mann–Whitney test. Finally, we analysed whether group differences were dependant on age, sex, physical status and/or surgical field. This analysis was performed by logistic regression because distribution of LOS was skewed. Patients were divided into two groups showing LOS above versus below or equal to the median LOS of the total sample. A multivariate logistic regression model tested whether depression had a significant influence on the defined binary LOS variable when simultaneously including age, sex, ASA classification and surgical field as covariates.
The secondary objectives were to compare patients with or without a clinically significant depressive state regarding selected health risk factors and other baseline patient characteristics. Univariate analyses of health risk factors and baseline patient characteristics with respect to the mentioned groups were carried out using Mann–Whitney tests and (exact) χ 2 tests, respectively. All variables with a P value less than 0.10 in the univariate analyses were included in a multivariate logistic regression model in order to determine the significant (independent) influencing factors of depression. Regression coefficients (B) with standard errors (SE) and odds ratios (ORs) with 95% confidence intervals (CIs) were given.
All significance tests were accomplished with α equal to 5%, two-tailed, and, due to the exploratory nature of the study, P values were not adjusted for the number of tests that were performed. For all statistical analyses, the software SPSS Statistics, version 18, was used (SPSS 2010).
Results
Out of the included 5429 patients, 1610 (29.7%; 95% CI 28.5–30.9%) showed WHO-5 scores of less than or equal to 13 indicating a clinically relevant depressive state, and 3819 patients (70.3%; 95% CI 69.1–71.5%) had WHO-5 scores above 13 indicating positive well-being.
Hospital LOS of patients with depression (n = 1238, median LOS 6.0 days, interquartile range 3.1–12.0 days) was statistically significantly longer than hospital LOS of patients without depression (n = 3069, median LOS 4.8 days, interquartile range 2.3–8.1 days; P < 0.001, Fig. 2 ). A multivariate logistic regression model with the dependent variable ‘above versus below or equal to the median LOS’ revealed that the influence of depression on LOS persisted [OR = 1.52 (95% CI 1.32–1.75), P < 0.001] when simultaneously including the covariates sex [OR = 0.95 (95% CI 0.84–1.08), P = 0.435], age [OR = 1.019 (95% CI 1.015–1.023), P < 0.001], ASA classification – ASA I, II versus III, IV [OR = 2.49 (95% CI 2.09–2.97), P < 0.001] and surgical field [P < 0.001; abdominothoracic surgery versus rest: OR = 0.88 (95% CI 0.75–1.03), P = 0.118; peripheral surgery versus rest: OR = 1.32 (95% CI 1.12–1.56), P = 0.001].
Fig. 2: no caption available.
Univariate analyses showed that patients with clinically relevant depressive states differed statistically significantly from patients without depression with regard to all analysed sociodemographic and clinical characteristics except for BMI and surgical field (Table 1 ). Differences in indicators of preoperative health and surgical field are shown in Fig. 3 . Interestingly, patients with depression had considerably worse subjective health and a smaller percentage taking physical exercise; however, differences were less strong with regard to physical health as estimated by the ASA classification, as well as the categories of surgical field (Fig. 3 ).
Table 1: Sociodemographic and clinical characteristics of patient sample (n = 5429) and comparison of patient groups scoring below and above the WHO-5 cut-off for clinically relevant depressive states
Fig. 3: no caption available.
All sociodemographic and clinical characteristics with a P less than 0.10 in the univariate analysis were entered simultaneously in a multivariate logistic regression model. As shown in Table 2 , six factors continued to be statistically significantly and independently associated with depression: less subjective health (P < 0.001), taking less physical exercise (P < 0.001), less sense of coherence (P < 0.001), more severe sleeping disturbances (P < 0.001), surgical field (P = 0.001) and younger age (P = 0.007).
Table 2: Multivariate analysis of sociodemographic characteristics and health risk factors associated with depression (n = 5010+ )
Discussion
The present study found that clinically significant depressive states are frequent conditions in surgical patients of preoperative anaesthesiological assessment and are associated with an increased LOS. The prevalence of 29.7% lies in the middle range of the depression rates between 15 and 50% that were reported for patients with different medical conditions in previous studies.1–5 This prevalence rate is moderately higher than the prevalence found in a recent study that also used the cut-off of 13 or less of the WHO-5 for depression screening: Aujla et al. 35 report depression rates of 21.3, 26.0 and 25.1% in people with type 2 diabetes mellitus, impaired glucose regulation and normal glucose tolerance, respectively. Correspondingly, the median WHO-5 score of 17 in this sample of surgical patients is lower than the median of 19 of a large German population sample (N = 2473).36
Hospital LOS represents an indicator of physical recovery, the related healthcare use and associated costs. Because it is multiply determined, the influence of specific factors on LOS was found to be significant but small in previous studies on patients with cardiovascular surgery.37–39 To our knowledge, the current study is the first one to report a longer LOS in depressed patients in the preoperative anaesthesiological assessment clinic who came from diverse surgical specialties. The risk of having a LOS above the median was 52% higher in patients with depression than in patients without depression even when factors were taken into account that have proven to have an influence on surgical outcomes such as age,8 sex,8 surgical field40 and ASA classification.15,41
The finding that depression was associated with a worse socioeconomic, psychological and physical state confirms that it is a serious condition.1,3,5 Independent factors known to be correlates of depression in general population were also identified in our study: sleep disturbances,19 sense of coherence,23 subjective experience of health20,21 as well as regular physical exercise.42 The influence of age was relatively small and not clinically relevant. In contrast to subjective experience of health and regular physical exercise, surgical field and physical health as estimated by the ASA classification were only weakly associated with depression, even though these two factors had an impact on outcomes in this study and previous research.15,40,41 However, the influence of ASA classification and surgery might have been greater in a sample with a higher percentage of patients in the ASA categories III and IV, and when analysing the effects of specific surgical procedures and diagnoses instead of surgical field. Low preoperative subjective well-being may, for example, be influenced by the worries of patients concerning the reason for the planned surgery.
Interestingly, also tobacco smoking and alcohol use disorders did not show any independent association with depression, even though there is evidence from previous studies that depression is frequent in people with substance use disorders (for overview see 43,44 ). These results suggest that depressive affect, smoking, problem drinking and general physical health as estimated by the ASA classification are factors that have independently of each other an impact on outcomes in surgical patients.
Methodological limitations
Preoperative assessment clinics are a busy setting with limited resources of time and personnel, so that it is not possible to make comprehensive psychiatric examinations in large patient samples. Brief computer-based self-assessment represents a feasible instrument to measure lifestyle and health risk factors in this special setting. The WHO-5, a brief screening instrument, can easily be integrated in this assessment and gives information about the current depressive state of patients. However, with this measurement, clinicians cannot make diagnoses of mood disorder according to International Classification of Diseases-10 or Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision.24,32 In this study, a clinically relevant depressive state was defined by a WHO-5 sum score of 13 or less indicating a considerable loss of positive mood, energy and interest in activities, as well as substantial decrease of sleep quality and psychomotor functioning. Patients who show a relevant depressive state during the past 2 weeks according to their answers in the WHO-5 may show either subthreshold depressive syndromes, transient elevated depressive symptoms or a specific depressive disorder for more than 2 weeks.33,34 However, a WHO-5 sum score of 13 or less does not specify these states in terms of specific psychiatric disorders. Therefore, this screening will not allow including the diagnosis depression in the patient's chart. This is very important to consider for the patients and the physicians.
The inclusion tree of this study requires further consideration. Out of all patients assessed for eligibility, a considerable portion was not included due to obvious reasons such as age below 18 years or insufficient knowledge of German language. Only a minor portion (3%) was not able or willing to use a computer, and less than 25% refused participation. One might speculate whether these patients had more or less symptoms of depression than the included patients. Patients who feel less depressed might, for example, be less interested in participating in a self-assessment of lifestyle factors leading to a higher rate of depression in the included patients. However, the computerised questionnaire was not introduced as a psychiatric depression screening, but as a lifestyle assessment to give feedback on general factors of health behaviour. One should also keep in mind that it is known from clinical practice that patients with depression show difficulties in motivation, interest and activity and might, therefore, rather decline than agree to participate in filling out questionnaires of lifestyle assessment. Finally, as shown for a subsample of the present study, there were other major reasons to refuse participation, most of all lack of interest, complaints and time constraints.28 Having these limitations in mind, it can be concluded that the 5429 patients undergoing computerised lifestyle screening in this study constitute a large and clinically relevant sample.
Clinical implications
There are three major clinical implications of this study. First, clinically significant depressive states are common in surgical patients of preoperative anaesthesiological assessment; depression is associated with worse physical and mental health factors and has an impact on hospital LOS. Therefore, patients should routinely undergo brief depression screening during preoperative anaesthesiological assessment in order to implement depression treatment if wished by the patient and required by evaluation by a psychiatric specialist. Second, by gaining more knowledge about preoperative depression and its associated factors, clinicians may be more successful in detecting depression in surgical patients and addressing the most important current problems of these patients such as sleeping disturbance, lack of physical exercise, low subjective health and low sense of coherence. Third, during hospital stay, patients with depressive states require a different pathway (Fig. 4 ). Preoperative information tailored to these patient needs should be considered including the subjective health status and the sense of coherence. Also, all relevant steps to decrease the perioperative risk should be named in this information and multimodal strategies given, for example, early mobilisation and maintaining sleep by avoiding additional noise. Risk reduction should be one of the goals to decrease LOS. According to a given patient's needs, depression therapy may be started during or after the hospital stay. The results of this study suggest both pharmacological and psychotherapeutic1,3 treatment options for the different factors associated with depression. Contemporary depression therapy offers a wealth of treatment possibilities including specialised programmes for depression in people with medical conditions addressing sleeping disturbances, physical exercise, as well as subjective health and SOC.1,3,4,19
Fig. 4: no caption available.
Conclusion
Clinically significant depressive states are frequent and serious conditions in surgical patients of preoperative anaesthesiological assessment. The problems of depressed patients include a lack of physical exercise, sleeping disturbances, decreased subjective health and low sense of coherence. In order to detect and treat depression and these associated impairments in surgical patients, therapy programmes are needed that call for a close collaboration of anaesthesiologists, surgeons and clinical psychologists.
Acknowledgements
The authors wish to thank the team of the preoperative anaesthesiological assessment clinic, Department of Anaesthesiology and Intensive Care Medicine, Campus Virchow Klinikum and Campus Charité Mitte, Charité – Universitätsmedizin Berlin, for their excellent help with patient recruitment. They also would like to thank Saskia Otto, MA, and Dr Bartosz Adamcio for their assistance with preparing figures.
The present work was supported by Deutsche Krebshilfe, Bonn, Germany, and by inner university grants, Charité – Universitätsmedizin Berlin, Germany.
The authors have no conflicts of interest to declare.
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