- Question: Since frailty is pertinent to the clinical outcomes of older patients with hip fracture, is a 5-item chart-derived frailty index, including anemia and malnutrition, associated with mortality and quality of life 12 months after surgery?
- Findings: Frailty identified through chart-derived frailty index is associated with the occurrence of major perioperative complications, including delirium and pulmonary infection, and long-term low quality of life in older patients undergoing hip fracture surgery.
- Meaning: Targeting frailty improvement might help accelerate the recovery of older patients undergoing hip fracture repair.
Hip fracture is a serious event in the older population associated with morbidity and mortality, and it remains an important health problem with increasing longevity globally.1 Meanwhile, hip fracture has a major impact on patients’ quality of life,2 which is affected by an individual’s loss of ability to pursue different activities with regard to attachment, role, enjoyment, security, and control.3
Advanced age is a well-established risk factor for adverse postoperative outcomes.4 The American Society of Anesthesiologists (ASA) score is used to evaluate patients’ physical fitness and likelihood of survival.5 However, among the older surgical population, outcomes and quality of life vary substantially and are not consistent with age or ASA score.6 Recently, clinicians have found that frailty could predict clinical outcomes in older patients undergoing surgery. Makary et al pointed out that morbidity and mortality among older patients undergoing surgery could be partly attributed to frailty status.7 Frailty is a state of decreased physiological reserve and increased vulnerability to stressors due to age- and disease-related deficits that accumulate across multiple domains. More than half of patients with hip fracture could be considered frail according to the literature, and frail patients had worse quality of life 1 year after hip fracture than nonfrail patients.8
Identifying frail patients on admission helps tailor medical care plans and keeps patients and their families informed. However, frailty assessment tools require extra work and are not integrated into routine clinical management. According to Amrock et al,9 a validated chart-derived frailty index (CFI) is a 5-term addition (including advanced age, low body mass index [BMI], anemia, malnutrition, and impaired renal dysfunction) using routine laboratory values to evaluate a patient’s frailty status, which has a comparable power to predict geriatric-specific surgical risk. It also identifies some adjustable factors, such as anemia and malnutrition, which might help patients’ functional recovery after surgery.
Evidence from Western patients on the association between frailty and clinical outcomes after surgery has been widely reported in the recent decade. However, this topic has not been extensively explored in the Asian population. We conducted this retrospective study to investigate the association between frailty status and perioperative complications and long-term quality of life in older Chinese patients who underwent hip fracture surgeries.
This retrospective cohort study was conducted on older patients (aged ≥65 years) with low-energy hip fractures who underwent surgical repair under spinal or general anesthesia. This study was approved by the Institutional Review Board of Peking University People’s Hospital, and the requirement for informed consent was waived due to the retrospective nature of this study. This study complied with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for a cohort study. Patients were divided into 2 groups according to their CFI: high CFI group (CFI, 3–5) and low CFI group (CFI, 0–2). The occurrence of complications, length of stay, and long-term quality of life were compared between the 2 groups.
Patients aged ≥65 years who underwent hip fracture repair surgery between June 1, 2019 and May 31, 2020 at Peking University People’s Hospital, Beijing, were included. Patients were identified by searching through the Anesthesia Information Management System (AIMS). Hip fractures comprised femoral neck fracture and intertrochanteric and subtrochanteric fractures. Patients who underwent multiple surgical repairs in addition to hip fracture repair were excluded.
We calculated the CFI according to Amrock et al’s9 method. Specifically, patients were given 1 point for the following conditions: age >70 years, preoperative BMI <18.5 kg/m2, hematocrit <35%, albumin <34 g/L, or serum creatinine >176.8 μmol/L (2.0 mg/dL), and 0 point was given if otherwise. The CFI was represented by the sum of the 5 parameters.9 A higher score indicates a higher level of frailty. To obtain a clear understanding of the association between frailty and clinical prognosis, patients were divided into the high CFI (CFI, 3–5) and low CFI groups (CFI, 0–2). Perioperative management, complications, and length of hospital stay were recorded. The EuroQol 5-dimensional questionnaire (EQ-5D) was obtained through telephone interviews 12 months after surgery to assess mortality and long-term quality of life.
Patients were admitted to the orthopedic ward from the emergency department. Tylox (oral oxycodone 5 mg and acetaminophen 325 mg) was administered preoperatively to alleviate pain. Before surgery, a single-shot fascia iliaca compartment block (0.3% ropivacaine 30 mL) was administered in the operating room, and patient-controlled analgesia using sufentanil (3 μg/bolus; lockout time of 10 minutes) was started after surgery.
Patients received standardized monitors, including electrocardiography (ECG), pulse oximetry, and an arterial line during surgery. The anesthesia method was left to the discretion of the attending anesthesiologist. Spinal anesthesia was performed through the L3 to L4 intervertebral space with 0.5% ropivacaine 2.2 to 3 mL. General anesthesia was induced with etomidate, cisatracurium, and sufentanil, and the airway was secured with a tracheal tube. The patients were extubated in the operating room. Hypotension (<90/60 mm Hg) was treated with epinephrine or phenylephrine. Threshold of red blood cell transfusion was set as a hemoglobin concentration <9 g·dL−1. Patients with unstable blood pressure or oxygen dependency were admitted to the intensive care unit (ICU) after surgery for intense monitoring.
Since the history of stroke and dementia are known risk factors for delirium10 and these 2 conditions were rare in our study, these 2 variables were combined to represent baseline-compromised brain function.
The preparation time was defined as the number of calendar days between the diagnosis of hip fracture and surgery.
Definition of Outcomes
The primary outcome was mortality within 12 months after surgery. The incidences of postoperative complications, including delirium, pneumonia, deep venous thrombosis, stroke, and acute myocardial infarction, were also recorded. Patients’ quality of life was assessed through telephone interviews 12 months after surgery using the EQ-5D.
Delirium was defined as acute, transient, fluctuating, and usually reversible disturbances in attention, cognition, or attention level. It was assessed every 12 hours by trained nurses using the confusion assessment method (CAM).11
The incidences of pneumonia, deep venous thrombosis, stroke, and ICU admission were identified by checking medical records and discharge diagnoses.
EQ-5D is a measure of health status, assessing daily activities, including mobility, self-care, usual activities, pain/discomfort, and anxiety/depression.8 Each dimension consists of a 3-level response: no problems, moderate problems, or severe problems. A scoring algorithm is available by which each health status description can be expressed as an overall score using the published Chinese tariffs for the Chinese population,12 ranging from 0 (death) to 1 (full health). EQ-5D questionnaires were acquired according to the script for telephone administration of the EQ-5D-3L simplified Chinese version for China through telephone interviews 12 months after surgery. The EQ-5D has good measurement properties and is used to measure outcomes in patients recovering from a hip fracture.
The normality distribution of different variables was tested using the Kolmogorov-Smirnov test. Continuous variables are expressed as mean ± standard deviation or median with interquartile range (Q1–Q3). Categorical variables are expressed as percentages. Between-group differences were evaluated using the independent t test or Mann-Whitney U test for continuous variables and the χ2 test or Fisher exact test for categorical variables, as appropriate. The prediction of different risk indices, including frailty status (CFI), ASA classification, and chronological age, on postoperative complications was presented as an area under the receiver operating characteristic (ROC) curve. All P values were 2-tailed, and P < .05 was considered statistically significant. Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) version 22.0 statistical software package (SPSS Inc).
Sample Size Calculation
The study was initially designed as a retrospective cohort study. Given the existing evidence that the 1-year mortality rates are 23% and 5% for frail and nonfrail patients after hip fracture, respectively,8 when the α value is 0.05, a sample size of 73 patients in each group has a power of 90% to detect the difference between the 2 groups. The following formula was used to calculate the sample size:
A total of 381 patients were included in this retrospective study, with 102 and 279 in the high and low CFI groups, respectively (Figure 1).
Patients in the high CFI group were significantly older than those in the low CFI group (83 ± 5 vs 73 ± 7; P < .001). Disease burden was not different between groups, with a comparable percentage of patients experiencing hypertension, diabetes, coronary artery disease, and stroke/Alzheimer’s disease (Table 1). More patients in the high CFI group had anemia (94 [92.1%] vs 71 [25.4%]; P < .001) and malnutrition (85 [83.3%] vs 35 [0.7%]; P < .001) (Table 2).
Anesthetic and Surgical Profiles
Surgical procedures did not differ between the 2 groups, including hemiarthroplasty or total hip arthroplasty for femoral neck fracture and proximal femoral nail antirotation for intertrochanteric and subtrochanteric fractures. The anesthesia approach (spinal or general), surgical duration, and anesthesia duration were similar between the 2 groups (Table 1).
Table 1. -
Demographic, Surgical, and Anesthetic Data
||High CFI group (n = 102)
||Low CFI group (n = 279)
|Male gender, n (%)
||83 ± 5
||78 ± 7
||20.8 ± 4.4
||23.5 ± 3.8
|Hypertension, n (%)
|Diabetes, n (%)
|Coronary artery disease, n (%)
| General anesthesia
| Spinal anesthesia
|Duration of anesthesia (min)
|Duration of surgery (min)
|Diagnosis, n (%)
Fracture of femoral neck
|Surgical procedure, n (%)
Proximal femoral nail antirotation
Values are mean ± SD or number (proportion) or median (Q1–Q3). Statistics are t-value for t test of normalized continuous variables, M-W for nonparametric variables, or χ2 for test of categorical variables.
Abbreviations: ASA, American Society of Anesthesiologists; BMI, body mass index; CFI, chart-derived index; SD, standard deviation.
aP < .05.
Table 2. -
Frailty Status and Clinical Outcomes
||High CFI group (n = 102)
||Low CFI group (n = 279)
||Mean difference (95% CI)
|Chart-derived frailty index
||3.3 ± 0.5
||1.4 ± 0.6
||37.8 ± 3.2
||30.7 ± 6.2
||0.29 ± 0.04
||0.37 ± 0.05
|Anemia (hematocrit <35%), n (%)
|Malnutrition (albumin <34 g/L), n (%)
|Blood loss (mL)
|Patients who required intraoperative blood products, n (%)
|Patients who required postoperative blood products, n (%)
|Pneumonia, n (%)
|Delirium, n (%)
|ICU admittance, n (%)
|Postoperative length of stay (d)
|Loss to follow-up 12 mo after surgery
|12-mo mortality, n (%)
||n = 64
||n = 209
|EQ-5D utility score
||0.63 ± 0.22
||0.72 ± 0.22
||–0.09 (−0.16 to −0.03)
|Patients with severe problems in domains of EQ-5D-3L, n (%)
||2.33 (−6.22 to 10.87)
||7.36 (−1.80 to 16.53)
| Usual activities
||4.11 (−3.64 to 11.87)
||–0.32 (−7.87 to 7.23)
||1.47 (−5.13 to 8.06)
Values are mean ± SD or number (proportion) or median (Q1–Q3). Statistics are t-value for t test of normalized continuous variables, M-W for nonparametric variables, or χ2 for test of categorical variables. Chart-derived frailty index was calculated as addition of the patient’s conditions, including age >70 y, preoperative BMI <18.5, hematocrit <35%, albumin <34 g/L, and serum creatinine >176.8 μmol/L (2.0 mg/dL).
Abbreviations: BMI, body mass index; CFI, chart-derived frailty index; CI, confidence interval; EQ-5D, EuroQol 5-dimensional questionnaire; EQ-5D-3L, 3-level version of EQ-5D ICU, intensive care unit; SD, standard deviation.
aP < .05.
Blood loss during surgery was comparable between the 2 groups. However, more patients in the high CFI group consumed blood products intraoperatively (34 [33.3%] vs 32 [11.5%]; P < .001) and after surgery (81 [79.4%] vs 130 [46.5%]; P < .001) than patients in the low CFI group.
No Patient Died During Hospitalization
Patients in the high CFI group had an increased incidence of delirium by 13.80% (95% confidence interval [CI], 6.31–21.29) (17 [16.6%] vs 8 [2.8%]; P < .001) compared to patients in the low CFI group. Patients in the high CFI group had an increased incidence of pneumonia by 17.71% (95% CI, 7.08–23.34) (40 [39.2%] vs 60 [21.5%]; P < .001) compared to patients in the low CFI group. Patients in the high CFI group had an increased incidence of ICU admittance by 25.02% (95% CI, 15.71–34.33) (31 [30.3%] vs 15 [5.3%], P < .001) than patients in the low CFI group (Table 2).
There were 69 patients who lost to follow-up, with 15 and 54 patients in the high and low CFI groups, respectively. More patients died in the high CFI group 1 year after surgery with an increased mortality of 19.33% (95% CI, 9.47–29.18) (26.4% [23/87] vs 7.1% [16/225]; P < .001).
Sixty-four patients in the high CFI group and 209 patients in the low CFI group completed the EQ-5D survey 1 year after surgery. The EQ-5D utility score in the high CFI group was significantly lower than that in the low CFI group (0.63 ± 0.22 vs 0.72 ± 0.22; P = .002). More patients in the high CFI group had severe problems in mobility, self-care, and daily activity (Table 2).
To evaluate the predictive accuracy of frailty status (CFI), ASA classification, and chronological age on postoperative complications, we described the ROC curve and computed the area under the curve (AUC). Although the AUCs of ASA + age + frailty were the largest, there was no statistical significance between the AUCs of ASA + frailty and ASA + age + frailty prediction as CIs of the AUCs overlapped. Thus, including frailty in the model to predict complications and mortality increased the predictive abilities of the models, with AUCs ranging from 0.609 to 0.823 (Figure 2).
In this retrospective study, we utilized a previously validated chart-derived frailty score to understand the association between frailty and postoperative complications, mortality, and long-term quality of life in older patients with hip fracture in China. Our study demonstrated that a high frailty score was associated with adverse clinical outcomes, mortality, and low quality of life in older patients undergoing hip fracture repair.
According to the literature from the West, frailty is recognized as an important risk factor for adverse clinical outcomes and increased mortality after surgery. However, the association between frailty and surgical outcomes in older Asian patients has not been fully understood. Our study revealed that the frailty status was associated with adverse long-term prognosis in Chinese patients. The 1-year mortality rates were 26.4% (23 of 87) and 7.1% (16 of 225) in the high CFI and low CFI groups, respectively, which are consistent with the result of van de Ree et al’s8 study showing mortality rates of 23.2% (86 of 371) and 4.3% (14 of 325), respectively, in frail and nonfrail patients after hip fracture surgery. The anesthesia approach did not play a role with regard to mortality, as the 2 groups had comparable choice of spinal or general anesthesia, but the mortality was different, which is consistent with White et al’s13 large-scale analysis of 11,805 patients undergoing hip fracture operations.
A high frailty index was associated with an increased incidence of delirium in our study, similar to a recent meta-analysis involving 1008 older patients undergoing elective surgeries.14 In the high CFI group in our study, 92.1% of patients were anemic, and anemia is associated with cerebral hypoperfusion. A previous study suggested that homologous blood transfusion is a protective factor for patients with delirium with the lowest measured hemoglobin level <9.7 mg/dL.15 Therefore, avoiding anemia in older patients might be helpful in preventing delirium. No association between the anesthesia method and postoperative delirium was established in our study, which was in accordance with the Prevention of Delirium and Complications Associated With Surgical Treatments Trial.16
Several delirium prediction tools exist, among which the Vochteloo model is a reliable, feasible, and valid instrument for predicting delirium in patients with hip fracture.17 The Vochteloo model has 9 items, 3 of which, namely, hearing problem, vision problem, and advanced age, are deficits in frailty status. The age >79 years, failure to spell word backward, disorientation to place, and higher nurse-rated illness severity (AWOL) model is based on general patients to predict delirium.18 One of its 4 conditions is advanced age (>79 years), showing its association with frailty. Therefore, our exploration of the association between frailty status and delirium is not independent of or contrary to other existing assessment tools but could enrich our knowledge about older surgical candidates.
As expected, frailty further increased the power of the ASA classification in predicting delirium, pneumonia, ICU admission, and 1-year mortality in the current study. Including frailty in our model to predict complications and mortality increased its predictive ability. The ASA classification describes patients’ well-being.5 Frailty captures a holistic sense of how a set of conditions affects an individual’s function and identifies those with decreased physiologic reserves in multiple organ systems. The contribution of frailty to adverse outcomes after surgery could be explained by vulnerability to intrinsic and extrinsic stressors, decreased cognitive reserve, and dysregulation of immune and inflammatory responses.19,20
Frailty was also associated with a low quality of life 1 year after hip fracture surgery, which might be explained by the higher incidence of postoperative complications and poor recovery from the surgery. The association between frailty and low quality of life was consistent with the findings of previous studies. Inoue et al21 found that the frailty status was associated with poor functional recovery after hip fracture repair. Quality of life is among the key outcomes defined by the Institute for Healthcare Improvement (IHI) Triple Aim and Core Outcome Measures in Effectiveness Trials initiative in addition to traditional outcomes, such as morbidity, mortality, and length of stay. In the current study, all patients had a low quality of life, with the average EQ-5D utility score being 0.62 and 0.73 in the high and low CFI groups, respectively. A higher percentage of individuals in the high CFI group had severe problems in mobility, self-care, and usual activity 12 months after surgery, and attention should be drawn to improve these basic impaired functions.
The CFI scoring system can easily identify the frail cohort at admission with routine laboratory results, which is objective and convenient and requires no extra cost or effort. Among various frailty instruments, some require prospective obtaining of frail phenotype (such as the Fried phenotype, including weight loss, decreased grid strength, exhaustion, low activity, and slowed walking speed),7 collection of functional capacity (such as the Edmonton Frail Scale, which assesses cognition, social support, and mood continence),22 or at least observing the patient (Clinical Frailty Scale).23 Some assessment tools could be applied in retrospective studies, such as the 5-factor modified frailty index (comorbid diabetes, hypertension, congestive heart failure, chronic obstructive pulmonary disease, and functional status), which require careful medical history recordings.24 The CFI provides objective measurements with comparable predictive performance with the Robinson score and 11-factor modified frailty index according to Amrock et al.9 Once a patient has been identified as frail, physicians can integrate frailty into their evaluation of the risks, benefits, and prognosis of surgery.25 In addition, there is an opportunity to improve outcomes in frail patients with hip fracture because both anemia and malnutrition represent modifiable risk factors. For example, consider intravenous ferroin infusion to treat anemia or protein supplementation to address malnutrition. Targeting frailty improvement could have an implication in helping patients’ functional recovery after surgery.22
Our study has some limitations. First, perioperative data were retrospectively collected, which could have missed some clinical outcomes. The low incidence rate of delirium (6.5%) revealed in our study compared with significantly higher levels in other studies might be attributed to the retrospective design. Second, Bonferroni correction (adjusting type I error rate) was not conducted when implementing multiple comparisons of incidences of different complications, which might render a stronger association between frailty and adverse outcomes. Potential false-positive factors encourage the investigation of potential measures to accelerate the recovery of older patients and improve outcomes in future prospective studies.
In conclusion, frailty evaluation among Chinese patients through CFI is associated with the occurrence of major perioperative complications, mortality, and long-term low quality of life in older patients undergoing hip fracture surgery. Targeting frailty improvement may help accelerate the recovery of these older patients.
The authors thank Ms Jian Zhang from the Department of Applied Linguistics in Peking University Health Science Center, Beijing, China, who provided medical writing editing. They also thank Dr Sainan Zhu, PhD, from the Department of Biostatistics, Peking University First Hospital, Beijing, China, for her help with statistical analysis.
Name: Hong Zhao, MD.
Contribution: This author helped with study design, data analysis, and manuscript preparation.
Name: Peiyao Wei, MD.
Contribution: This author helped with data collection.
Name: Yi Feng, MD.
Contribution: This author helped with study design.
This manuscript was handled by: Robert Whittington, MD.
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