Clinical Frailty Scale as a predictor of short-term mortality: A systematic review and meta-analysis of studies on diagnostic test accuracy

The hazard of mortality across different levels of frailty are increased among patients with high Braden scores

PURPOSE

To examine the prognostic accuracy of the Clinical Frailty Scale (CFS) and Braden Scale (BS) separately and combined for 90-day mortality. Furthermore, to examine the effect of frailty on mortality depending on different levels of the Braden score.

METHODS

The study included acutely admitted medical patients ≥ 65 years. We used an optimum cutoff for CSF and BS at ≥ 4 and ≤ 19, respectively. CFS categorized frailty as Non-frail (< 4), Frail (4-5), and Severely frail (> 5). Prognostic accuracy was estimated by the area under the receiver operating characteristic curves (AUROC) with 95% confidence intervals (CI). Cox regression analysis was used to compute the adjusted hazard ratio (aHR) for mortality.

RESULTS

The mean age among 901 patients (54% female) was 79 years. The AUROC for CFS and BS was 0.65 (CI95% 0.60-0.71) and 0.71 (CI95% 0.66-0.76), respectively. aHR for mortality of CFS ≥ 4, BS ≤ 19, and combined were 2.3 (CI95% 1.2-4.2), 1.9 (CI95% 1.3-2.9), and 1.9 (CI95% 1.3-2.8), respectively. For BS > 19, the aHR for mortality was 2.2 (CI95% 1.0-4.8) and 3.5 (CI95% 1.4-8.6) for 'frail' and 'severely frail', respectively. aHR for BS ≤ 19 was 1.1 (CI95% 0.4-3.2) and 1.3 (CI95% 0.5-3.7) for 'frail' and 'severely frail', respectively.

CONCLUSION

Although CFS and BS were associated with 90-day mortality among older acutely admitted medical patients, the prognostic accuracy was poor-to-moderate, and the combination of CFS and BS did not improve the prognostic accuracy. However, the hazard of mortality across different levels of frailty groups were particularly increased among patients with high BS scores.

The effect of frailty on mortality and functional outcomes in spontaneous intracerebral haemorrhage

INTRODUCTION

Limited data in patients with spontaneous intracerebral haemorrhage (SICH) showed that frailty was associated with mortality; however, there was insufficient data on functional outcomes. This study aimed to investigate the effect of frailty on overall mortality and 90-day functional outcomes in SICH.

MATERIALS AND METHODS

We conducted a retrospective study of 1223 patients diagnosed with SICH from January 2014 to December 2020. Frailty was defined as a clinical frailty scale (CFS) score of 4-9. Binary cut-offs were defined using receiver operating curve analysis. 90-day poor functional outcomes (PFO) were defined as modified Rankin Scale (mRS) ≥3, and utility-weighted mRS (UW-mRS) were based on previous validated studies respectively. Regression analyses were conducted to investigate the association between frailty and outcomes. Confounders adjusted for included demographics, cardiovascular risk factors and haematoma characteristics.

RESULTS

1091 patients met the inclusion criterion. 167 (15.3 %) had 30-day mortality and 730 (66.9 %) had 90-day PFO. Frailty was significantly associated with lower overall survival (HR: 1.54; 95 % CI: 1.11-2.14, p=0.010), 90-day PFO (OR: 1.90; 95 % CI: 1.32-2.74; p<0.001) and poorer UW-mRS (β: -0.06; 95 % CI: (-0.08 to -0.04); p<0.001) even after adjusting for confounders.

CONCLUSIONS

Frailty was significantly associated with greater mortality and PFO after incident SICH, even after adjusting for a priori confounders. Frail male individuals may be predisposed to poorer outcomes from higher prevalence of cortical atrophy. The use of CFS in younger individuals may aid management by predicting outcomes after incident SICH. Identifying frail individuals with incident SICH could aid in decision-making and the surgical management of SICH.

Development and validation of a diagnostic nomogram for frailty in cancer patients

BACKGROUND

The presence of frailty decreases the overall survival of cancer patients. An accurate and operational diagnostic method is needed to help clinicians choose the most appropriate treatment to improve patient outcomes.

METHODS

Data were collected from 10 649 cancer patients who were prospectively enrolled in the Investigation on Nutritional Status and its Clinical Outcomes of Common Cancers (INSCOC) project in China from July 2013 to August 2022. The training cohort and validation cohort were randomly divided at a ratio of 7:3. The multivariable logistic regression analysis, multivariate Cox regression analyses, and the least absolute shrinkage and selection operator (LASSO) method were used to develop the nomogram. The concordance index and calibration curve were used to assess the diagnostic utility of the nomogram model.

RESULTS

The 10 risk factors associated with frailty in cancer patients were age, AJCC stage, liver cancer, hemoglobin, radiotherapy, surgery, hand grip strength (HGS), calf circumference (CC), PG-SGA score and QOL from the QLQ-C30. The diagnostic nomogram model achieved a good C index of 0.847 (95% CI, 0.832-0.862, P < 0.001) in the training cohort and 0.853 (95% CI, 0.83-0.876, P < 0.001) in the validation cohort. The prediction nomogram showed 1-, 3-, and 5-year mortality C indices in the training cohort of 0.708 (95% CI, 0.686-0.731), 0.655 (95% CI, 0.627-0.683), and 0.623 (95% CI, 0.568-0.678). The 1-, 3-, and 5-year C indices in the validation cohort were similarly 0.743 (95% CI, 0.711-0.777), 0.680 (95% CI, 0.639-0.722), and 0.629 (95% CI, 0.558-0.700). In addition, the calibration curves and decision curve analysis (DCA) were well-fitted for both the diagnostic model and prediction model.

CONCLUSIONS

The nomogram model provides an accurate method to diagnose frailty in cancer patients. Using this model could lead to the selection of more appropriate therapy and a better prognosis for cancer patients.

Prediction of postoperative mortality in older surgical patients by clinical frailty scale: A systematic review and meta-analysis

AIMS

To systematically evaluate the predictive efficacy of clinical frailty scale (CFS) for postoperative mortality older surgical patients, and to evaluate the prevalence of frailty in the included studies.

DESIGN

A systematic review and meta-analysis of observational studies was conducted, utilizing the MOOSE guidelines for the evaluation of both. Quality assessment of the articles was also performed.

DATA SOURCES

The protocol was registered (CRD42023423552). Relevant English and Chinese language studies published until October 20th, 2023 were retrieved from PubMed, Web of Science, Embase, Medline, CINAHL,Cochrane, WAN FANG DATA, VIP Information, CNKI, and SinoMed databases.

REVIEW METHODS

Study were included in which frailty was measured by the CFS and postoperative mortality was reported for older surgery patients. A meta-analysis to predict postoperative mortality and frailty prevalence was performed using STATA 17.0 software.

RESULTS

Sixteen cohort studies were included (5,864 participants) from 1,513 records. All studies' Newcastle-Ottawa Scale (NOS) scores were above 6 points. It was found that the prevalence of surgical frailty in the older was 0.36(CI 0.20-0.52). Patients assessed as frail by the CFS were associated with higher all-cause mortality (OR:4.01; CI 2.59-6.23). Subgroup analysis shows that frailty was associated with1-month mortality (OR:3.85; CI 1.11-13.45) and 1-year mortality (OR:4.43; CI 2.18-8.99).

CONCLUSIONS

The prevalence of frailty is high in older surgical patients, and CFS can effectively predict the mortality of older surgical patients with frailty.

The Association Between Frailty Evaluated by Clinical Frailty Scale and Mortality of Older Patients in the Emergency Department: A Prospective Cohort Study

Background

Frailty epitomizes the most complex consequence of an aging population. This study aimed to evaluate the impact of frailty, measured using the Clinical Frailty Scale (CFS), on outcomes of older people in an emergency department (ED).

Methods

We conducted a prospective observational study enrolling patients aged 65 years and older in a medical center of Taiwan between March 8, 2021, and November 30, 2021. The primary outcome was 90-day mortality rate. Individuals were categorized into three groups based on the CFS scores. Logistic regression was employed to examine the influence of frailty on clinical outcomes following covariate adjustment. Survival analysis was conducted using Kaplan-Meier curves and Log rank tests.

Results

A total of 473 individuals were included in the study, with a mean age of 82.1 years, and 60.5% of them were males. The 90-day mortality rate was 10.6%. Among these groups, the CFS score 7-9 group had the highest 90-day mortality rate (15.9%), followed by the CFS score 4-6 group (8.0%) and the CFS score 1-3 group (7.1%). The multiple logistic regression analyses demonstrated a significant impact of CFS score on prognosis, with adjusted odd ratios of 1.24 (95% CI 1.06-1.47) for 90-day mortality, 1.18 (95% CI 1.06-1.31) for hospitalization, and 1.30 (95% CI 1.12-1.52) for 180-day mortality. The Kaplan-Meier curves revealed a significantly higher 90-day mortality rate for patients with high CFS scores (Log rank tests, p = 0.019).

Conclusion

In the older ED population, the severity of frailty assessed by the CFS emerged as a significant and important prognostic factor for hospitalization, 90-day mortality, and 180-day mortality.

Association of frailty with adverse outcomes in surgically treated geriatric patients with hip fracture: A meta-analysis and trial sequential analysis

OBJECTIVE

Some studies have associated frailty and prognostic outcomes in geriatric hip fracture patients, but whether frailty can predict postoperative outcomes remains controversial. This review aims to assess the relationship between frailty and adverse postoperative outcomes in geriatric patients with hip fracture.

METHODS

Based on electronic databases, including PubMed, Embase, Web of Science, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library, Chinese National Knowledge Infrastructure, and WanFang Data, we systematically searched for studies that investigated the association between frailty and adverse outcomes among patients aged 60 or over after hip fracture surgery. Stata 17.0 and Trial Sequential Analysis viewer software were used to obtain pooled estimates and verify whether the sample size was sufficient and the evidence robust.

RESULTS

Twenty-one studies involving 49,196 patients were included for quantitative analysis. Compared with nonfrail patients, frail patients had a higher risk of inpatient mortality (risk ratio [RR] = 1.93, 95% confidence interval [CI]: 1.66-2.23), 30-day mortality (RR = 2.13, 95% CI: 1.23-3.70), and 1-year mortality (RR = 2.44, 95% CI: 1.47-4.04). Frailty can significantly predict postoperative complications (RR = 1.76, 95% CI: 1.38-2.23), including delirium, pneumonia, cardiac complications, urinary tract infection, and surgical site infection; the association between frailty and deep venous thrombosis/pulmonary embolism and acute kidney injury needs further analysis. Trial sequential analysis showed that the findings regarding mortality were reliable and robust.

CONCLUSION

This meta-analysis provides detailed information indicating that frailty is a substantial predictor of mortality and selected postoperative complications.

Predictive performance of different measures of frailty (CFS, mFI-11, mFI-5) on postoperative adverse outcomes among colorectal cancer patients: a diagnostic meta-analysis

PURPOSE

To clarify the predictive performance of different measures of frailty, including Clinical Frailty Scale (CFS), 11-factor modified Frailty Index (mFI-11), and 5-factor modified Frailty Index (mFI-5), on adverse outcomes.

METHODS

PubMed, Embase, Web of Science, and other databases were retrieved from the inception of each database to June 2023. The pooled sensitivity, specificity, and the area under the summary receiver operating curve (SROC) values were analyzed to determine the predictive power of CFS, mFI-11, and mFI-5 for adverse outcomes.

RESULTS

A total of 25 studies were included in quantitative synthesis. The pooled sensitivity values of CFS for predicting anastomotic leakage, total complications, and major complications were 0.39, 0.57, 0.45; pooled specificity values were 0.70, 0.58, 0.73; the area under SROC values were 0.58, 0.6, 0.66. The pooled sensitivity values of mFI-11 for predicting total complications and delirium were 0.38 and 0.64; pooled specificity values were 0.83 and 0.72; the area under SROC values were 0.64 and 0.74. The pooled sensitivity values of mFI-5 for predicting total complications, 30-day mortality, and major complications were 0.27, 0.54, 0.25; pooled specificity values were 0.82, 0.84, 0.81; the area under SROC values were 0.63, 0.82, 0.5.

CONCLUSION

The results showed that CFS could predict anastomotic leakage, total complications, and major complications; mFI-11 could predict total complications and delirium; mFI-5 could predict total complications and 30-day mortality. More high-quality research is needed to support the conclusions of this study further.

Do-Not-ResuscitateDecision-Making during the COVID-19 Pandemic in a Teaching Hospital: Lessons Learned for the Future

Method

A cross-sectional survey study was conducted between February 2021 and April 2021 for all doctors and doctors in training, working in the Antwerp University Hospital during the COVID-19 pandemic.

Results

127 doctors participated in this study. The familiarity with the different scores used in the triage during the COVID-10 pandemic was 51% for the Clinical Frailty Scale (CFS) and 20% for the Charlson Comorbidity Index (CCI). Participants indicated that their DNR decision is based on various aspects such as clinical assessment, comorbidities, patient's wishes, age, prognosis, and functional state.

Conclusion

The familiarity with the different scores used during triage assessments is low. The total clinical picture of the patient is needed to make a considered decision, and this total picture of the patient seems to be well encompassed by frailty measurement (CFS). Although many participants indicated that the different scores do not offer much added value compared to their clinical assessment, it can help guide DNR decisions, especially for doctors in training.

Assessment of frailty by paramedics using the clinical frailty scale - an inter-rater reliability and accuracy study

BACKGROUND

Frailty assessment by paramedics in the prehospital setting is understudied. The goals of this study were to assess the inter-rater reliability and accuracy of frailty assessment by paramedics using the Clinical Frailty Scale (CFS).

METHODS

This was a cross-sectional study with paramedics exposed to 30 clinical vignettes created from real-life situations. There was no teaching intervention prior to the study and paramedics were only provided with the French version of the CFS (definitions and pictograms). The primary outcome was the inter-rater reliability of the assessment. The secondary outcome was the accuracy, compared with the expert-based assessment. Reliability was determined by calculating an intraclass correlation coefficient (ICC). Accuracy was assessed through a mixed effects logistic regression model. A sensitivity analysis was carried out by considering that an assessment was still accurate if the score differed from no more than 1 level.

RESULTS

A total of 56 paramedics completed the assessment. The overall assessment was found to have good inter-rater reliability (ICC = 0.87 [95%CI 0.81-0.93]). The overall accuracy was moderate at 60.6% (95%CI 54.9-66.1) when considering the full scale. It was however much higher (94.8% [95%CI 92.0-96.7] when close assessments were considered as accurate. The only factor associated with accurate assessment was field experience.

CONCLUSION

The assessment of frailty by paramedics was reliable in this vignette-based study. However, the accuracy deserved to be improved. Future research should focus on the clinical impact of these results and on the association of prehospital frailty assessment with patient outcomes.

REGISTRATION

This study was registered on the Open Science Framework registries ( https://doi.org/10.17605/OSF.IO/VDUZY ).

Red cell distribution width and mortality in older patients with frailty in the emergency department

BACKGROUND

The red cell distribution width (RDW) reflects the degree of heterogeneity of red blood cells. Elevated RDW is associated both with frailty and with increased mortality in hospital-admitted patients. In this study we evaluate whether high RDW values are associated with mortality in older emergency department (ED) patients with frailty, and if the association is independent of the degree of frailty.

METHODS

We included ED patients with the following criteria: ≥ 75 years of age, Clinical Frailty Scale (CFS) score of 4 to 8, and RDW % measured within 48 h of ED admission. Patients were allocated to six classes by their RDW value: ≤ 13%, 14%, 15%, 16%, 17%, and ≥ 18%. The outcome was death within 30 days of ED admission. Crude and adjusted odds ratios (OR) with 95% confidence intervals (CI) for a one-class increase in RDW for 30-day mortality were calculated via binary logistic regression analysis. Age, gender and CFS score were considered as potential confounders.

RESULTS

A total of 1407 patients (61.2% female), were included. The median age was 85 with an inter-quartile range (IQR) of 80-89, median CFS score 6 (IQR: 5-7), and median RDW 14 (IQR: 13-16). Of the included patients, 71.9% were admitted to hospital wards. A total of 85 patients (6.0%) died during the 30-day follow-up. Mortality rate was associated with RDW increase (p for trend < .001). Crude OR for a one-class increase in RDW for 30-day mortality was 1.32 (95% CI: 1.17-1.50, p < .001). When adjusted for age, gender and CFS-score, OR of mortality for one-class RDW increase was still 1.32 (95% CI: 1.16-1.50, p < .001).

CONCLUSION

Higher RDW values had a significant association with increased 30-day mortality risk in frail older adults in the ED, and this risk was independent of degree of frailty. RDW is a readily available biomarker for most ED patients. It might be beneficial to include it in risk stratification of older frail ED patients to identify those who could benefit from further diagnostic assessment, targeted interventions, and care planning.