Multidimensional Frailty Score Research Articles

Multidimensional Frailty Score for the prediction of postoperative outcomes in elderly patients with fragility fractures.

Multidimensional Frailty Score for the prediction of postoperative outcomes in elderly patients with fragility fractures.

Efficacy of geriatric multidisciplinary oncology clinic in the surgical treatment decision-making process for frail elderly patients with colorectal cancer.

PurposeMultidisciplinary care has become a cornerstone of colorectal cancer management. To evaluate the clinical efficacy of a geriatric multidisciplinary oncology clinic (GMOC), we analyzed the surgical treatment decision-making process and outcomes.MethodsThis retrospective single-center study reviewed the data of patients aged ≥65 years who participated in the GMOC at a tertiary referral hospital between 2015 and 2021. The clinical adherence rate, comprehensive geriatric assessment, and a multidimensional frailty score (MFS) were obtained. The groups that were recommended and not recommended for surgery were compared, analyzing the factors impacting the decision and 1-year survival outcomes. Furthermore, the postoperative complications of patients who underwent surgery were evaluated.ResultsA total of 165 patients visited the GMOC, and 74 had colorectal cancer (mean age, 85.5 years [range, 81.2–89.0 years]). Among patients with systemic disease (n = 31), 7 were recommended for surgery, and 5 underwent surgery. Among patients with locoregional disease (n = 43), 18 were recommended for surgery, and 12 underwent surgery. Patients recommended and not recommended for surgery had significantly different activities of daily living (ADL) (P = 0.024), instrumental ADL (P = 0.001), Mini-Mental State Examination (P = 0.014), delirium risk (P = 0.039), and MFS (P = 0.001). There was no difference in the 1-year overall survival between the 2 groups (P = 0.980). Of the 17 patients who underwent surgery, the median (interquartile range) of operation time was 165.0 minutes (120.0–270.0 minutes); hospital stay, 7.0 days (6.0–8.0 days); and 3 patients had wound complications.ConclusionProper counseling of patients through the GMOC could lead to appropriate management and favorable outcomes.

How does the multidimensional frailty score compare with grip strength for predicting outcomes after hip fracture surgery in older patients? A retrospective cohort study

BackgroundFrailty and low handgrip strength (HGS) are associated with adverse outcomes after hip fracture (HF) surgery. We aimed to compare the predictive role of frailty and HGS for adverse outcome in HF patients.MethodsWe included older patients (age ≥ 65 years) who underwent HF surgery to compare the predictive role of HGS and hip-multidimensional frailty score (Hip-MFS) for postoperative complications and mortality. The Hip-MFS was calculated based on comprehensive geriatric assessment (CGA), and HGS was measured with a hand dynamometer. The primary outcome was a composite of postoperative complications (e.g., pneumonia, urinary tract infection, delirium, acute pulmonary thromboembolism, and unplanned intensive care unit admission). The secondary outcomes were 6-month mortality and mortality at the end of follow-up.ResultsThe median observation time was 620.5 days (interquartile range: 367.0–784.8 days). Among the 242 patients (mean age: 81.5 ± 6.7 years, 73.1% women), 106 (43.8%) experienced postoperative complications. The 6-month mortality and mortality at the end of follow-up were 7.4% (n = 18) and 20.7% (n = 50), respectively. The Hip-MFS (odds ratio [OR], 1.250; 95% confidence interval [CI], 1.092–1.432) and HGS (OR, 1.147; 95% CI, 1.082–1.215) could predict postoperative complications. The Hip-MFS could predict both 6-month mortality (hazard ratio [HR], 1.403; 95% CI, 1.027–1.917) and mortality at the end of follow-up (HR, 1.493; 95% CI, 1.249–1.769) after adjustment, while HGS was only associated with mortality at the end of follow-up (HR, 1.080; 95% CI, 1.024–1.139). For mortality at the end of follow-up, predictive models with the Hip-MFS were superior to those with HGS in the time-dependent receiver-operating curve analysis after adjustment (p = 0.017). Furthermore, the addition of Hip-MFS or HGS to the American Society of Anesthesiologists (ASA) classification improved its prognostic ability.ConclusionsBoth the Hip-MFS and HGS could predict postoperative complications and improve prognostic utility when combined with the ASA classification. The Hip-MFS was a stronger predictor of mortality than HGS after HF surgery. HGS could be a useful pre-screening tool to identify patients at a high risk of postoperative complications and those who may benefit from further CGA.

This Month in Anesthesiology

This Month in Anesthesiology

Frailty in Elderly Gastric Cancer Patients Undergoing Gastrectomy

Introduction: There is a dearth of literature on frailty specifically in elderly (aged ≥65 years) gastric cancer patients undergoing gastrectomy. We aim to assess the effects of frailty on postoperative outcomes. Methods: A review of a prospective database was performed from November 2011 to April 2019. Frailty was assessed by multidimensional frailty score (MFS). Outcomes assessed were early postoperative complications and mortality, and length of stay. Results: 289 patients were included. The mean age was 77.3 (range 66–94) years. 183 (63.3%) were males and 172 (59.5%) had early cancer. 275 (95.2%) underwent minimally invasive gastrectomy. 79 (27.3%) patients suffered early postoperative complications, with 47 (16.3%) suffering from Clavien-Dindo grade ≥2 complications. One-year, 90-day, 30-day, and inhospital mortality were 6.6, 1.4, 0.7, and 0%, respectively. 111 (38.4%) of patients were classified as “frail” based on MFS > 5. “Frail” patients were associated with higher 1-year mortality (odds ratio (OR) 4.51, 95% CI 1.57–12.98, p = 0.005) on univariate analysis. On multivariate analysis, “frail” patients did not have significantly increased 1-year mortality. However, when definition of “frail” was changed from MFS > 5 to MFS > 6, frailty was significantly associated with increased 1-year mortality (OR 3.73, 95% CI 1.11–12.53, p = 0.033). Conclusions: Elderly gastric cancer patients undergoing gastrectomy with MFS > 5 do not have increased mortality risk. The influence of frailty on postoperative outcomes may vary based on the risk of the surgical procedure.

Comparison of multidimensional frailty score, grip strength, and gait speed in older surgical patients.

BackgroundFrail older adults are at increased risk of post‐operative morbidity compared with robust counterparts. Simple methods testing frailty such as grip strength or gait speed have shown promising results for predicting post‐operative outcome, but there is a debate regarding the most appropriate and precise frailty assessment method. We compared the predictive value of multidimensional frailty score (MFS) with grip strength, gait speed, or conventional risk stratification tool for predicting post‐operative complications in older surgical patients.MethodsFrom January 2016 to June 2017, 648 older surgical patients (age ≥ 65 years) were included for analysis. MFS was calculated based on the preoperative comprehensive geriatric assessment. Grip strength and gait speed were measured before surgery. The primary outcome was a composite of post‐operative complications (e.g. pneumonia, urinary tract infection, delirium, acute pulmonary thromboembolism, and unplanned intensive care unit admission). The secondary outcome was the 6 month all‐cause mortality.ResultsAmong 648 patients (mean age 76.6 ± 5.4 years, 52.8% female), 66 (10.2%) patients experienced post‐operative complications, and the 6 month mortality was 3.9% (n = 25). Grip strength, gait speed, MFS, and American Society of Anesthesiologists (ASA) classification could predict post‐operative complication but only MFS (hazard ratio = 1.581, 95% confidence interval 1.276–1.959, P < 0.001) could predict 6 month mortality after adjustment. MFS (C‐index = 0.750) had a superior prognostic utility compared with age (0.638, P = 0.008), grip strength (0.566, P < 0.001), and ASA classification (0.649, P = 0.004). MFS improved the predictive value on age [C‐index of 0.638 (age) vs. 0.758 (age + MFS), P < 0.001] and ASA classification [C‐index of 0.649 (ASA) vs. 0.765 (ASA + MFS), P < 0.001] for post‐operative complication; however, gait speed or grip strength did not provide additional prognostic value in both age and ASA.ConclusionsMultidimensional frailty score based on preoperative comprehensive geriatric assessment showed better utility than age, grip strength, gait speed, or ASA classification for predicting post‐operative complication and 6 month mortality. MFS also showed incremental predictive ability for post‐operative complications with the addition of age and ASA classification. Accordingly, MFS is superior to grip strength or gait speed for predicting complications among older surgical patients.

MULTIDIMENSIONAL FRAILTY SCORE IS SUPERIOR TO PREDICT COMPLICATIONS AFTER SURGERY THAN CONVENTIONAL RISK FACTORS

Frail older adults are at increased risk for postoperative morbidity compared with their robust counterparts. We compared predictive utility of multidimensional frailty score (MFS) with physical performance parameters or conventional risk stratification indicators to identify postoperative complication in older surgical patients. From January 2016 to June 2017, 648 older surgical patients (age≥ 65) were included for analysis. The MFS was calculated through comprehensive geriatric assessment (CGA). Grip strength and gait speed were measured preoperatively. The primary outcome was postoperative complication (eg, pneumonia, urinary tract infection, delirium, acute pulmonary thromboembolism, and unplanned ICU admission). Secondary outcome was 6-months all-cause mortality. Sixty-six (10.2%) patients experienced postoperative complications and 6-months mortality was 3.9% (n=25). Grip strength, gait speed, MFS and ASA classification could predict postoperative complication but only MFS (Hazard Ratio = 1.564, 95% CI, 1.283-1.905, p < 0.001) could predict 6-months mortality after full adjustment. MFS (C index = 0.747) had superior prognostic utility than age (0.638, p value = 0.008), grip strength (0.566, p value < 0.001) and ASA classification (0.649, p value = 0.004). MFS only had additive predictive value on both age (C-index of 0.638 (age) vs 0.754 (age +MFS), p = 0.001) and ASA classification (C index of 0.649 (ASA) to 0.762 (ASA + MFS), p < 0.001) for postoperative complication, but gait speed or grip strength had no statistical additive prognostic value on both age and ASA classification.

Simple Method of Screening for Frailty in Older Adults Using a Chronometer and Tape Measure in Clinic.

Detecting frailty in older adults scheduled for surgery is important to predict the occurrence of adverse outcomes, but because of its complexity, frailty screening is not commonly performed. The objective of the current study was to assess whether frailty can be screened for using automatically measured usual gait speed (UGS) and mid-arm circumference (MAC) in the outpatient clinic. Prospective, cross-sectional study. Geriatric center of a tertiary hospital. Outpatients aged 65 and older (N = 113). Frailty status was evaluated according to a multidimensional frailty score (MFS) using a comprehensive geriatric assessment, and participants were classified into 5 categories. UGS was evaluated by having participants walk through the clinic using an automated laser-gated chronometer. MAC was recorded using a tape measure on a blood pressure cuff. Correlations between these two physical measurements and MFS were assessed. The mean age of the 93 participants who successfully underwent UGS evaluation was 75.8 ± 4.7; 35 were male. In this population, the mean Charlson Comorbidity Index was 2.2 ± 1.4, mean MFS was 4.1 ± 2.0, and 20 participants were considered to be at high risk of experiencing adverse outcomes. Mean UGS was 0.75 ± 0.16 m/s, and mean MAC was 31.2 ± 1.9 cm); both physical parameters were correlated with MFS (UGS: standardized beta = -0.420, P < .001; MAC: standardized beta = -0.457, P < .001). Using UGS and MFS, the area under curve of receiver operating curve for determining which participants were at high risk of experiencing adverse outcomes was 0.809 (P < .001). UGS and MAC are viable methods of clinically screening for frailty.

A Review of Frailty Syndrome and Its Physical, Cognitive and Emotional Domains in the Elderly.

Background: Frailty, a very important complication of increasing age, is a well-recognised concept although it has not been accurately measured in the clinical setting. The aim of this literature review is to summarise commonly used frailty screening tools, and to describe how new measurement methods have been developed recently. Methods: Several frailty measurement tools including the most cited and newly developed scales have been described in this review. We searched the MEDLINE using the search terms; “frailty score, scale, tool, instrument, index, phenotype” and then summarised selected tools for physical, cognitive, emotional and co-morbidity domains. Results: The most cited frailty measurement methods developed from 1999 to 2005 are primarily criteria for physical frailty (e.g., frailty phenotype). More recently developed tools (e.g., triad of impairment and multidimensional frailty score) consider cognitive and emotional domains in addition to physical deficit in measuring frailty. Co-morbidity has also been considered as a domain of frailty in several measurement tools. Conclusion: Although frailty tools have traditionally assessed physical capability, cognitive and emotional impairment often co-exist in older adults and may have shared origins. Therefore, newer tools which provide a composite measure of frailty may be more relevant for future use.

Is Frailty a Modifiable Risk Factor of Future Adverse Outcomes in Elderly Patients with Incident End-Stage Renal Disease?

Little is known about the clinical significance of frailty and changes of frailty after dialysis initiation in elderly patients with end-stage renal disease (ESRD). We prospectively enrolled 46 elderly patients with incident ESRD at a dialysis center of a tertiary hospital between May 2013 and March 2015. Frailty was assessed by using a comprehensive geriatric assessment protocol and defined as a multidimensional frailty score of ≥ 10. The main outcome was the composite of all-cause death or cardiovascular hospitalization, as determined in June 2016. The median age of the 46 participants was 71.5 years, and 63.0% of them were men. During the median 17.7 months follow-up, the rate of composite outcome was 17.4%. In multivariate logistic regression analysis, after adjusting for age, sex, diabetes, body mass index (BMI), and time of predialytic nephrologic care, female sex, and increased BMI were associated with increased and decreased odds of frailty, respectively. In multivariate Cox proportional hazards analysis, after adjusting for age, sex, diabetes, BMI, and time of predialytic nephrologic care, frailty was significantly associated with the composite adverse outcome. In repeated frailty assessments, the multidimensional frailty score significantly improved 12 months after the initiation of dialysis, which largely relied on improved nutrition. Therefore, frailty needs to be assessed for risk stratification in elderly patients with incident ESRD.

Prediction of Postoperative Complications Using Multidimensional Frailty Score in Older Female Cancer Patients with American Society of Anesthesiologists Physical Status Class 1 or 2

Even low-risk, elderly patients are at increased risk for postoperative morbidity compared with their younger counterparts. We sought to evaluate the role of a scoring model in predicting adverse surgical outcomes in low-risk, older, female cancer patients. From October 2011 to May 2014, two hundred and eighty-one low-risk female patients (aged 65 years and older, American Society of Anesthesiologists class 1 or 2) undergoing curative cancer surgery were included. The Multidimensional Frailty Score (MFS) was calculated by comprehensive geriatric assessment. The primary end point was postoperative complication (eg, pneumonia, urinary tract infection, delirium, acute pulmonary thromboembolism, and unplanned ICU admission). Secondary outcomes were length of hospital stay and institutionalization. Twenty patients experienced postoperative complications and 15 patients were discharged to nursing facilities. The fully adjusted odds ratio (OR) per 1-point increase in MFS was 1.412 (95% CI, 1.012-1.969; p = 0.042) for postoperative complications, 1.377 (95% CI, 0.935-2.026; p = 0.105) for institutionalization, and 1.411 (95% CI, 1.110-1.793; p = 0.005) for prolonged hospital stay. The high-risk group (MFS ≥7) showed an increased risk for postoperative complications (OR = 8.513; 95% CI, 2.210-32.785; p = 0.002), institutionalization (OR = 1.291; 95% CI, 0.324-5.152; p = 0.717), and prolonged hospital stay (OR = 2.336; 95% CI, 1.090-5.006; p = 0.029) compared with the low-risk group (MFS <7), after adjusting confounders. Multidimensional Frailty Score based on a preoperative comprehensive geriatric assessment is useful for predicting postoperative complications and prolonged hospital stay, even in low-risk elderly women who are undergoing cancer surgery.

Multidimensional frailty score for the prediction of postoperative mortality risk.

The number of geriatric patients who undergo surgery has been increasing, but there are insufficient tools to predict postoperative outcomes in the elderly. To design a predictive model for adverse outcomes in older surgical patients. From October 19, 2011, to July 31, 2012, a single tertiary care center enrolled 275 consecutive elderly patients (aged ≥65 years) undergoing intermediate-risk or high-risk elective operations in the Department of Surgery. The primary outcome was the 1-year all-cause mortality rate. The secondary outcomes were postoperative complications (eg, pneumonia, urinary tract infection, delirium, acute pulmonary thromboembolism, and unplanned intensive care unit admission), length of hospital stay, and discharge to nursing facility. Twenty-five patients (9.1%) died during the follow-up period (median [interquartile range], 13.3 [11.5-16.1] months), including 4 in-hospital deaths after surgery. Twenty-nine patients (10.5%) experienced at least 1 complication after surgery and 24 (8.7%) were discharged to nursing facilities. Malignant disease and low serum albumin levels were more common in the patients who died. Among the geriatric assessment domains, Charlson Comorbidity Index, dependence in activities of daily living, dependence in instrumental activities of daily living, dementia, risk of delirium, short midarm circumference, and malnutrition were associated with increased mortality rates. A multidimensional frailty score model composed of the above items predicted all-cause mortality rates more accurately than the American Society of Anesthesiologists classification (area under the receiver operating characteristic curve, 0.821 vs 0.647; P = .01). The sensitivity and specificity for predicting all-cause mortality rates were 84.0% and 69.2%, respectively, according to the model's cutoff point (>5 vs ≤5). High-risk patients (multidimensional frailty score >5) showed increased postoperative mortality risk (hazard ratio, 9.01; 95% CI, 2.15-37.78; P = .003) and longer hospital stays after surgery (median [interquartile range], 9 [5-15] vs 6 [3-9] days; P < .001). The multidimensional frailty score based on comprehensive geriatric assessment is more useful than conventional methods for predicting outcomes in geriatric patients undergoing surgery.