Literature DB >> 32212087

Frailty Predicts Morbidity and Mortality After Laparoscopic Cholecystectomy for Acute Cholecystitis: An ACS-NSQIP Cohort Analysis.

Alexander M Fagenson1, Benjamin D Powers2, Konstantinos A Zorbas3, Sunil Karhadkar1, Andreas Karachristos4, Antonio Di Carlo1, Kwan N Lau5.   

Abstract

BACKGROUND: Current guidelines recommend laparoscopic cholecystectomy be offered for patients with acute cholecystitis except those deemed as high risk. Few studies have examined the impact of frailty on outcomes for patients undergoing laparoscopic cholecystectomy. Therefore, the aim of this study was to determine the association of frailty with postoperative morbidity and mortality in patients undergoing laparoscopic cholecystectomy for acute cholecystitis.
METHODS: Patients undergoing laparoscopic cholecystectomy for acute cholecystectomy were identified from 2005 to 2010 in the American College of Surgeons National Surgical Quality Improvement Project (NSQIP). The Modified Frailty Index (mFI) was used a surrogate for frailty, and patients were stratified as non-frail (mFI 0), low frailty (mFI 1-2), intermediate frailty (mFI 3-4) and high frailty (mFI ≥ 5). Univariable and multivariable analyses were performed. Receiver operator curves (ROC) and an area under the curve (AUC) were generated to determine accuracy of mFI in predicting postoperative morbidity and mortality.
RESULTS: Of the 6898 patients undergoing laparoscopic cholecystectomy, 3245 (47%) patients were non-frail. There were 2913 (42%) patients with low-frailty, 649 (9%) patients with intermediate frailty, and 91 (2%) with high frailty. Clavien IV complications were higher for intermediate frail patients (OR 1.81, 95% CI 1.00-3.28, p = 0.050) and high-frail patients (OR 4.59, 95% CI 1.98-10.7, p < 0.001). Additionally, mortality was higher for patients with intermediate frailty (OR 4.69, 95% CI 1.37-16.0, p = 0.014) and high frailty (OR 12.2, 95% CI 2.67-55.5, p = 0.001). The mFI had excellent accuracy for mortality (AUC = 0.83) and Clavien IV complications (AUC = 0.73).
CONCLUSION: Frailty is associated with postoperative morbidity and mortality in patients undergoing laparoscopic cholecystectomy for acute cholecystitis.

Entities:  

Keywords:  Acute cholecystitis; Frailty; Laparoscopic cholecystectomy; Outcomes research

Mesh:

Year:  2020        PMID: 32212087      PMCID: PMC7222970          DOI: 10.1007/s11605-020-04570-1

Source DB:  PubMed          Journal:  J Gastrointest Surg        ISSN: 1091-255X            Impact factor:   3.452


Introduction

Laparoscopic cholecystectomy (LC) is the standard treatment for acute cholecystitis (AC), and is one of the most common operations performed with 460,000 cholecystectomies performed annually in the USA.[1] Given the high incidence of AC in the US population, many patients present with multiple comorbidities are at risk for complications. For these higher risk patients, operative mortality rates for LC approach 20%.[2] Gallbladder drainage in the form of a percutaneous cholecystotomy tube has been recommended as an acceptable option for these higher risk patients.[3] Newer technologies including endoscopic ultrasound-guided drainage and cryoablation are now being offered.[4]–[7] While guidelines have often characterized high-risk patients as those who are critically ill and/or elderly, few studies have examined the impact of frailty among patients undergoing laparoscopic cholecystectomy.[2],[8]–[11] Earlier version of the 2013 Tokyo guidelines focused on clinically related characteristics of cholecystitis. The 2018 revisions of Tokyo guidelines incorporated the Charlson Comorbidity Index (CCI) and American Society of Anesthesiologists (ASA) classification to account for patient-specific factors.[12] Conventional risk assessment scores, such as ASA score, Model for End-stage-Liver Disease (MELD) score, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Albumin-Bilirubin score (ALBI), and Child-Pugh-Turcotte (CPT) score are of limited use. They either include limited number of preoperative factors, focus on a single organ state, or were constructed for other purposes. Thus, there is a need to identify preoperative clinical variables for high-risk patients with acute cholecystitis undergoing cholecystectomy that encompass the concept of frailty. Frailty is an established method used to study outcomes in surgery. One of the most widely used frailty assessment tools is the frailty index from the Canadian Study on Health and Aging (CSHA).[13] In 2013, Velanovich described a simplified edition of the CSHA frailty index, which was named the Modified Frailty Index (mFI).[14] The mFI was created by mapping the variables in the American College of Surgeons National Surgical Quality Improvement Project (NSQIP) database used to calculate the CSHA score. Several studies have shown that frailty is predictive of morbidity and prolonged postoperative recovery.[11],[15]–[19] Few studies have been done to evaluate the role of mFI for preoperative risk assessment of patients with cholecystitis. Therefore, the aim of this study was to determine if the mFI was associated with postoperative morbidity and mortality in patients undergoing laparoscopic cholecystectomy for acute cholecystitis.

Methods

Patients undergoing non-emergent laparoscopic cholecystectomy from 2005 to 2010 for acute or acute-on-chronic cholecystitis were identified in the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) participant use file at the national level. The ACS NSQIP is a nationally validated, risk-adjusted, outcomes-based program that collects data on a prospective systematic sample of patients undergoing major surgery. Patients were identified based on Current Procedural Terminology (CPT) codes and International Classification of Disease (ICD-9) codes. Primary CPT codes utilized were 47562, 47563, 47564, 47600, 47605, and 47610, and a secondary CPT code: 47579 was present in the cases of CPT 47600 and 47610 (both “removal of gallbladder”). The ICD-9 code: 575.12 was used to identify patients with cholecystitis.

Modified Frailty Index Calculation

The mFI consists of 11 NSQIP preoperative variables. One point was allotted for each of the following preoperative comorbidities: (1) patient functional status; (2) diabetes mellitus treated with insulin or oral medications; (3) hypertension requiring treatment; (4) congestive heart failure (CHF); (5) myocardial infarction (MI); (6) prior cardiac surgery or percutaneous coronary angioplasty, or history of angina; (7) chronic obstructive pulmonary disease (COPD) or pneumonia, (8) rest pain or gangrene secondary to peripheral vascular disease (PVD) or PVD treated with angioplasty, revascularization, amputation; (9) impaired sensorium within 48 h prior to the surgical procedure not in the context of concomitant neurologic disease such as dementia; (10) history of transient ischemic attack (TIA) or cerebrovascular accident (CVA) without neurologic deficits; and (11) CVA with neurologic deficits. Possible mFI values range from 0 to 11. Total mFI was calculated, and patients were stratified based on their mFI score and classified as non-frail (mFI 0), low frailty (mFI 1–2), intermediate frailty (mFI 3–4), or high frailty (mFI ≥ 5) (Table 1) .
Table 1

Demographics of the study groups

No frailty (n = 3245)Low frailty (n = 2913)Intermediate frailty (n = 649)High frailty (n = 91)p value
Age, years, median (IQR)42 (31–54)63 (52–74)72 (63–79)72 (66–78)< 0.001
Male, n (%)1112 (34)1498 (51)435 (67)60 (66)< 0.001
White, n (%)1458 (45)1387 (48)305 (47)38 (42)0.149
Body mass index, kg/m228.3 (24.7–33.0)29.6 (25.6–33.9)28.5 (24.8–33.4)29.2 (25.4–34.6)< 0.001
ASA ≥ 3, n (%)431 (13)1567 (57)605 (93)87 (96)< 0.001
Albumin ≤ 3.5 g/dl, n (%)732 (28)1113 (46)396 (68)68 (81)< 0.001
Bilirubin ≥ 1.2 mg/dl, n (%)601 (20)825 (30)188 (31)32 (36)< 0.001
SGOT ≥ 40 U/L834 (28)788 (29)196 (32)38 (43)0.006
Creatinine ≥ 1.2 mg/dl, n (%)185 (6.2)659 (24)291 (46)56 (62)< 0.001
Platelet ≤ 150, n (%)186 (6.0)369 (13)117 (19)21 (23)< 0.001
Hematocrit ≤ 35, n (%)638 (21)895 (32)322 (51)69 (76)< 0.001
White blood cell ≥ 111088 (35)1138 (40)302 (48)50 (55)< 0.001
Preoperative variables included in calculation of mFI
Dependent functional status, n (%)0 (0)261 (9.0)275 (42)78 (86)< 0.001
Diabetes mellitus, n (%)0 (0)662 (23)402 (62)75 (83)< 0.001
Hypertension, n (%)0 (0)2392 (82)610 (94)87 (96)< 0.001
CHF, n (%)0 (0)24 (0.8)37 (5.7)27 (30)< 0.001
History of MI within 6 months, n (%)0 (0)13 (0.4)35 (5.4)14 (15)< 0.001
History of PCI/CS/Angina, n (%)0 (0)218 (7.5)193 (30)31 (34)< 0.001
COPD or pneumonia, n (%)0 (0)136 (4.7)132 (20)29 (32)<0.001
PVD, n (%)0 (0)19 (0.7)60 (9.2)27 (30)< 0.001
Impaired sensorium, n (%)0 (0)18 (0.6)45 (6.9)25 (28)< 0.001
TIA/CVA without residual deficit, n (%)0 (0)71 (2.4)70 (11)23 (25)< 0.001
CVA/stroke with residual deficit, n (%)0 (0)42 (1.4)94 (15)42 (46)< 0.001

No frailty = mFI 0, Low frailty = mFI 1–2, Intermediate frailty = mFI 3–4, High frailty = mFI ≥ 5

ASA American Society of Anesthesiologists, SGOT serum glutamic-oxaloacetic transaminase, CHF congestive heart failure, MI myocardial infarction, PCI percutaneous coronary intervention, CS cardiac surgery, COPD chronic obstructive pulmonary disease, PVD peripheral vascular disease, TIA transient ischemic attack, CVA cerebrovascular accident; italic font represents statistically significant associations

Demographics of the study groups No frailty = mFI 0, Low frailty = mFI 1–2, Intermediate frailty = mFI 3–4, High frailty = mFI ≥ 5 ASA American Society of Anesthesiologists, SGOT serum glutamic-oxaloacetic transaminase, CHF congestive heart failure, MI myocardial infarction, PCI percutaneous coronary intervention, CS cardiac surgery, COPD chronic obstructive pulmonary disease, PVD peripheral vascular disease, TIA transient ischemic attack, CVA cerebrovascular accident; italic font represents statistically significant associations

Population Baseline Characteristics

Baseline demographic, laboratory, and clinical data were compared. Patients’ demographic variables included age, gender, race (categorized as white or other) and body mass index (BMI), and ASA score. Preoperative laboratory variables analyzed were serum albumin, total serum bilirubin, serum glutamic-oxaloacetic transaminase (SGOT), creatinine, platelet count, hematocrit, and white blood cell count.

Outcomes

Postoperative outcomes assessed included 30-day mortality and standard 30-day postoperative outcomes as routinely collected by NSQIP including superficial surgical site infection (SSI), deep SSI surgical site infection, organ space SSI surgical site infection, sepsis, septic shock, myocardial infarction (MI), cardiac arrest requiring cardiopulmonary resuscitation (CPR), pneumonia, reintubation, ventilator dependence (failure to wean from mechanical ventilation > 48 h after surgery), progressive renal insufficiency with no requirement for dialysis, acute renal failure with need of dialysis, urinary tract infection, deep venous thrombosis, stroke, length of stay, and operative time. Clavien class IV complications are life-threatening complications that lead to single-organ or multi-organ dysfunction, requiring intensive care unit (ICU) management. In our study, Clavien class IV complications are any of the following complications in the NSQIP database: cardiac arrest requiring CPR, MI, pulmonary embolism, postoperative acute renal failure requiring dialysis, septic shock, failure to wean from mechanical ventilation > 48 h after surgery, and unplanned postoperative reintubation.

Statistical Analysis

Categorical variables were expressed as frequencies (n) with percentages, and continuous variables were expressed as medians with interquartile range (IQR). Normality of continuous data was measured by the Kolgomorov-Smirnov tests and continuous data was of non-normal distribution. Univariable analysis was performed by the chi square and Mann-Whitney U tests for categorical and continuous variables respectively. A backward stepwise multivariable logistic regression analysis was used to identify risk factors for mortality and Clavien class IV complications. Factors that were significant on univariable analysis (p < 0.05) were included in the multivariable model. The impact of each individual frailty component was studied, and the odds of mortality and Clavien class IV complications were calculated for each mFI component. Results from multivariable analysis were reported as odds ratios (OR), 95% confidence interval (95% CI), and p value. Receiver operator characteristic curves (ROC) and an area under the curve (AUC) were generated to measure accuracy of mFI in predicting mortality and Clavien class IV complications. Statistical analysis was performed using SPSS version 26 (IBM). Two-tailed p values of less than 0.05 were deemed statistically significant. The study used de-identified data and was exempt from the Temple University Hospital Institutional Review Board.

Results

Demographics

A total of 6898 patients underwent laparoscopic cholecystectomy for acute cholecystitis from 2005 to 2010. The preoperative characteristics for each group are shown in Table 1. The median age was 55 years (IQR 40–69), 55% were female (n = 3793), and the median BMI was 28.7 kg/m2 (IQR 25.1–33.4). 3245 (47%) patients were non-frail (mFI 0), 2913 (42%) patients with low frailty (mFI 1–2), 649 (9%) with intermediate frailty (mFI 3–4), and 91 (2%) high frailty (mFI ≥ 5) patients. Increasing age, male gender, ASA score ≥ 3, hypoalbuminemia, hyperbilirubinemia, elevated SGOT, elevated creatinine, thrombocytopenia, low hematocrit, and elevated WBC count all significantly increased as frailty increased (p < 0.001) (Table 1). The individual frailty components as calculated in the mFI are also illustrated in Table 1.

Postoperative Outcomes

Postoperative mortality and morbidity classified by frailty groups are shown in Table 2. An increasing rate of morality and Clavien class IV complications were observed as frailty increased. For the intermediate frailty group, the mortality rate was 6.0% (p < 0.001) and Clavien IV complication rate was 11% (p < 0.001) (Table 2). The mortality rate for the high frailty group was 20% (p < 0.001) and rate of Clavien IV complications was 28% (p < 0.001) (Table 2). Length of stay and operative time were significantly longer as frailty increased (both p < 0.001).
Table 2

30-day postoperative outcomes

No frailty (n = 3245)Low frailty (n = 2913)Intermediate frailty (n = 649)High frailty (n = 91)p value
Mortality, n (%)6 (0.2)38 (1.3)39 (6.0)18 (20)< 0.001
Clavien IV complications, n (%)48 (1.5)156 (5.4)73 (11)25 (28)< 0.001
Superficial SSI, n (%)37 (1.1)65 (2.2)18 (2.8)4.0 (4.4)< 0.001
Deep incisional SSI, n (%)7.0 (0.2)12 (0.4)6.0 (0.9)4.0 (4.4)< 0.001
Organ space SSI, n (%)28 (0.9)45 (1.5)11 (1.7)2.0 (2.2)0.052
Pneumonia, n (%)11 (0.3)54 (1.9)31 (4.8)6.0 (6.6)< 0.001
Reintubation, n (%)11 (0.3)54 (1.9)31 (4.8)8.0 (8.8)< 0.001
Pulmonary embolism, n (%)4.0 (0.1)11 (0.4)3 (0.5)0 (0)0.162
Deep venous thrombosis, n (%)5.0 (0.2)9.0 (0.3)7.0 (1.1)1.0 (1.1)0.001
Ventilator dependence, n (%)5.0 (0.2)55 (1.9)49 (7.6)16 (18)< 0.001
Progressive renal insufficiency, n (%)3.0 (0.1)28 (1.0)11 (1.7)9.0 (9.9)<0.001
Acute renal failure, n (%)3.0 (0.1)18 (0.6)10 (1.5)7.0 (7.7)< 0.001
Urinary tract infection, n (%)12 (0.4)42 (1.4)12 (1.8)2 (2.2)< 0.001
Stroke, n (%)0 (0)6.0 (0.2)6.0 (0.9)1.0 (1.1)< 0.001
Cardiac arrest requiring CPR, n (%)30 (0.1)8.0 (0.3)10 (1.5)7.0 (7.7)< 0.001
Myocardial infarction, n (%)2.0 (0.1)13 (0.4)13 (2.0)0 (0)< 0.001
Sepsis, n (%)29 (0.9)66 (2.3)23 (3.5)8.0 (8.8)< 0.001
Septic shock, n (%)12 (0.4)39 (1.3)28 (4.3)8.0 (8.8)< 0.001
Reoperation, n (%)37 (1.1)81 (2.8)34 (5.2)8.0 (8.8)< 0.001
Length of stay, days, median (IQR)2 (1–4)4 (2–6)7 (4–11)13 (7–23)< 0.001
Operative time, minutes, median (IQR)75 (52–104)84 (59–115)84 (63–118)87 (68–112)< 0.001

No frailty = mFI 0, Low frailty = mFI 1–2, Intermediate frailty = mFI 3–4, High frailty = mFI ≥ 5; SSI, surgical site infection; italic font represents statistically significant associations

30-day postoperative outcomes No frailty = mFI 0, Low frailty = mFI 1–2, Intermediate frailty = mFI 3–4, High frailty = mFI ≥ 5; SSI, surgical site infection; italic font represents statistically significant associations Univariable and multivariable regression analyses for postoperative Clavien class IV (CLIVCs) complications are shown in Table 3. After multivariable regression, intermediate and high frailty were significantly associated with an increased risk for postoperative CLIVCs (OR 1.81, 95% CI 1.00–3.28, p = 0.050 and OR 4.59, 95% CI 1.98–10.7, p < 0.001) (Table 3). An ASA ≥ 3 placed patients at increased risk (OR 3.34, 95% CI 1.72–6.50, p < 0.001) for CLIVCs; however, age ≥ 65 years (OR 1.16, 95% CI 0.58–2.29, p = 0.551) and male sex (OR 0.95, 95% CI 0.52–1.72, p = 0.860) were not associated with an increased risk of CLIVCs.
Table 3

Factors associated with Clavien IV complications

UnivariableMultivariable
OR95% CIp valueOR95% CIp value
Frailty
  No frailtyRefRef
  Low frailty3.772.72–5.23< 0.0011.731.15–2.610.009
  Intermediate frailty8.445.80–12.28< 0.0011.811.00–3.280.050
  High frailty25.214.7–43.4< 0.0014.591.98–10.7< 0.001
Age ≥ 65 years2.401.91–3.03< 0.0011.160.58–2.290.551
Male (vs female)1.701.35–2.15< 0.0010.950.52–1.720.860
BMI ≥ 301.160.92–1.470.203
White (vs others)0.840.66–1.060.138
ASA ≥ 3, n (%)6.314.75–8.40< 0.0013.341.72–6.50< 0.001
Albumin ≤ 3.5 g/dl, n (%)3.232.49–4.190.0011.861.00–3.490.051
Bilirubin ≥ 1.2 mg/dl, n (%)1.791.40–2.28< 0.0011.150.61–2.180.663
SGOT ≥ 40 U/L1.751.38–2.23< 0.0011.160.65–2.080.617
Creatinine ≥ 1.2 mg/dl, n (%)3.522.77–4.49< 0.0011.360.64–2.900.420
Platelet ≤ 150, n (%)2.111.56–2.86< 0.0010.770.33–1.810.547
Hematocrit ≤35, n (%)2.792.21–3.54< 0.0011.470.78–2.800.238
White blood cell ≥ 112.001.58–2.53< 0.0011.310.75–2.300.339

No frailty = mFI 0, Low frailty = mFI 1–2, Intermediate frailty = mFI 3–4, High Frailty = mFI ≥ 5

BMI body mass index, ASA American Society of Anesthesiologists, SGOT, serum glutamic-oxaloacetic transaminase; italic font represents statistically significant associations

Factors associated with Clavien IV complications No frailty = mFI 0, Low frailty = mFI 1–2, Intermediate frailty = mFI 3–4, High Frailty = mFI ≥ 5 BMI body mass index, ASA American Society of Anesthesiologists, SGOT, serum glutamic-oxaloacetic transaminase; italic font represents statistically significant associations Univariable and multivariable regression analyses for postoperative mortality are shown in Table 4. Intermediate and high frailty patients were at increased risk for postoperative mortality (OR 4.69, 95% CI 1.37–16.0, p = 0.014 and OR 12.2, 95% CI 2.67–55.5, p = 0.001). While low frailty (mFI 1–2), age ≥ 65 years, male sex, ASA ≥ 3, albumin, bilirubin, SGOT, creatinine, WBC, and hematocrit were not associated with an increased risk for mortality.
Table 4

Factors associated with mortality

UnivariableMultivariable
OR95% CIp valueOR95% CIp value
Frailty
No frailtyRefRef
Low frailty7.143.01–16.9< 0.0011.440.51–4.100.494
Intermediate frailty34.514.6–81.9< 0.0014.691.37–16.00.014
High frailty133.151.4–345.1< 0.00112.22.67–55.50.001
Age ≥ 65 years5.203.40–7.96< 0.0012.240.62–8.070.217
Male (vs female)1.591.07–2.370.0200.770.26–2.330.647
BMI ≥ 300.700.46–1.060.091
White (vs others)1.060.71–1.560.790
ASA ≥ 3, n (%)29.411.9–72.4< 0.0016.040.99–36.890.052
Albumin ≤ 3.5 g/dl, n (%)7.154.09–12.51< 0.0011.430.38–5.380.594
Total bilirubin ≥ 1.2 mg/dl, n (%)3.882.58–5.85< 0.0011.730.57–5.220.330
SGOT ≥ 40 U/L2.811.87–4.25< 0.0011.980.65–6.010.228
Creatinine ≥ 1.2, n (%)5.463.65–8.17< 0.0011.260.38–4.190.712
Platelet ≤ 150, n (%)4.032.62–6.22< 0.0011.030.27–3.880.966
Hematocrit ≤ 35, n (%)5.303.47–8.10< 0.0011.440.38–5.500.591
White blood cell ≥ 111.711.15–2.550.0081.990.68–5.810.209

No frailty = mFI 0, Low frailty = mFI 1–2, Intermediate frailty = mFI 3–4, High frailty = mFI ≥ 5

BMI body mass index, ASA American Society of Anesthesiologists, SGOT, serum glutamic-oxaloacetic transaminase; italic font represents statistically significant associations

Factors associated with mortality No frailty = mFI 0, Low frailty = mFI 1–2, Intermediate frailty = mFI 3–4, High frailty = mFI ≥ 5 BMI body mass index, ASA American Society of Anesthesiologists, SGOT, serum glutamic-oxaloacetic transaminase; italic font represents statistically significant associations An analysis of the adjusted risk of each frailty component toward CLIVCs is shown in Table 5. After multivariable regression, dependent functional status (OR 4.28, 95% CI 3.21–5.71, p < 0.001), hypertension (OR 2.45, 95% CI 1.85–3.21, p < 0.001), COPD or pneumonia preoperatively (OR 1.80, 95% CI 1.21–2.68, p = 0.004), and diabetes mellitus (OR 1.42, 95% CI 1.07–1.87, p = 0.013) placed patients at increased risk for postoperative CLIVCs (Table 5).
Table 5

Individual frailty components associated with Clavien IV complications

UnivariableMultivariable
OR95% CIp valueOR95% CIp value
Dependent functional status (vs independent)6.495.03–8.35< 0.0014.283.21–5.71< 0.001
Diabetes mellitus2.652.07–3.40< 0.0011.421.07–1.870.013
Hypertension3.612.78–4.68< 0.0012.451.85–3.25< 0.001
Congestive heart failure5.493.19–9.43< 0.0011.800.97–3.310.061
History of MI within 6 months3.301.56–6.990.0011.360.59–3.120.471
History of PCI/CS/angina1.991.38–2.87< 0.0011.070.62–1.600.726
COPD or pneumonia3.402.36–4.91< 0.0011.801.21–2.680.004
Peripheral vascular disease3.151.74–5.69< 0.0011.090.57–2.070.791
Impaired sensorium5.483.19–9.43< 0.0011.550.85–2.830.155
TIA/CVA without residual deficit2.801.69–4.63< 0.0011.380.80–2.360.244
CVA/stroke with residual deficit3.071.91–4.91< 0.0010.860.51–1.440.561

MI myocardial infarction, PCI percutaneous coronary intervention, CS cardiac surgery, COPD chronic obstructive pulmonary disease, TIA transient ischemic attack, CVA cerebrovascular accident; italic font represents statistically significant associations

Individual frailty components associated with Clavien IV complications MI myocardial infarction, PCI percutaneous coronary intervention, CS cardiac surgery, COPD chronic obstructive pulmonary disease, TIA transient ischemic attack, CVA cerebrovascular accident; italic font represents statistically significant associations An analysis of the adjusted risk of each frailty component toward mortality is shown in Table 6. Dependent functional status (OR 9.28, 95% CI 5.81–14.8, p < 0.001), hypertension (OR 1.83, 95% CI 1.09–3.06, p = 0.023), congestive heart failure (OR 2.72, 95% CI 1.27–5.84, p = 0.010), history of PCI/CS/Angina (OR 2.03, 95% CI 1.25–3.30, p = 0.004), COPD or pneumonia (OR 3.11, 95% CI 1.87–5.17, p < 0.001), and impaired sensorium (OR 4.34, 95% CI 2.25–8.38, p < 0.001) were all significantly associated with an increased risk for postoperative mortality (Table 6).
Table 6

Individual frailty components associated with mortality

UnivariableMultivariable
OR95% CIp valueOR95% CIp value
Dependent functional status (vs Independent)18.011.9–27.1< 0.0019.285.81–14.8< 0.001
Diabetes mellitus3.122.08–4.70< 0.0011.260.78–2.040.341
Hypertension4.032.54–6.39< 0.0011.831.09–3.060.023
Congestive heart failure14.67.95–26.9< 0.0012.721.27–5.840.010
History of MI within 6 months4.791.71–13.50.0010.990.29–3.390.990
History of PCI/CS/angina2.191.21–3.950.0082.031.25–3.300.004
COPD or pneumonia8.185.20–12.8< 0.0013.111.87–5.17< 0.001
Peripheral vascular disease2.710.98–7.500.0460.480.15–1.500.204
Impaired sensorium20.811.9–36.5< 0.0014.342.25–8.38< 0.001
TIA/CVA without residual deficit3.151.44–6.900.0021.590.63–4.030.328
CVA/stroke with residual deficit4.342.22–8.48< 0.0010.660.31–1.430.295

MI myocardial infarction, PCI percutaneous coronary intervention, CS cardiac surgery, COPD chronic obstructive pulmonary disease, TIA transient ischemic attack, CVA cerebrovascular accident; italic font represents statistically significant associations

Individual frailty components associated with mortality MI myocardial infarction, PCI percutaneous coronary intervention, CS cardiac surgery, COPD chronic obstructive pulmonary disease, TIA transient ischemic attack, CVA cerebrovascular accident; italic font represents statistically significant associations Receiver operator characteristic curves (ROC) demonstrate that the mFI can accurately predict mortality and CLVCs in this patient cohort. The area under the curve (AUC) for mortality was 0.83, while the AUC for CLIVCs was 0.73 (Fig. 1).
Fig. 1

Receiver operator characteristic curves (ROC) of modified frailty index (mFI) for a mortality and b Clavien IV complications

Receiver operator characteristic curves (ROC) of modified frailty index (mFI) for a mortality and b Clavien IV complications

Discussion

In this analysis, we show that frailty as measured by mFI is associated with increased postoperative morbidity and mortality for patients undergoing laparoscopic cholecystectomy for acute cholecystitis. Frailty is associated with an increased risk for death up to 12-fold for patients with high-frailty. Confirmed by ROC analysis, mFI is sensitive and specific for predicting postoperative CLIVCs (AUC 0.73) and mortality (AUC 0.83) (Fig. 1). Additionally, individual frailty components were studied and demonstrated that dependent functional status carried the most risk in contributing to postoperative morbidity (OR 4.28, 95% CI 3.21–5.71, p < 0.001) and mortality (OR 9.28, 95% CI 5.81–14.8, p < 0.001) (Tables 5 and 6). Studying individual frailty components is important to generate procedure-specific variables that may be utilized in future frailty scoring systems. The application of mFI using the NSQIP database has allowed for the use of a prognostic model to a heterogeneous population for a single disease process to measure clinical outcomes. Frailty is a marker for the sum of overall physiologic status and a useful tool to determine the risk of postoperative complications. Multiple models exist for calculating frailty, including the Frailty Index of Cumulative Deficits, Fried’s Frailty Phenotype, and the Frailty Index of Accumulative Deficit.[20] These models have been noted to have limitations as they are burdened by either increasing complexity or too simplistic which translates to limited predictability. Despite the increasing variety of frailty models, there is no universally accepted frailty definition or components. However, the mFI strikes a reasonable balance and has demonstrated clinical utility in colorectal, pancreatic, hepatic, vascular, and gynecologic surgery.[15],[21]–[23] Recently, Murphy and colleagues have studied the impact of frailty on outcomes for patients undergoing various emergency general surgical procedures using mFI.[11] In their analysis, 14% of patients underwent a cholecystectomy, and high frail patients were more likely to suffer a serious complications (OR 2.7, 95% CI 1.7–6.3) and were less likely to be discharged home (OR 0.25, 95% CI 0.19–0.33). Our study corroborates these findings in patients undergoing non-emergent cholecystectomy. Patients with low frailty had an increased risk of CLIVCs (OR 1.73, 95% CI 1.15–2.61, p = 0.009) but no increased risk of mortality (OR 1.44, 95% CI 0.51–4.10, p = 0.494). Enhanced risk stratification using the mFI, which can detect those with intermediate and high frailty, can allow patients to have their comorbidities optimized. These patients might be treated with intravenous antibiotics and placement of percutaneous cholecystostomy tube. Following medical therapy, frail patients can undergo preoperative rehabilitation known as “prehab,” which has shown to improve surgical outcomes.[24],[25] Thus, the mFI is a useful tool for preoperative risk stratification that affects clinical decision making. This study highlights the importance of individual frailty components and their risk towards postoperative morbidity and mortality. In fact, the 2018 Tokyo guidelines has added more patient specific factors including neurological dysfunction, ASA, and CCI to improve its accuracy.[12] On the other hand, the mFI has recently decreased the number of variables from 11 to 5, including the omission of impaired sensorium. In our study, impaired sensorium was a strong predictor of mortality (OR 4.34, 95% CI 2.25–8.38, p < 0.001) (Table 6). We believe that the decrease in the number of frailty components from 11 to 5 may diminish the predictive accuracy. Furthermore, a weighted frailty risk score incorporating the individual frailty components might produce the best procedure-specific risk score. Age is often utilized as a surrogate for frailty and to identify high-risk patients. However, data is conflicted with respect to age and outcomes following cholecystectomy.[26]–[28] Kanakala and colleagues analyzed 2117 patients undergoing LC from the UK at a single institution and found no association between increasing age and complications following LC.[26] Conversely, Murphy et al. utilized the National Inpatient Sample and studied 1,102,071 patients from 1998 to 2006 and found advanced age (> 65 years old) to be associated with increased complications (OR 2.16, 95% CI 2.01–2.32) and conversion to an open procedure (OR 2.61, 95% CI 2.42–2.81).[27] Furthermore, Giger et al. studied 22,953 patients undergoing LC from a Swiss national database and found increased age to be associated with increased rate of intraoperative and postoperative local/systemic complications (all p < 0.001).[28] Our multivariable regression revealed that age was not associated with an increased rate of CLIVCs (OR 1.16, 95% CI 0.58–2.29, p = 0.551) or mortality (OR 2.24, 95% CI 0.62–8.07, p = 0.217) (Tables 3 and 4).Instead, increasing frailty was significantly (p < 0.001) associated with postoperative CLIVCs and mortality (Tables 3 and 4). This suggests that with the advances in perioperative care, older patients can undergo laparoscopic cholecystectomy without an increased risk of complications and mortality. This study is not without limitations. While NSQIP variables are collected in a prospective fashion, the mFI was retrospectively applied to patients which may lead to misclassification error. Percutaneous cholecystostomy tube placement data are not collected by NSQIP and therefore no comparison can be made to patients undergoing this procedure. In addition, we are unable to identify those patients who undergo cholecystectomy after percutaneous drainage. We also acknowledge that some of the variables in the mFI are no longer collected in NSQIP. We argue they should be brought back in, especially impaired sensorium which carried an increased risk of postoperative mortality.

Conclusion

In summary, this study demonstrates the association of frailty with postoperative morbidity and mortality in patients undergoing laparoscopic cholecystectomy for acute cholecystitis. Increasing frailty however is significantly associated with Clavien IV complications and mortality while age is not. The mFI should be considered as a tool to aid in risk stratification and clinical decision making for patients who are traditionally thought to be high risk or the elderly. Individualized assessment of patients by frailty components may assist in the decision to pursue cholecystectomy or an alternative treatment option. Future research is needed to corroborate the findings in this retrospective cohort study.
  27 in total

1.  Endoscopic transduodenal drainage of the gallbladder: implications for endoluminal treatment of gallbladder disease.

Authors:  Todd H Baron; Mark D Topazian
Journal:  Gastrointest Endosc       Date:  2006-12-01       Impact factor: 9.427

Review 2.  Tokyo Guidelines 2018: diagnostic criteria and severity grading of acute cholecystitis (with videos).

Authors:  Masamichi Yokoe; Jiro Hata; Tadahiro Takada; Steven M Strasberg; Horacio J Asbun; Go Wakabayashi; Kazuto Kozaka; Itaru Endo; Daniel J Deziel; Fumihiko Miura; Kohji Okamoto; Tsann-Long Hwang; Wayne Shih-Wei Huang; Chen-Guo Ker; Miin-Fu Chen; Ho-Seong Han; Yoo-Seok Yoon; In-Seok Choi; Dong-Sup Yoon; Yoshinori Noguchi; Satoru Shikata; Tomohiko Ukai; Ryota Higuchi; Toshifumi Gabata; Yasuhisa Mori; Yukio Iwashita; Taizo Hibi; Palepu Jagannath; Eduard Jonas; Kui-Hin Liau; Christos Dervenis; Dirk J Gouma; Daniel Cherqui; Giulio Belli; O James Garden; Mariano Eduardo Giménez; Eduardo de Santibañes; Kenji Suzuki; Akiko Umezawa; Avinash Nivritti Supe; Henry A Pitt; Harjit Singh; Angus C W Chan; Wan Yee Lau; Anthony Yuen Bun Teoh; Goro Honda; Atsushi Sugioka; Koji Asai; Harumi Gomi; Takao Itoi; Seiki Kiriyama; Masahiro Yoshida; Toshihiko Mayumi; Naoki Matsumura; Hiromi Tokumura; Seigo Kitano; Koichi Hirata; Kazuo Inui; Yoshinobu Sumiyama; Masakazu Yamamoto
Journal:  J Hepatobiliary Pancreat Sci       Date:  2018-01-09       Impact factor: 7.027

3.  Accumulating deficits model of frailty and postoperative mortality and morbidity: its application to a national database.

Authors:  Vic Velanovich; Heath Antoine; Andrew Swartz; David Peters; Ilan Rubinfeld
Journal:  J Surg Res       Date:  2013-02-01       Impact factor: 2.192

4.  Preoperative frailty and quality of life as predictors of postoperative complications.

Authors:  Adrienne Saxton; Vic Velanovich
Journal:  Ann Surg       Date:  2011-06       Impact factor: 12.969

5.  Frailty as a predictor of surgical outcomes in older patients.

Authors:  Martin A Makary; Dorry L Segev; Peter J Pronovost; Dora Syin; Karen Bandeen-Roche; Purvi Patel; Ryan Takenaga; Lara Devgan; Christine G Holzmueller; Jing Tian; Linda P Fried
Journal:  J Am Coll Surg       Date:  2010-04-28       Impact factor: 6.113

6.  Frailty index predicts severe complications in gynecologic oncology patients.

Authors:  Shitanshu Uppal; Elena Igwe; Laurel W Rice; Ryan J Spencer; Stephen L Rose
Journal:  Gynecol Oncol       Date:  2015-01-17       Impact factor: 5.482

7.  Simplified frailty index to predict adverse outcomes and mortality in vascular surgery patients.

Authors:  Joseph Karam; Athanasios Tsiouris; Alexander Shepard; Vic Velanovich; Ilan Rubinfeld
Journal:  Ann Vasc Surg       Date:  2013-05-24       Impact factor: 1.466

8.  Effect of diabetes on outcomes in patients undergoing emergent cholecystectomy for acute cholecystitis.

Authors:  Efstathios Karamanos; Emre Sivrikoz; Elizabeth Beale; Linda Chan; Kenji Inaba; Demetrios Demetriades
Journal:  World J Surg       Date:  2013-10       Impact factor: 3.352

9.  Frailty predicts risk of life-threatening complications and mortality after pancreatic resections.

Authors:  Toms Augustin; Matthew D Burstein; Eric B Schneider; Gareth Morris-Stiff; Jane Wey; Sricharan Chalikonda; R Matthew Walsh
Journal:  Surgery       Date:  2016-08-18       Impact factor: 3.982

10.  Endoscopic ultrasound guided gallbladder drainage - is it ready for prime time?

Authors:  Umesha Boregowda; Chandraprakash Umapathy; Arpitha Nanjappa; Helen Wong; Madhav Desai; Marina Roytman; Thimmaiah Theethira; Shreyas Saligram
Journal:  World J Gastrointest Pharmacol Ther       Date:  2018-12-05
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  5 in total

1.  Mortality risk estimation in acute calculous cholecystitis: beyond the Tokyo Guidelines.

Authors:  Ana María González-Castillo; Juan Sancho-Insenser; Maite De Miguel-Palacio; Josep-Ricard Morera-Casaponsa; Estela Membrilla-Fernández; María-José Pons-Fragero; Miguel Pera-Román; Luis Grande-Posa
Journal:  World J Emerg Surg       Date:  2021-05-11       Impact factor: 5.469

2.  The Correlation Between Case Total Work Relative Value Unit, Operative Stress, and Patient Frailty: Retrospective Cohort Study.

Authors:  Katherine M Reitz; Patrick R Varley; Nathan L Liang; Ada Youk; Elizabeth L George; Myrick C Shinall; Paula K Shireman; Shipra Arya; Edith Tzeng; Daniel E Hall
Journal:  Ann Surg       Date:  2021-10-01       Impact factor: 13.787

3.  Association between modified frailty index and surgical outcomes in intradural skull base surgery.

Authors:  Khodayar Goshtasbi; Arash Abiri; Brandon M Lehrich; Mehdi Abouzari; Harrison W Lin; Hamid R Djalilian; Frank P K Hsu; Edward C Kuan
Journal:  J Clin Neurosci       Date:  2021-07-26       Impact factor: 2.116

4.  Strategies to Promote ResiliencY (SPRY): a randomised embedded multifactorial adaptative platform (REMAP) clinical trial protocol to study interventions to improve recovery after surgery in high-risk patients.

Authors:  Katherine Moll Reitz; Christopher W Seymour; Jennifer Vates; Melanie Quintana; Kert Viele; Michelle Detry; Michael Morowitz; Alison Morris; Barbara Methe; Jason Kennedy; Brian Zuckerbraun; Timothy D Girard; Oscar C Marroquin; Stephen Esper; Jennifer Holder-Murray; Anne B Newman; Scott Berry; Derek C Angus; Matthew Neal
Journal:  BMJ Open       Date:  2020-09-29       Impact factor: 2.692

5.  Frailty in elderly patients with acute appendicitis.

Authors:  Alexander Reinisch; Martin Reichert; Christian Charles Ondo Meva; Winfried Padberg; Frank Ulrich; Juliane Liese
Journal:  Eur J Trauma Emerg Surg       Date:  2022-02-02       Impact factor: 2.374

  5 in total

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