Preoperative Predictors of Discharge Destination after Endovascular Repair of Abdominal Aortic Aneurysms

Readmissions Following Endovascular Thoracic and Thoracoabdominal Aortic Repairs in The Vascular Implant Surveillance and Interventional Outcomes Network (VISION)

OBJECTIVES

Investigate readmission rates, diagnoses associated with readmission, and associations with mortality through 90-days post-operatively after elective endovascular thoracic and thoracoabdominal aortic repair overall and by extent of coverage.

METHODS

A cohort of index elective non-traumatic endovascular thoracic and thoracoabdominal aortic cases from 2010-2018 was derived from the Vascular Implant Surveillance and Interventional Outcomes Network. Cohort readmissions within 90-days postoperative were examined both overall and by Crawford extent (CE) of aortic coverage. Postoperative mortality was examined by reason for readmission and CE.

RESULTS

The cohort consisted of 2,093 patients who underwent endovascular thoracic and thoracoabdominal aortic repair (1,541 CE 0A/0B; 240 CE 1-3; 312 CE 4-5). Cumulative risk for 90-day readmission was 34.3% in CE 0A/0B repairs, 33.4% in CE4-5 repairs and 47.4% in CE 1-3 repairs. Compared to CE 0A/B, patients with CE 1-3 repairs experienced an increased risk of readmission within 90 days postoperatively after adjusting for preoperative factors (aHR 1.27(1.00,1.61) while the readmission risk for CE 4-5 repairs did not differ significantly (aHR 0.83 (0.64,1.06). Significant risk factors for 90-day readmission included COPD, dialysis dependence, limited ambulation, visceral/spinal ischemia, and in-hospital stroke. Discharge to home was protective against readmission (HR 0.65, CI 0.54-0.79). Patients with a readmission within 90-days had a 7.89-fold increase in 90-day mortality (HR 7.84; 5.17, 11.9) compared to those not readmitted.

CONCLUSIONS

Increasing extent of endovascular thoracic and thoracoabdominal aortic repair was associated with higher 90-day readmission rates. Readmission for all CE was associated with near 8-fold increased risk of mortality. Risk factors associated with increased risk for readmission included pulmonary insufficiency, renal disease, and poor functional status. These findings can inform stakeholders about investment of resources to improve processes of care that both target prevention and mitigate risk of readmission after elective endovascular thoracic and thoracoabdominal aortic repair.

[Inpatient rehabilitation for patients 65 years and older with abdominal aortic aneurysm repair: Indications and long-term outcome]

BACKGROUND

In Germany, there is no data available on the frequency of inpatient rehabilitation (IR) after elective endovascular (EVAR) and open (OAR) abdominal aortic aneurysm (AAA) repair.

OBJECTIVE

To report for the first time on the outcome of patients 65 years and older and thus of retirement age with and without IR after AAA repair in a retrospective analysis of routine data from all eleven regional companies of the AOK health insurance fund (AOK-Gesundheit).

METHODS

Anonymized data of 16,358 patients 65 years and older with intact abdominal aortic aneurysm treated with EVAR (n = 12,960) or OAR (n = 3,398) between 01/01/2010 and 12/31/2016 were analyzed. Patients with postoperative IR (n = 1,531) were compared to those without postoperative IR (n = 14,827) with respect to general patient characteristics, comorbidities, perioperative and postoperative outcomes, and survival. The average follow-up of patients with postoperative and without postoperative IR was 49.9 months and 51.8 months, respectively.

RESULTS

5.4% of EVAR patients, but 24.6% of OAR patients were referred to IR (p < 0.001). Patients with IR were sicker than those without IR. Parameters significantly influencing the use of IR included OAR vs EVAR (Odds Ratio [OR] 6.03), condition after cerebral infarction (OR 1.53), and women vs men (OR 1.49). Perioperative influencing parameters were cerebral infarction (OR 2.40), blood transfusions (OR 2.21) and complex critical care (OR 2.15). After nine years, the Kaplan-Meier estimated survival was 41.9% for patients with vs 43.4% for those without IR in the EVAR group (p = 0.178). For OAR, it was 50.2% for patients with IR vs 49.8% for patients without IR (p = 0.006). In multivariate regression analysis, postoperative IR had a significant effect on long-term survival in OAR but not in EVAR patients.

CONCLUSION

There are no generally binding guidelines for the indication of IR after AAA repair. It should therefore be a requirement for the future that the fitness of each patient with elective AAA repair be determined with a score before and after the procedure in order to make indications for AHB more comparable. The score should be documented in the hospital discharge letter.

Preoperative predictors of nonhome discharge after fenestrated-branched endovascular repair of complex abdominal and thoracoabdominal aortic aneurysms

BACKGROUND

Nonhome discharge (NHD) has significant implications for patient counseling and discharge planning and is frequently required following fenestrated-branched endovascular aortic repair (FB-EVAR) of complex abdominal aortic aneurysms (CAAA) and thoracoabdominal aortic aneurysms (TAAA). We aimed to identify preoperative predictors of NHD after elective FB-EVAR for CAAA and TAAA and develop a risk calculator able to predict NHD.

METHODS

A retrospective review of prospectively collected data on all patients undergoing FB-EVAR between January 2007 and December 2021 at a single institution was performed. Exclusion criteria were admission from a nonhome setting, emergency and repeat FB-EVAR, and discharge to an unknown destination. The cohort was randomly split into separate development (70% of patients) and validation (30%) cohorts to develop a predictive calculator for NHD. Independent variables associated with NHD were assessed in a series of logistic regression analyses from 100 bootstrapped samples of the development set, and a model was developed using the most predictive variables. Resulting parameter estimates were applied to data in the validation set to assess model discrimination and calibration.

RESULTS

From the initial cohort of 712 FB-EVAR patients, 644 were included in the study (74% male; mean age, 75.4 ± 7.6 years), including 452 with CAAA (70%) and 192 with TAAA (30%). Early mortality occurred in eight patients (1.2%; 5 in CAAA and 3 in TAAA) and the median hospital stay was 5 days (4 for CAAA and 7 for TAAA). Ninety-seven patients (15%) had a NHD. On multivariable analysis, older age (per year, odds ratio [OR], 1.08; P < .001), female gender (OR, 3.03; P < .001), smoking (OR, 2.86; P = .01), congestive heart failure (OR, 3.05; P = .004), peripheral artery disease (OR, 1.81; P = .07), and extent I (OR, 3.17), II (OR, 2.84), and III (OR, 2.52; all P = .08) TAAAs were associated with an increased likelihood of NHD in the development set. Based on these factors, the risk calculator was developed which accurately predicts NHD in the validation set with an area under the curve of 0.7.

CONCLUSIONS

Older, female smokers with congestive heart failure and peripheral artery disease and more extensive aneurysms are at highest risk of NHD after FB-EVAR. Using only preoperative factors, our risk calculator can predict accurately who will have a NHD, allowing enhanced preoperative patient counselling and accelerated hospital discharge.

Development and Validation of a Novel Preoperative Risk Score to Identify Patients at Risk for Nonhome Discharge after Elective Endovascular Aortic Aneurysm Repair (EVAR)

BACKGROUND

Nonhome discharge (NHD) to a rehabilitation or skilled nursing facility after elective endovascular aortic repair (EVAR) is uncommon. However, NHD after surgery has an important impact on patient quality of life and postdischarge outcomes. Understanding factors that put patients undergoing EVAR at high risk for NHD is essential to providing adequate preoperative counseling and shared decision making. This study aimed to identify independent predictors of NHD following elective EVAR and to create a clinically useful preoperative risk score.

METHODS

Elective EVAR cases were queried from the Society for Vascular Surgery Vascular Quality Initiative 2014-2018. A risk score was created by splitting the data set into two-thirds for development and one-third for validation. A parsimonious stepwise hierarchical multivariable logistic regression controlling for hospital level variation was performed in the development dataset, and the beta-coefficients were used to assign points for a risk score. The score was then validated, and model performance assessed.

RESULTS

Overall, 24,426 patients were included and 932 (3.8%) required NHD. Multivariable analysis in the development group identified independent predictors of NHD, which were used to create a 20-point risk score. Patients were stratified into 3 groups based upon their risk score: low risk (0-7 points; n = 16,699) with an NHD rate of 1.8%, moderate risk (8-13 points; n = 7,315) with an NHD rate of 7.3%, and high risk (≥14 points; n = 412) with an NHD rate of 21.8%. The risk score had good predictive ability with c-statistic = 0.75 for model development and c-statistic = 0.73 in the validation dataset.

CONCLUSIONS

This novel risk score can predict NHD following EVAR using characteristics that can be identified preoperatively. Utilization of this score may allow for improved risk assessment, preoperative counseling, and shared decision making.

Comparative Analysis of Morbidity and Mortality Outcomes in Elderly and Nonelderly Patients Undergoing Elective TEVAR: A Systematic Review and Meta-Analysis

OBJECTIVE

Due to an ever-increasing ageing population and limited available data around the use of thoracic endovascular aortic repair (TEVAR) in elderly patients, investigating its efficacy and safety in this age cohort is of vital importance. We thus reviewed the existing literature on this topic to assess the feasibility of TEVAR in elderly patients with severe thoracic aortic pathologies.

METHODS

We identified all original research studies that assessed TEVAR in elderly patients published up to 2023. Morbidity, as assessed by neurological and respiratory complications, endoleaks, and length of stay, was the primary endpoint. Short-term mortality and long-term survival were the secondary endpoints. The Mantel-Haenszel random and fixed effects methods were used to calculate the odds ratios for each outcome. Further sensitivity and subgroup analyses were performed to validate the outcomes.

RESULTS

Twelve original studies that evaluated elective TEVAR outcomes in elderly patients were identified. Seven studies directly compared the use of TEVAR between an older and a younger patient group. Apart from a shorter hospital stay in older patients, no statistically significant difference between the morbidity outcomes of the two different cohorts was found. Short-term mortality and long-term survival results favoured the younger population.

CONCLUSIONS

The present meta-analysis indicates that, due to a safe perioperative morbidity profile, TEVAR should not be contraindicated in patients based purely on old age. Further research using large patient registries to validate our findings in elderly patients with specific aortic pathologies and both elective and emergency procedures is necessary.

Predicting Non-home Discharge After Lung Surgery: Analysis of the General Thoracic Surgery Database

BACKGROUND

Anticipating the need for non-home discharge (NHD) enables improved patient counseling and expedites placement, potentially reducing length of stay and hospital readmission. The objective of this study was to create a simple, preoperative, clinical prediction tool for NHD using The Society of Thoracic Surgeons General Thoracic Surgery Database (STS GTSD).

METHODS

The STS GTSD was queried for patients who underwent elective anatomic lung cancer resection between 2009 and 2019. Exclusion criteria included age <18 years, percentage predicted diffusion capacity of the lung for carbon monoxide <20% or >150%, N3 or M1 disease, incomplete datasets, and mortality. The primary outcome was defined as discharge to an extended care, transitional care, rehabilitation center, or another hospital. Multivariable logistic regression was used to select risk factors and a nomogram for predicting risk of NHD was developed. The approach was cross-validated in 100 replications of a training set consisting of randomly selected two-thirds of the cohort and a validation set of remaining patients.

RESULTS

A total of 35 948 patients from the STS GTSD met inclusion criteria. Final model variables used to derive the nomogram for NHD risk prediction included age (P < .001), percentage predicted diffusion capacity of the lung for carbon monoxide (P < .001), open surgery (P < .001), cerebrovascular history (P < .001), and Zubrod score (P < .001). The receiver operating characteristic curve, using sensitivities and specificities of the model, yielded area under the curve of 0.74. In 100 replicated cross-validations, out-of-sample area under the curve ranged from 0.72-0.76.

CONCLUSIONS

Using readily available preoperative variables, our nomogram prognosticates the risk of NHD after anatomic lung resection with good discriminatory ability. Such risk stratification can enable improved patient counseling and facilitate better planning of patients' postoperative needs.

Evaluating Social Determinants of Health Variables in Advanced Analytic and Artificial Intelligence Models for Cardiovascular Disease Risk and Outcomes: A Targeted Review

Introduction/Purpose

Predictive models incorporating relevant clinical and social features can provide meaningful insights into complex interrelated mechanisms of cardiovascular disease (CVD) risk and progression and the influence of environmental exposures on adverse outcomes. The purpose of this targeted review (2018-2019) was to examine the extent to which present-day advanced analytics, artificial intelligence, and machine learning models include relevant variables to address potential biases that inform care, treatment, resource allocation, and management of patients with CVD.

Methods

PubMed literature was searched using the prespecified inclusion and exclusion criteria to identify and critically evaluate primary studies published in English that reported on predictive models for CVD, associated risks, progression, and outcomes in the general adult population in North America. Studies were then assessed for inclusion of relevant social variables in the model construction. Two independent reviewers screened articles for eligibility. Primary and secondary independent reviewers extracted information from each full-text article for analysis. Disagreements were resolved with a third reviewer and iterative screening rounds to establish consensus. Cohen's kappa was used to determine interrater reliability.

Results

The review yielded 533 unique records where 35 met the inclusion criteria. Studies used advanced statistical and machine learning methods to predict CVD risk (10, 29%), mortality (19, 54%), survival (7, 20%), complication (10, 29%), disease progression (6, 17%), functional outcomes (4, 11%), and disposition (2, 6%). Most studies incorporated age (34, 97%), sex (34, 97%), comorbid conditions (32, 91%), and behavioral risk factor (28, 80%) variables. Race or ethnicity (23, 66%) and social variables, such as education (3, 9%) were less frequently observed.

Conclusions

Predictive models should adjust for race and social predictor variables, where relevant, to improve model accuracy and to inform more equitable interventions and decision making.

Predicting Elective Surgical Patient Outcome Destination Based on the Preoperative Modified Frailty Index and Laboratory Values

INTRODUCTION

To determine the accuracy of preoperative modified frailty index (mFI) with or without laboratory values (mFI-labs or labs-continuous) in predicting postoperative discharge destination. Discharge destination is important to providers and patients. The ability to accurately predict discharge destination preoperatively can improve hospital resource utilization and help set patient and family expectations.

METHODS

Cohort analysis of the 2018 American College of Surgeon National Surgical Quality Improvement Project (ACS-NSQIP) Participant Use File of patients undergoing operations with complete data point sets: age, sex, operation work relative-value units; mFI-clinical based on 12 clinical findings, mFI-labs based on seven laboratory values. The nine hierarchical destinations: home, home with assistance, multi-level community, unskilled-care facility, rehabilitation facility, skilled-nursing facility, acute care hospital, hospice, or death, from best to worst outcome. Data were analyzed using univariate analysis, multiple logistic regression and supervised learning artificial neural networks.

RESULTS

Univariate and multivariate in general showed that patients with higher mFI-clinical and mFI-lab scores, as well as older age and more complex operations were more likely to be discharged to facilities other than home. However, these statistical techniques could not predict the exact destination. An artificial neural network analysis demonstrated perfect location prediction in 64.9% of cases and within one level of prefect prediction is 87.4%.

CONCLUSIONS

Using a limited number of preoperative factors, combining the mFI-clinical with laboratory values significantly improves the destination prediction performance significantly better than using the values separately. Preoperative knowledge of the likely discharge destination can benefit postoperative care planning and delivery.

Sex-specific criteria for repair should be utilized in patients undergoing aortic aneurysm repair

OBJECTIVE

Female patients are more likely to undergo repair of intact and ruptured abdominal aortic aneurysm (AAA) at smaller aortic diameter compared with male patients. By adjusting for inherent anatomic differences between sexes, aortic size index (ASI) and aortic height index (AHI) may provide an additional method for guiding treatment. We therefore analyzed sex-specific criteria for AAA repair using aortic diameter, ASI, and AHI.

METHODS

We identified all patients who underwent AAA repair between 2003 and 2019 in the Vascular Quality Initiative database. The Dubois and Dubois formula was used to calculate body surface area; aortic diameter was divided by body surface area to calculate ASI. Aortic diameter was divided by height to calculate AHI. Cumulative distribution curves were used to plot the proportion of patients who underwent repair of ruptured aneurysm according to aortic diameter, ASI, and AHI. Multivariable logistic regression modeling was used to identify the association of female sex with perioperative mortality and any major postoperative complication.

RESULTS

We identified 55,647 patients, of whom 12,664 were female (20%). For both intact and rupture repair, female patients were older, less likely to undergo endovascular aneurysm repair, and more likely to have comorbid conditions. Female patients underwent repair at smaller median aortic diameter compared with male patients for intact (5.4 vs 5.5 cm; P < .001) and rupture repair (6.7 vs 7.7 cm; P < .001). However, ASI was higher in female patients for both intact (3.1 vs 2.7 cm/m²; P < .001) and rupture repair (3.8 vs 3.7 cm/m²; P < .001), whereas AHI was higher in female patients for intact repair (3.3 vs 3.1 cm/m; P < .001) but lower for rupture repair (4.1 vs 4.3 cm/m; P < .001). When analyzing the cumulative distribution of rupture repair in male patients, 12% of rupture repairs were performed at an aortic diameter below 5.5 cm. To achieve the same proportion of rupture repair in female patients, the repair diameter was only 4.9 cm. However, when ASI and AHI were used, female and male patients both reached 12% of rupture repair at an ASI of 2.7 cm/m² and an AHI of 3.0 cm/m.

CONCLUSION

Our study provides data to strongly support the sex-specific 5.0-cm aortic diameter threshold suggested for repair in female patients by the Society for Vascular Surgery. The high percentage of patients undergoing rupture repair below 5.5 cm in male patients and 5.0 cm in female patients highlights the need to better identify patients at risk of rupture at smaller aortic diameters.

Risk Factors and Clinical Outcomes of Nonhome Discharge in Patients With Acute Decompensated Heart Failure: An Observational Study

Background

No clinical studies have focused on the factors associated with discharge destination in patients with acute decompensated heart failure.

Methods and Results

Of 4056 consecutive patients hospitalized for acute decompensated heart failure in the KCHF (Kyoto Congestive Heart Failure) registry, we analyzed 3460 patients hospitalized from their homes and discharged alive. There were 3009 and 451 patients who were discharged to home and nonhome, respectively. We investigated the factors associated with nonhome discharge and compared the outcomes between home discharge and nonhome discharge. Factors independently and positively associated with nonhome discharge were age ≥80 years (odds ratio [OR],1.76; 95% CI,1.28–2.42), body mass index ≤22 kg/m² (OR,1.49; 95% CI,1.12–1.97), poor medication adherence (OR, 2.08; 95% CI,1.49–2.88), worsening heart failure (OR, 2.02; 95% CI, 1.46–2.82), stroke during hospitalization (OR, 3.74; 95% CI, 1.75–8.00), functional decline (OR, 12.24; 95% CI, 8.74–17.14), and length of hospital stay >16 days (OR, 4.14; 95% CI, 3.01–5.69), while those negatively associated were diabetes mellitus (OR, 0.69; 95% CI, 0.51–0.94), cohabitants (OR, 0.62; 95% CI, 0.46–0.85), and ambulatory state before admission (OR, 0.25; 95% CI, 0.18–0.36). The cumulative 1‐year incidence of all‐cause death was significantly higher in the nonhome discharge group than in the home discharge group. The nonhome discharge group compared with the nonhome discharge group was associated with a higher adjusted risk for all‐cause death (hazard ratio, 1.66; P<0.001).

Conclusions

The discharge destination of patients with acute decompensated heart failure is influenced by factors such as prehospital social background, age, body mass index, low self‐care ability, events during hospitalization (worsening heart failure, stroke, etc), functional decline, and length of hospital stay; moreover, the prognosis of nonhome discharge patients is worse than that of home discharge patients.

Registration Information

clinicaltrials.gov. Identifier: NCT02334891.

Depression Predicts Non-Home Discharge After Abdominal Aortic Aneurysm Repair

BACKGROUND

Mental health's impact on vascular surgical patients has long been overlooked. While outside the expertise of most surgeons, understanding the role that depression plays in the postoperative course could provide additional insight into opportunities to improve surgical outcomes and healthcare value. Additionally, non-home discharge (NHD) to a rehabilitation or skilled nursing facility after surgery is associated with impaired quality of life and higher postdischarge complications, readmissions, and mortality. We hypothesized that depression would be associated with an increased risk for NHD following abdominal aortic aneurysm (AAA) repair.

METHODS

Nonruptured AAA repair cases were identified from the National Inpatient Sample (NIS) using ICD-9 codes between 2005 and 2014. Depression, comorbidities, postoperative complications, and discharge destination were evaluated using statistical tests as appropriate to the data. A hierarchical multivariable logistic regression controlling for hospital level variation was used to examine the independent association between depression, and the primary outcome of NHD controlling for median income and confounders meeting P < 0.05 on univariate analysis.

RESULTS

There were 99,934 total cases analyzed, of which 4,755 (4.8%) were diagnosed with depression and 10,618 (11.9%) required NHD. Patients with depression were younger, more likely to be women, white, have diabetes, chronic obstructive pulmonary disease, hypertension, tobacco use, and more likely to experience a postoperative complication. On adjusted multivariable analysis, patients with depression were more likely to require NHD (odds ratio [OR] 1.87, 95% confidence interval [CI]: 1.68-2.08, c-statistic = 0.82). On stratified analysis by operative approach, depression had a larger effect estimate in endovascular repair (OR 2.19; 95% CI: 1.90-2.52) versus open repair (OR 1.60; 95% CI: 1.38-1.87).

CONCLUSIONS

In a nationally representative sample, patients with depression were more likely to require NHD after AAA repair. This study highlights the importance that depression plays in postoperative outcomes after AAA repair. Furthermore, addressing mental health preoperatively has the potential to improve outcomes in patients undergoing AAA repair.

A novel preoperative risk score for nonhome discharge after elective thoracic endovascular aortic repair

BACKGROUND

Nonhome discharge (NHD) to a rehabilitation or skilled nursing facility after vascular surgery is poorly described despite its large impact on patients. Understanding postsurgical NHD risk is essential to providing adequate preoperative counseling and shared decision making, particularly for elective surgeries. We aimed to identify independent predictors of NHD after elective thoracic endovascular aortic repair (TEVAR) for thoracic aortic aneurysms (TAA) and to create a clinically useful preoperative risk score.

METHODS

Elective TEVAR cases for descending TAA were queried from the Society for Vascular Surgery Vascular Quality Initiative from 2014 to 2018. A risk score was created by splitting the dataset into two-thirds for model development and one-third for validation. A parsimonious stepwise hierarchical multivariable logistic regression controlling for hospital level variation was performed in the development dataset, and the beta-coefficients were used to assign points for a risk score. This score was then cross-validated and model performance assessed.

RESULTS

Overall, 1469 patients were included and 213 (14.5%) required NHD. At baseline, patients who required NHD were more likely to be ≥80 years old (35.2% vs 19.4%), female (58.7% vs 40.6%), functionally dependent (42.3% vs 24.0%), and anemic (46.5% vs 27.8%), and to have chronic obstructive pulmonary disease (41.3% vs 33.4%), congestive heart failure (18.8% vs 11.1%), and American Society of Anesthesiologists class ≥4 (51.6% vs 39.8%; all P < .05). Multivariable analysis in the development group identified independent predictors of NHD that were used to create an 18-point risk score. Patients were stratified into three groups based upon their risk score: low risk (0-7 points; n = 563) with an NHD rate of 4.3%, moderate risk (8-11 points; n = 701) with an NHD rate of 17.0%, and high risk (≥12 points; n = 205) with an NHD rate of 34.2%. The risk score had good predictive ability with a c-statistic of 0.75 for model development and a c-statistic of 0.72 in the validation dataset.

CONCLUSIONS

This novel risk score can predict NHD after TEVAR for TAA using characteristics that can be identified preoperatively. The use of this score may allow for improved risk assessment, preoperative counseling, and shared decision making.

Risk score for nonhome discharge after lower extremity bypass

OBJECTIVE

Patients undergoing lower extremity bypass (LEB) for peripheral artery disease require intensive health care resource utilization including rehabilitation and skilled nursing facilities. However, few studies have evaluated factors that lead to nonhome discharge (NHD) in this population of patients. This study sought to predict NHD by preoperative risk factors in patients undergoing LEB for peripheral artery disease using a novel risk score.

METHODS

The Vascular Study Group of New England database was queried for elective LEB for peripheral artery disease including claudication and critical limb ischemia from 2003 to 2017. Patients were excluded if the procedure was not elective, if they were not admitted from home, if they were bedridden, or if they died during the index admission. Only preoperative factors were considered in the analysis. The primary end point was NHD including rehabilitation and skilled nursing facilities. Data were split two-thirds for model derivation and one-third for validation. In the derivation cohort, bivariate analysis assessed the association of preoperative factors with NHD. A parsimonious manual stepwise binary logistic regression for NHD aimed at maximizing the C statistic while maintaining model simplicity was performed. A risk score was developed using the β coefficients and applied to the validation data set. The risk score performance was assessed using a C statistic and Hosmer-Lemeshow test for model fit.

RESULTS

There were 10,145 cases included with an overall NHD rate of 26.4% (n = 2676). Mean age was 66 years (range, 41-90 years). NHD patients were older (72 years vs 64 years; P < .01) and more frequently male (57.2% vs 42.8%; P < .01) and nonwhite (16.1% vs 9.9%; P < .01); they more frequently had tissue loss (54.2% vs 23.0%; P < .01), anemia (16.0% vs 5.3%; P < .01), severe cardiac comorbidity (21.8% vs 10.5%; P < .01), and insulin-dependent diabetes (33.3% vs 18.2%; P < .01). On multivariable analysis, factors associated with NHD included age, sex, nonwhite race, tissue loss, cardiac comorbidity, partial ambulatory deficit, and insulin-dependent diabetes. The C statistic was 0.78 in the derivation group and 0.79 in the validation group, with Hosmer-Lemeshow P > .999. The risk score ranged from 0 to 18, with a mean score of 4 (standard deviation ±3.5). The risk score was divided into low risk (0-4 points; n = 5272 [52%]; NHD = 10.1%]), moderate risk (5-9 points; n = 3663 [36.7%]; NHD = 36.7%), and high risk (≥10 points; n = 1210 [11.9%]; NHD = 66.1%).

CONCLUSIONS

This novel risk score was highly predictive for NHD after LEB for peripheral artery disease using only preoperative comorbidities. High-risk patients account for 12% of LEB but nearly a third of all patients requiring NHD. This risk score can be used preoperatively to determine high-risk patients for NHD, which may help improve preoperative counseling and hospital efficiency by allocating resources appropriately.