Thirty-day readmission after lower extremity bypass in diabetic patients

Epidemiology and Burden of Peripheral Artery Disease in People With Type 2 Diabetes: A Systematic Literature Review

Type 2 diabetes (T2D) and lower-extremity peripheral artery disease (PAD) are growing global health problems associated with considerable cardiovascular (CV) and limb-related morbidity and mortality, poor quality of life and high healthcare resource use and costs. Diabetes is a well-known risk factor for PAD, and the occurrence of PAD in people with T2D further increases the risk of long-term complications. As the available evidence is primarily focused on the overall PAD population, we undertook a systematic review to describe the burden of comorbid PAD in people with T2D. The MEDLINE, Embase and Cochrane Library databases were searched for studies including people with T2D and comorbid PAD published from 2012 to November 2021, with no restriction on PAD definition, study design or country. Hand searching of conference proceedings, reference lists of included publications and relevant identified reviews and global burden of disease reports complemented the searches. We identified 86 eligible studies, mostly observational and conducted in Asia and Europe, presenting data on the epidemiology (n = 62) and on the clinical (n = 29), humanistic (n = 12) and economic burden (n = 12) of PAD in people with T2D. The most common definition of PAD relied on ankle-brachial index values ≤ 0.9 (alone or with other parameters). Incidence and prevalence varied substantially across studies; nonetheless, four large multinational randomised controlled trials found that 12.5%-22% of people with T2D had comorbid PAD. The presence of PAD in people with T2D was a major cause of lower-limb and CV complications and of all-cause and CV mortality. Overall, PAD was associated with poor quality of life, and with substantial healthcare resource use and costs. To our knowledge, this systematic review provides the most comprehensive overview of the evidence on the burden of PAD in people with T2D to date. In this population, there is an urgent unmet need for disease-modifying agents to improve outcomes.

Insulin Requirement and Infrainguinal Bypass Outcomes in Patients with Peripheral Arterial Disease

BACKGROUND

Diabetes mellitus (DM) is a major risk factor for peripheral artery disease. The association of DM with major adverse limb events (MALE) after lower extremity revascularization remains controversial, as patients with diabetes are typically analyzed as a single, homogenous group. Using a large national database, this study examines the impact of insulin use and glycemic control on the outcomes following infrainguinal bypass. The hypothesis is that prevalent insulin therapy and elevated hemoglobin A1c (HbA1c) are associated with an increased risk of MALEs after infrainguinal bypass in patients with DM and could therefore be used for risk stratification.

METHODS

The Vascular Quality Initiative database files for infrainguinal bypass (2007-2021) were retrospectively reviewed. Patients with DM undergoing bypass for peripheral artery disease were included. Patients on dialysis or with prior kidney transplantation were excluded. The characteristics and outcomes of patients with insulin-requiring diabetes mellitus (IRDM) were compared to those of patients not requiring insulin (noninsulin-requiring diabetes mellitus [NIRDM]) prior to the bypass procedure.

RESULTS

A total of 9,686 patients with DM (56% IRDM) underwent bypass. Patients with IRDM were significantly younger than patients with NIRDM, more likely to be female (P < 0.01), African American (P < 0.01), and Hispanic (P = 0.031), and more likely to have comorbidities and be categorized into American Society of Anesthesiologist classes IV-V. They were more likely to be treated for chronic limb-threatening ischemia (P < 0.001). Patients with IRDM had significantly higher perioperative complications with no difference in perioperative mortality between the 2 groups. Beyond the perioperative period, with a mean follow-up of 427 days, patients with IRDM had significantly lower crude rates of primary patency and higher crude rates of major amputation, MALE, and mortality compared to patients with NIRDM. Regression analyses demonstrated that insulin requirement, but not HbA1c, was independently associated with a higher risk of MALE (hazard ratio = 1.17 [1.06-1.29]) and mortality (hazard ratio = 1.28 [1.16-1.43]).

CONCLUSIONS

Insulin requirement, but not HbA1c, is significantly associated with MALEs and survival after infrainguinal bypass in the Vascular Quality Initiative. Stratification of patients with DM based on their prevalent insulin use prior to infrainguinal bypass surgery could improve the prediction of outcomes of peripheral arterial bypass surgery in patients with diabetes.

Editor's Choice - A Systematic Review and Meta-Analysis of the Incidence and Risk Factors for Re-admission to Hospital in People with Diabetes Related Foot Disease

OBJECTIVE

The aim of this study was to systematically review the incidence and risk factors for 30 day re-admission to hospital following an index admission to treat diabetes related foot disease (DFD).

DATA SOURCES

A literature search was conducted using Medline/PubMed, Scopus, Cochrane Library, and CINAHL databases.

METHODS

The study was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Studies that reported the rate of total or DFD related 30 day re-admissions were included. Meta-analysis was performed using a random effects model to calculate the pooled mean (95% confidence interval [CI]) of the proportion of patients re-admitted to hospital within 30 days. Meta-regression was performed to determine the association between risk factors and 30 day re-admission.

RESULTS

Sixteen retrospective studies with a total of 124 683 participants were included. The mean total 30 day re-admission rate was 22.0% (95% CI 17.0 - 27.0%) while the mean DFD related 30 day re-admission rate was 10.0% (95% CI 7.0 - 15.0%). Meta-regression found that greater prevalence of peripheral neuropathy (p = .045) was associated with a higher rate of any 30 day re-admission, and male sex (p = .023) and private health insurance (p = .048) were associated with lower rates of any 30 day re-admission. Coronary artery disease (p= .025) was associated with a higher rate of DFD related re-admission. All studies had low or moderate risk of bias.

CONCLUSION

This systematic review suggested that about one fifth of patients with DFD are re-admitted to hospital within 30 days, of which about half are to treat DFD. Risk factors for re-admission included female gender, peripheral neuropathy, lack of private health insurance, and coronary artery disease.

Common sampling and modeling approaches to analyzing readmission risk that ignore clustering produce misleading results

Background

There is little consensus on how to sample hospitalizations and analyze multiple variables to model readmission risk. The purpose of this study was to compare readmission rates and the accuracy of predictive models based on different sampling and multivariable modeling approaches.

Methods

We conducted a retrospective cohort study of 17,284 adult diabetes patients with 44,203 discharges from an urban academic medical center between 1/1/2004 and 12/31/2012. Models for all-cause 30-day readmission were developed by four strategies: logistic regression using the first discharge per patient (LR-first), logistic regression using all discharges (LR-all), generalized estimating equations (GEE) using all discharges, and cluster-weighted (CWGEE) using all discharges. Multiple sets of models were developed and internally validated across a range of sample sizes.

Results

The readmission rate was 10.2% among first discharges and 20.3% among all discharges, revealing that sampling only first discharges underestimates a population’s readmission rate. Number of discharges was highly correlated with number of readmissions (r = 0.87, P < 0.001). Accounting for clustering with GEE and CWGEE yielded more conservative estimates of model performance than LR-all. LR-first produced falsely optimistic Brier scores. Model performance was unstable below samples of 6000–8000 discharges and stable in larger samples. GEE and CWGEE performed better in larger samples than in smaller samples.

Conclusions

Hospital readmission risk models should be based on all discharges as opposed to just the first discharge per patient and utilize methods that account for clustered data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-020-01162-0.

Intelligent therapeutic decision support for 30 days readmission of diabetic patients with different comorbidities

The significance of medication therapy in managing comorbid diabetes is vital for maintaining the overall wellness of patients and reducing the cost of healthcare. Thus, using appropriate medication or medication combinations will be necessary for improved person-centred care and reduce complications associated with diagnosis and treatment. This study explains an intelligent decision support framework for managing 30 days unplanned readmission (30_URD) of comorbid diabetes using the Random Forest (RF) algorithm and Bayesian Network (BN) model. After the analysis of the medical records of 101,756 de-identified diabetic patients treated with 21 medications for 28 comorbidity combinations, the optimal medications for minimizing the likelihood of early readmissions were determined. This approach can help for identifying and managing most vulnerable patients thereby giving room to enhance post-discharge monitoring through clinical specialist supports to build critical-self management skills that will minimize the cost of diabetes care.

A systematic review and meta-analysis of risk factors for and incidence of 30-day readmission after revascularization for peripheral artery disease

OBJECTIVE

Readmission to the hospital after revascularization for peripheral artery disease (PAD) is frequently reported. No consensus exists as to the exact frequency and risk factors for readmission. This review aimed to determine the incidence of and risk factors for 30-day readmission after revascularization for PAD.

METHODS

PubMed/Medline (Ovid), Scopus, Web of Science, the Cochrane Library, and CINAHL were searched systematically from inception until May 20, 2018. Studies were eligible for inclusion if they included patients with diagnosed PAD undergoing revascularization and reported the readmission rate and a statistical evaluation of the association of at least one risk factor with readmission. Studies were excluded if data for other procedures could not be distinguished from revascularization. Two authors undertook study selection independently with the final inclusion decision resolved through consensus. The PRISMA and Meta-analyses of Observational Studies in Epidemiology guidelines were followed regarding data extraction and quality assessment, which was performed by two authors independently. Data were pooled using a random effects model.

RESULTS

The primary outcome was readmission within 30 days of revascularization. Fourteen publications reporting the outcomes of 526,008 patients were included. Reported readmission rates ranged from 10.9% to 30.0% with a mean of 16.4% (95% confidence interval [CI], 15.1%-17.9%). Meta-analyses suggested the following risk factors had a significant association with readmission: female sex (odds ratio [OR], 1.13; 95% CI, 1.05-1.21), black race (OR, 1.36; 95% CI, 1.28-1.46), dependent functional status (OR, 1.72; 95% CI, 1.43-2.06), critical limb ischemia (OR, 2.12; 95% CI, 1.72-2.62), emergency admission (OR, 1.75; 95% CI, 1.43-2.15), hypertension (OR, 1.39; 95% CI, 1.26-1.54), heart failure (OR, 1.82; 95% CI, 1.50-2.20), chronic pulmonary disease (OR, 1.19; 95% CI, 1.08-1.32), diabetes (OR, 1.47; 95% CI, 1.32-1.63), chronic kidney disease (OR, 1.93; 95% CI, 1.62-2.31), dialysis dependence (OR, 2.08; 95% CI, 1.75-2.48), smoking (OR, 0.83; 95% CI, 0.78-0.89), postoperative bleeding (OR, 1.70; 95% CI, 1.23-2.35), and postoperative sepsis (OR, 4.13; 95% CI, 2.02-8.47).

CONCLUSIONS

Approximately one in six patients undergoing revascularization for PAD are readmitted within 30 days of their procedure. This review identified multiple risk factors predisposing to readmission, which could potentially serve as a way to target interventions to reduce readmissions.

A Dashboard Prototype for Tracking the Impact of Diabetes on Hospital Readmissions Using a National Administrative Database

Background

Over the past several decades, diabetes mellitus has contributed to a significant disease burden in the general population. Evidence suggests that patients with a coexisting diabetes diagnosis consume more hospital resources, and have higher readmission rates compared to those who do not. Against the backdrop of bundled-payment programs, healthcare systems cannot underestimate the importance of monitoring patient health information at the population level.

Methods

Using the data from the Centers for Medicare and Medicaid Services (CMS) administrative claims database, we created a dashboard prototype to enable hospitals to examine the impact of diabetes on their all-cause readmission rates and financial implications if diabetes was present at the index hospitalization. The technical design involved loading the relevant 10th revision of International Classification of Diseases (ICD-10) codes provided by the medical team and flagging diabetes patients at the claim. These patients were then tagged for readmissions within the same database. The odds ratios were determined based on data from two groups: those with diabetes at index hospitalization which include type 1 only, type 2 only, and type 1 and type 2 diabetes, plus those without diabetes at index hospitalization.

Results

The dashboard presents summary data of diabetes readmissions quality metrics at a national level. Users can visualize summary data of each state and compare odds ratios for readmissions as well as raw hospitalization data at their facility. Dashboard users can also view data classified by a diagnosis-related group (DRG) system. In addition to a “national” data view, for users who inquire about data specific to demographic regions, the DRG view can be further stratified at the state level or county level. At the DRG level, users can view data about the cost per readmissions for all index hospitalization with and without diabetes.

Conclusions

The dashboard prototype offers users a virtual interface which displays visual data for quick interpretation, monitors changes at a population level, and enables administrators to benchmark facility data against local and national trends. This is an important step in using data analytics to drive population level decision making to ultimately improve medical systems.

A Unique All-Payer Rate-Setting System Controls the Cost but Not the Racial Disparity in Lower Extremity Revascularization Procedures

BACKGROUND

Patients with peripheral arterial disease often have high comorbidity burden that may complicate post-interventional course and drive increased health-care expenditures. Racial disparity had been observed in lower extremity revascularization (LER) patterns and outcomes. In 2014, Maryland adopted an all-payer rate-setting system to limit the rising hospitalization costs. This resulted in an aggregate payment system in which hospital compensation takes place as an overall per capita expenditure for hospital services. We sought to examine racial differences and other patient-level factors that might lead to discrepancies in LER hospital costs in the State of Maryland.

METHODS

We used International Classification of Diseases, Ninth Revision codes to identify patients who underwent infrainguinal open bypass (open) and endovascular repair (endo) in the Maryland Health Services Cost Review Commission database (2009-2015). Multivariable generalized linear model regression analysis was conducted to report cost differences adjusting for patient-specific demographics, comorbidities, and insurance status. Logistic regression analysis was used to assess quality metrics: intensive care unit (ICU) admission, 30-day readmission, protracted length of stay (pLOS) (endo: pLOS >9, open: pLOS > 10 days) and in-hospital mortality.

RESULTS

Among patients undergoing open, costs were higher for nonwhite patients (African-American [AA]: $6,092 [4,682-7,501], other: $3,324 [437-6,212]; both P ≤ 0.024), diabetics ($2,058 [837-3,279]; P < 0.001), and patients with Medicaid had an increased cost over Medicare patients by $4,325 (1,441-7,209). Critical limb ischemia (CLI) was associated with $5,254 (4,014-6,495) risk-adjusted cost increment. In addition, AA patients demonstrated higher risk-adjusted odds of ICU admission (adjusted odds ratio [aOR] [95% confidence interval {CI}]:1.65 [1.46-1.86]; P < 0.001) and pLOS (aOR [95% CI]: 1.56 [1.37-1.79]; P < 0.001) than their white counterparts. For patients undergoing endo, costs were higher for nonwhite patients (AA: $2,642 [1,574-3,711], other: $4,124 [2,091-6,157]; both P < 0.001). Patients with CLI and heart failure had increased costs after endo. AA patients were more likely to be readmitted or stayed longer after endo (1.16 [1.03-1.29], 1.34 [1.21-1.49]; both P < 0.010, respectively). The overall cost trend was rapidly increasing before all-payer rate policy implementation but it dramatically plateaued after 2014.

CONCLUSIONS

This study showed that the all-payer rate-setting system has curbed the LER rising costs, but these costs remained disproportionally higher for disadvantaged populations such as AA and Medicaid communities. This underpins the existing racial disparity in LER. AA patients had higher LER costs, most likely driven by extended hospitalization and ICU admission. Efforts could be directed to evaluate the contributing socioeconomic factors, invest in primary prevention of comorbid conditions that had shown to be associated with prohibitive costs, and identify mechanisms to overcome the existing racial disparity in LER within the promising cost-saving payment system at the State of Maryland.

Short- and long-term readmission rates after infrainguinal bypass in a safety net hospital are higher than expected

OBJECTIVE

Readmission rates are expected to have an increasing effect on both the hospital bottom line and physician reimbursements. Safety net hospitals may be most vulnerable. We examined readmissions at 30 days, 90 days, and 1 year in a large safety net hospital to determine the magnitude and effect of short- and long-term readmission rates after lower extremity infrainguinal bypass in this setting.

METHODS

All nonemergent extremity infrainguinal bypass performed at a large safety net hospital between 2008 and 2016 were identified. Patient demographic, social, clinical, and procedural details were extracted from the electronic medical record. An analysis of patients readmitted at 30 days, 90 days, and 1 year was completed to determine the details of the readmission.

RESULTS

A total of 350 patients undergoing extremity infrainguinal bypass were identified. The most frequent indication was tissue loss (57%), followed by claudication (25.6%), and rest pain (17.4%). Patient insurance carriers included Medicare (61.7%), Medicaid (25.4%), and private (13%). The distal target was the popliteal and tibial artery in 52.6% and 47.4% cases, respectively. The majority of bypasses used autologous vein (73.1%). In-hospital complications included pulmonary complications (4.3%), urinary tract infection (3.1%), acute renal failure (2%), graft occlusion (2%), myocardial infarction (1.7%), bleeding (1.4%), surgical wound complications (1.1%), and stroke (0.9%). The 30-day readmission rate was 30% with the most common reasons for readmission being surgical wound complications, nonsurgical foot/leg wounds, nonextremity infectious causes, cardiac ischemia, and congestive heart failure. The 90-day readmission rate was 49.4% and the most common reasons for readmission from 31 to 90 days were nonsurgical foot/leg wounds, graft complications, surgical wound complications, cardiac ischemia, and contralateral leg morbidity. The readmission rate within 1 year was 72.2%. Readmission causes from 91 days to 1 year included graft complications, contralateral leg morbidity, nonextremity infectious, nonsurgical foot/leg wounds, cardiac ischemia, and congestive heart failure. A tibial bypass target was associated with 30-day (odds ratio [OR], 1.69; 95% confidence interval [CI], 1.06-2.69; P = .029) and 90-day (OR, 1.77; 95% CI, 1.14-2.74, P = .011) readmission. Nonprivate insurance (OR, 2.31; 95% CI, 1.17-4.57, P = .016), and critical limb ischemia (OR, 1.77; 95% CI, 1.14-2.74; P = .035) were associated with 1-year readmission.

CONCLUSIONS

Short- and long-term readmission rates in a safety net setting are high. The 30-day rates in this study are higher than historically reported. This data sets baseline rates for 90-day and 1-year readmission for future analyses. Although the majority of short-term readmissions are related to the index procedure, long-term readmission rates are more frequently related to systemic comorbidities. Targeted patient interventions aimed at preventing the most common reasons for readmission may improve readmission rates, particularly among patients with nonprivate insurance. However, other risk factors, such as tibial target, may not be modifiable and a higher readmission rate may need to be accepted in this population.

Risk factors for 30-day unplanned readmission following infrainguinal endovascular interventions

OBJECTIVE

Unplanned hospital readmissions following surgical interventions are associated with adverse events and contribute to increasing health care costs. Despite numerous studies defining risk factors following lower extremity bypass surgery, evidence regarding readmission after endovascular interventions is limited. This study aimed to identify predictors of 30-day unplanned readmission following infrainguinal endovascular interventions.

METHODS

We identified all patients undergoing an infrainguinal endovascular intervention in the targeted vascular module of the American College of Surgeons National Surgical Quality Improvement Program between 2012 and 2014. Perioperative outcomes were stratified by symptom status (chronic limb-threatening ischemia [CLI] vs claudication). Patients who died during index admission and those who remained in the hospital after 30 days were excluded. Indications for unplanned readmission related to the index procedure were evaluated. Multivariable logistic regression was used to identify preoperative and in-hospital (during index admission) risk factors of 30-day unplanned readmission.

RESULTS

There were 4449 patients who underwent infrainguinal endovascular intervention, of whom 2802 (63%) had CLI (66% tissue loss) and 1647 (37%) had claudication. The unplanned readmission rates for CLI and claudication patients were 16% (n = 447) and 6.5% (n = 107), respectively. Mortality after index admission was higher for readmitted patients compared with those not readmitted (CLI, 3.4% vs 0.7% [P < .001]; claudication, 2.8% vs 0.1% [P < .01]). Approximately 50% of all unplanned readmissions were related to the index procedure. Among CLI patients, the most common indication for readmission related to the index procedure was wound or infection related (42%), whereas patients with claudication were mainly readmitted for recurrent symptoms of peripheral vascular disease (28%). In patients with CLI, predictors of unplanned readmission included diabetes (odds ratio, 1.3; 95% confidence interval, 1.01-1.6), congestive heart failure (1.6; 1.1-2.5), renal insufficiency (1.7; 1.3-2.2), preoperative dialysis (1.4; 1.02-1.9), tibial angioplasty/stenting (1.3; 1.04-1.6), in-hospital bleeding (1.9; 1.04-3.5), in-hospital unplanned return to the operating room (1.9; 1.1-3.5), and discharge other than to home (1.5; 1.1-2.0). Risk factors for those with claudication were dependent functional status (3.5; 1.4-8.7), smoking (1.6; 1.02-2.5), diabetes (1.5; 1.01-2.3), preoperative dialysis (3.6; 1.6-8.3), procedure time exceeding 120 minutes (1.8; 1.1-2.7), in-hospital bleeding (2.9; 1.2-7.4), and in-hospital unplanned return to the operating room (3.4; 1.2-9.4).

CONCLUSIONS

Unplanned readmission after endovascular treatment is relatively common, especially in patients with CLI, and is associated with substantially increased mortality. Awareness of these risk factors will help providers identify patients at high risk who may benefit from early surveillance, and prophylactic measures focused on decreasing postoperative complications may reduce the rate of readmission.

Pre-operative predictors of poor outcomes in patients undergoing surgical lower extremity revascularisation - Retrospective cohort study

BACKGROUND

Surgical lower extremity revascularisation (LER) can lead to poor outcomes that include delayed hospital discharge, in-hospital mortality, major amputations and readmissions. The aim of this study was to identify pre-operative predictors associated with these poor clinical outcomes.

MATERIALS AND METHODS

All patients (n = 635; mean age 69; male 67.4%) who underwent surgical LER over a 5 year period in a single tertiary vascular institution were identified. Patients considered to have suffered a poor outcome (Group A) included all in-hospital mortality and major amputations, delayed discharges with a length of stay (LOS) over one standard deviation above the mean or any readmission under any specialty within 12 months. Group A included 247 patients (38.9%) and the good outcome group included the remaining 388 patients (61.1%) from which a sample of 99 patients were selected as controls (Group B).

RESULTS

Mean LOS for the entire study group was 14.4 ± 17.5 days, 12 month readmission rate was 29.1% and in-hospital mortality and major amputation rate was 2.7% and 1.4%, respectively. Pre-admission residence other than own home (OR 9.0; 95% CI 1.2-70.1; P = 0.036), atherosclerotic disease burden (OR 2.2; 95% CI 1.3-3.8; P = 0.003) and tissue loss (OR 3.0; 95% CI 1.6-5.3; P < 0.001) were identified as independent, statistically significant pre-operative predictors of poor outcome. Following discharge, group B patients had a significantly higher rate of amputation free survival and graft infection free survival (P < 0.001) compared to group A.

CONCLUSION

Recognition of pre-operative predictors of poor outcome should inform case selection and identify high risk patients requiring intensive perioperative optimisation and post discharge follow up.