Higher programmatic volume in paediatric heart surgery is associated with better early outcomes

2015 ◽  
Vol 25 (8) ◽  
pp. 1572-1578 ◽  
Author(s):  
Andrzej Kansy ◽  
Tjark Ebels ◽  
Christian Schreiber ◽  
Jeffrey P. Jacobs ◽  
Zdzislaw Tobota ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Hospital Mortality ◽  
Heart Surgery ◽  
Major Complication ◽  
High Volume ◽  
Patient Specific ◽  
Hospital Death ◽  
Data Set ◽  
Multivariable Logistic Regression

AbstractObjectivePrevious analyses have suggested an association between centre volume and in-hospital mortality, post-operative complications, and mortality in those patients who suffer from a complication. We sought to determine the nature of this association using a multicentre cohort.MethodsAll the patients, aged 18 years or younger, undergoing heart surgery at centres participating in the European Congenital Heart Surgeons Database (2003–2013) were included. Programmes were grouped as follows: small <150; medium 150–250; large 251–349; very large >350. Multivariable logistic regression was used to identify the differences between groups with the adjusted in-hospital mortality, onset of any and/or major complication, and in-hospital mortality in those patients with any and/or major complication. The outcomes were adjusted for patient specific risk factors and surgical risk factors.ResultsThe data set consisted of 119,345 procedures performed in 99 centres. Overall, in-hospital mortality was 4.63%; complications occurred in 23.4% of the patients. In-hospital mortality in patients with complications was 13.82%. Multivariable logistic regression showed that the risk of in-hospital death was higher in low- and medium-volume centres (p<0.001). The rate of the occurrence of any post-operative complication in small, medium, and large programmes was lower compared with very large centres (p<0.001). Low- and medium-volume centres were associated with significantly higher mortality in patients with any complication (p<0.001).ConclusionsOur analysis showed that the risk of in-hospital mortality was lower in higher-volume centres. Although the risk of complications is higher in high-volume centres, the mortality associated with complications that occurred in these centres was lower.

Risk factors and clinical outcomes associated with blood culture contamination

2021 ◽  
pp. 1-7
Author(s):  
Justin M. Klucher ◽  
Kevin Davis ◽  
Mrinmayee Lakkad ◽  
Jacob T. Painter ◽  
Ryan K. Dare
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Blood Culture ◽  
Hospital Mortality ◽  
Clinical Outcomes ◽  
Tertiary Care ◽  
Blood Cultures ◽  
Hospital Charges ◽  
Patient Specific ◽  
Contaminated Blood

Abstract Objective: To determine patient-specific risk factors and clinical outcomes associated with contaminated blood cultures. Design: A single-center, retrospective case-control risk factor and clinical outcome analysis performed on inpatients with blood cultures collected in the emergency department, 2014–2018. Patients with contaminated blood cultures (cases) were compared to patients with negative blood cultures (controls). Setting: A 509-bed tertiary-care university hospital. Methods: Risk factors independently associated with blood-culture contamination were determined using multivariable logistic regression. The impacts of contamination on clinical outcomes were assessed using linear regression, logistic regression, and generalized linear model with γ log link. Results: Of 13,782 blood cultures, 1,504 (10.9%) true positives were excluded, leaving 1,012 (7.3%) cases and 11,266 (81.7%) controls. The following factors were independently associated with blood-culture contamination: increasing age (adjusted odds ratio [aOR], 1.01; 95% confidence interval [CI], 1.01–1.01), black race (aOR, 1.32; 95% CI, 1.15–1.51), increased body mass index (BMI; aOR, 1.01; 95% CI, 1.00–1.02), chronic obstructive pulmonary disease (aOR, 1.16; 95% CI, 1.02–1.33), paralysis (aOR 1.64; 95% CI, 1.26–2.14) and sepsis plus shock (aOR, 1.26; 95% CI, 1.07–1.49). After controlling for age, race, BMI, and sepsis, blood-culture contamination increased length of stay (LOS; β = 1.24 ± 0.24; P < .0001), length of antibiotic treatment (LOT; β = 1.01 ± 0.20; P < .001), hospital charges (β = 0.22 ± 0.03; P < .0001), acute kidney injury (AKI; aOR, 1.60; 95% CI, 1.40–1.83), echocardiogram orders (aOR, 1.51; 95% CI, 1.30–1.75) and in-hospital mortality (aOR, 1.69; 95% CI, 1.31–2.16). Conclusions: These unique risk factors identify high-risk individuals for blood-culture contamination. After controlling for confounders, contamination significantly increased LOS, LOT, hospital charges, AKI, echocardiograms, and in-hospital mortality.

scholarly journals Infective endocarditis at a tertiary care hospital in South Korea

Heart ◽  
2020 ◽  
Vol 107 (2) ◽  
pp. 135-141 ◽  
Author(s):  
Jung Ho Kim ◽  
Hi Jae Lee ◽  
Nam Su Ku ◽  
Seung Hyun Lee ◽  
Sak Lee ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Infective Endocarditis ◽  
Mortality Rate ◽  
South Korea ◽  
Hospital Mortality ◽  
Care Hospital ◽  
Multivariable Logistic Regression ◽  
Long Term Prognosis

ObjectiveThe treatment of infective endocarditis (IE) has become more complex with the current myriad healthcare-associated factors and the regional differences in causative organisms. We aimed to investigate the overall trends, microbiological features, and outcomes of IE in South Korea.MethodsA 12-year retrospective cohort study was performed. Poisson regression was used to estimate the time trends of IE incidence and mortality rate. Risk factors for in-hospital mortality were identified with multivariable logistic regression, and model comparison was performed to evaluate the predictive performance of notable risk factors. Kaplan-Meier survival analysis and Cox regression were performed to assess long-term prognosis.ResultsWe included 419 patients with IE, the incidence of which showed an increasing trend (relative risk 1.06, p=0.005), whereas mortality demonstrated a decreasing trend (incidence rate ratio 0.93, p=0.020). The in-hospital mortality rate was 14.6%. On multivariable logistic regression analysis, aortic valve endocarditis (OR 3.18, p=0.001), IE caused by Staphylococcus aureus (OR 2.32, p=0.026), neurological complications (OR 1.98, p=0.031), high Sequential Organ Failure Assessment score (OR 1.22, p=0.023) and high Charlson Comorbidity Index (OR 1.11, p=0.019) were predictors of in-hospital mortality. Surgical intervention for IE was a protective factor against in-hospital mortality (OR 0.25, p<0.001) and was associated with improved long-term prognosis compared with medical treatment only (p<0.001).ConclusionsThe incidence of IE is increasing in South Korea. Although the mortality rate has slightly decreased, it remains high. Surgery has a protective effect with respect to both in-hospital mortality and long-term prognosis in patients with IE.

Early Active Irrigation-Suction Drainage among Enterocutaneous Fistulas Patients with Chronic Critical Illness: A Retrospective Cohort Study

2020 ◽  
Vol 86 (4) ◽  
pp. 346-353
Author(s):  
Zhizhao Jiang ◽  
Jianan Ren ◽  
Huajian Ren ◽  
Zhiwu Hong ◽  
Gefei Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Critical Illness ◽  
Mortality Rate ◽  
Hospital Mortality ◽  
Patient Specific ◽  
Hospital Death ◽  
Suction Drainage ◽  
Rehabilitation Therapy ◽  
Number Of Patients ◽  
Chronic Critical Illness

Enterocutaneous fistulas (ECFs) requiring admission to ICU is a serious surgical complication. A growing number of patients survive ECFs but remain chronically critically ill. The aim of our study was to investigate the risk factors of hospital death in patients with chronic critical illness attributed to ECFs. A retrospective single-center study was conducted in 163 ECF patients between 2013 and 2017. Patient-specific baseline characteristics, outcomes, and process of care variables were collected. Risk factors for hospital mortality were determined using univariate and multi-variate analyses. Patients were divided into the following two groups according to the hospital discharge outcome: group survivors (n = 106) and group nonsurvivors (n = 57). Patients who received active irrigation-suction drainage (AISD) within 24 hours after the diagnosis of ECFs had a significantly lower hospital mortality rate than those who received AISD after more than 24 hours (17.9% vs 46.9%, P < 0.001). Multivariate logistic regression analysis demonstrated that delayed AISD (adjusted odds ratio [AOR], 10.24; 95% confidence interval [CI], 3.03234.59; P < 0.001) and no rehabilitation therapy (AOR, 4.77; 95% CI, 1.43215.98; P = 0.011) were independently associated with a greater risk of hospital mortality. The hospital mortality rate in patients with more than or equal to four risk factors was 92.6 per cent (n = 57), compared with a mortality rate of 9.4 per cent (n = 106) in patients who did not have these risk factors ( P < 0.001). The risk of hospital death is exceptionally high among patients with chronic critical illness attributed to ECFs. Efforts aimed at early AISD and rehabilitation therapy are likely to be associated with improved clinical outcomes.

scholarly journals 399. Risk Factors for Mortality in COVID-19 Patients in a Community Teaching Hospital

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S268-S268
Author(s):  
Justin A Andrade ◽  
Karina Muzykovsky ◽  
James Truong
Keyword(s):  
Risk Factors ◽  
Renal Failure ◽  
Logistic Regression ◽  
Hospital Mortality ◽  
Teaching Hospital ◽  
Case Series ◽  
Advanced Age ◽  
Retrospective Case ◽  
Multivariable Logistic Regression ◽  
Community Teaching

Abstract Background As of May 2020, there were over 190,000 confirmed COVID-19 cases in New York City (NYC) with approximately 13,000 deaths. Previously published literature identified risk factors (advanced age, higher severity of illness and elevated d-dimer) for mortality in a cohort of patients from Wuhan, China and mechanical ventilation in a case series from NYC. Another case series from NYC evaluated clinical outcomes only. There are limited published studies assessing clinical characteristics, outcomes and risk factors for mortality in COVID-19 patients in NYC. The objective of this study was to assess the risk factors for mortality in patients with confirmed COVID-19 infections. Methods This study was a single center retrospective case-control at The Brooklyn Hospital Center, a 464-bed community teaching hospital. Adult patients with confirmed COVID-19 infection, who received at least 24 hours of COVID-19 therapy were included. Endpoints assessed were risk factors for mortality in COVID-19 patients, increase in QTc, renal failure or renal replacement therapy, ventricular fibrillation or ventricular tachycardia. Baseline characteristics between survivor and non-survivors were analyzed utilizing Mann-Whitney U test/two-tailed t-tests for continuous data and Chi-square/Fisher’s exact test for categorical data. Univariable and multivariable logistic regression analyses were conducted to identify the risk factors for in-hospital mortality. Results Two-hundred and eighty six patients were included in this analysis, of whom 97 (33.9%) were non-survivors and 189 (66.1%) patients were survivors. Diabetes and coronary artery disease were more common in non-survivors compared to survivors (p = 0.003 and p &lt; 0.001, respectively). Multivariable logistic regression showed higher in-hospital mortality in patients with advanced age (odds ratio 5.779, 95 % confidence interval 1.369–24.407), vasopressor initiation (OR 28.301, 95 % CI 3.307–242.176), and development of renal failure (OR 30.927, 95 % CI 1.871–511.201). Conclusion Risk factors associated with mortality for COVID-19 patients in a community teaching hospital include advanced age, vasopressor therapy, and development of renal failure. Disclosures All Authors: No reported disclosures

scholarly journals Invasive Mechanical Ventilation May Be an Important Factor of Mortality in Severe/Critical COVID-19 Pneumonia: A Retrospective Cohort Study

2020 ◽  
Author(s):  
Jing Wei ◽  
Lei Shi ◽  
Zhi Cheng ◽  
Xinye Jin ◽  
Wei Zhao ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mechanical Ventilation ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Invasive Mechanical Ventilation ◽  
Trial Registration ◽  
Hospital Death ◽  
Multivariable Logistic Regression Analysis ◽  
Multivariable Logistic Regression

Abstract Background: Many of severe COVID-19 patients are admitted to the hospital or even to the Intensive Care Unit(ICU). The present study was aimed to investigated the risk factors in death from COVID-19.Methods: In this retrospective study, all inpatients confirmed severe or critical COVID-19 from two tertiary hospital in Huangshi were included, who had been discharged or died by March19,2020. Demographic,clinical,treatment,laboratory data and information were extracted from electronic medical records and compared between survivors group and non-survivors group. The univariable and multivariable logistic regression analysis was used to analyze the risk factors associated with in-hospital death.Results: 81 patients were included in this study, of whom 55 were discharged and 26 died in hospital. In all patients, 36(44.4%) patients had comorbidity, including hypertension(27[33.3%]), diabetes(11[13.6%]) and coronary heart disease (CHD)(11[13.6%]), and 16(19.8%) patients accompanied with more than 2 kinds of underlying diseases. The proportion of CHD in non-survivors group was significantly higher than that in survivors group(26.9% vs 7.3%, P=0.032), but there were no differences in hypertension, diabetes and COPD between the non-survivors group and the survivors group. Multivariable logistic regression analysis showed increasing odds of in-hospital death associated with aspartate aminotransferase(AST) and invasive mechanical ventilation (IMV) (P<0.001)(P=0.017）.Conclusions: Invasive Mechanical Ventilation may contribute to mortality of severe/critical COVID-19 pneumonia, and with higher AST at admission was one of the indicators of poor prognosis.Trial registration: Chinese Clinical Trial Registration; ChiCTR2000031494; Registered 02 April 2020; http://www.medresman.org

scholarly journals Exploring relationships between in-hospital mortality and hospital case volume using random forest: results of a cohort study based on a nationwide sample of German hospitals, 2016–2018

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Martin Roessler ◽  
Felix Walther ◽  
Maria Eberlein-Gonska ◽  
Peter C. Scriba ◽  
Ralf Kuhlen ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Random Forest ◽  
Hospital Mortality ◽  
Patient Specific ◽  
Hospital Death ◽  
Case Volume ◽  
Hospital Case ◽  
Patient Groups ◽  
The Relationship ◽  
Strong Relationships

Abstract Background Relationships between in-hospital mortality and case volume were investigated for various patient groups in many empirical studies with mixed results. Typically, those studies relied on (semi-)parametric statistical models like logistic regression. Those models impose strong assumptions on the functional form of the relationship between outcome and case volume. The aim of this study was to determine associations between in-hospital mortality and hospital case volume using random forest as a flexible, nonparametric machine learning method. Methods We analyzed a sample of 753,895 hospital cases with stroke, myocardial infarction, ventilation > 24 h, COPD, pneumonia, and colorectal cancer undergoing colorectal resection treated in 233 German hospitals over the period 2016–2018. We derived partial dependence functions from random forest estimates capturing the relationship between the patient-specific probability of in-hospital death and hospital case volume for each of the six considered patient groups. Results Across all patient groups, the smallest hospital volumes were consistently related to the highest predicted probabilities of in-hospital death. We found strong relationships between in-hospital mortality and hospital case volume for hospitals treating a (very) small number of cases. Slightly higher case volumes were associated with substantially lower mortality. The estimated relationships between in-hospital mortality and case volume were nonlinear and nonmonotonic. Conclusion Our analysis revealed strong relationships between in-hospital mortality and hospital case volume in hospitals treating a small number of cases. The nonlinearity and nonmonotonicity of the estimated relationships indicate that studies applying conventional statistical approaches like logistic regression should consider these relationships adequately.

scholarly journals Efficacy and safety of 5 mg olanzapine for nausea and vomiting management in cancer patients receiving carboplatin: integrated study of three prospective multicenter phase II trials

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Senri Yamamoto ◽  
Hirotoshi Iihara ◽  
Ryuji Uozumi ◽  
Hitoshi Kawazoe ◽  
Kazuki Tanaka ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Cancer Patients ◽  
Phase Ii ◽  
Low Dose ◽  
Nausea And Vomiting ◽  
Efficacy And Safety ◽  
Multivariable Logistic Regression ◽  
Related Risk ◽  
Total Control

Abstract Background The efficacy of olanzapine as an antiemetic agent in cancer chemotherapy has been demonstrated. However, few high-quality reports are available on the evaluation of olanzapine’s efficacy and safety at a low dose of 5 mg among patients treated with carboplatin regimens. Therefore, in this study, we investigated the efficacy and safety of 5 mg olanzapine for managing nausea and vomiting in cancer patients receiving carboplatin regimens and identified patient-related risk factors for carboplatin regimen-induced nausea and vomiting treated with 5 mg olanzapine. Methods Data were pooled for 140 patients from three multicenter, prospective, single-arm, open-label phase II studies evaluating the efficacy and safety of olanzapine for managing nausea and vomiting induced by carboplatin-based chemotherapy. Multivariable logistic regression analyses were performed to determine the patient-related risk factors. Results Regarding the endpoints of carboplatin regimen-induced nausea and vomiting control, the complete response, complete control, and total control rates during the overall study period were 87.9, 86.4, and 72.9%, respectively. No treatment-related adverse events of grade 3 or higher were observed. The multivariable logistic regression models revealed that only younger age was significantly associated with an increased risk of non-total control. Surprisingly, there was no significant difference in CINV control between the patients treated with or without neurokinin-1 receptor antagonist. Conclusions The findings suggest that antiemetic regimens containing low-dose (5 mg) olanzapine could be effective and safe for patients receiving carboplatin-based chemotherapy.

Hyperoxia is associated with adverse outcomes in the cardiac intensive care unit: insights from the Medical Information Mart for Intensive Care (MIMI-III) database

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A.Y Lui ◽  
L Garber ◽  
M Vincent ◽  
L Celi ◽  
J Masip ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Adverse Outcomes ◽  
Rank Test ◽  
Positive Pressure ◽  
Cardiac Intensive Care Unit ◽  
Multivariable Logistic Regression ◽  
Cardiac Intensive Care

Abstract Background Hyperoxia produces reactive oxygen species, apoptosis, and vasoconstriction, and is associated with adverse outcomes in patients with heart failure and cardiac arrest. Our aim was to evaluate the association between hyperoxia and mortality in patients (pts) receiving positive pressure ventilation (PPV) in the cardiac intensive care unit (CICU). Methods Patients admitted to our medical center CICU who received any PPV (invasive or non-invasive) from 2001 through 2012 were included. Hyperoxia was defined as time-weighted mean of PaO2 &gt;120mmHg and non-hyperoxia as PaO2 ≤120mmHg during CICU admission. Primary outcome was in-hospital mortality. Multivariable logistic regression was used to assess the association between hyperoxia and in-hospital mortality adjusted for age, female sex, Oxford Acute Severity of Illness Score, creatinine, lactate, pH, PaO2/FiO2 ratio, PCO2, PEEP, and estimated time spent on PEEP. Results Among 1493 patients, hyperoxia (median PaO2 147mmHg) during the CICU admission was observed in 702 (47.0%) pts. In-hospital mortality was 29.7% in the non-hyperoxia group and 33.9% in the hyperoxia group ((log rank test, p=0.0282, see figure). Using multivariable logistic regression, hyperoxia was independently associated with in-hospital mortality (OR 1.507, 95% CI 1.311–2.001, p=0.00508). Post-hoc analysis with PaO2 as a continuous variable was consistent with the primary analysis (OR 1.053 per 10mmHg increase in PaO2, 95% CI 1.024–1.082, p=0.0002). Conclusions In a large CICU cohort, hyperoxia was associated with increased mortality. Trials of titration of supplemental oxygen across the full spectrum of critically ill cardiac patients are warranted. Funding Acknowledgement Type of funding source: None

Abstract P192: Metabolomic Profiles Associated with Coronary Heart Disease in Women

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Nina P Paynter ◽  
Raji Balasubramanian ◽  
Shuba Gopal ◽  
Franco Giulianini ◽  
Leslie Tinker ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Logistic Regression ◽  
Heart Disease ◽  
Tier 2 ◽  
Validation Data ◽  
Data Set ◽  
Chd Risk ◽  
Tier 1 ◽  
Chd Risk Factors

Background: Prior studies of metabolomic profiles and coronary heart disease (CHD) have been limited by relatively small case numbers and scant data in women. Methods: The discovery set examined 371 metabolites in 400 confirmed, incident CHD cases and 400 controls (frequency matched on age, race/ethnicity, hysterectomy status and time of enrollment) in the Women’s Health Initiative Observational Study (WHI-OS). All selected metabolites were validated in a separate set of 394 cases and 397 matched controls drawn from the placebo arms of the WHI Hormone Therapy trials and the WHI-OS. Discovery used 4 methods: false-discovery rate (FDR) adjusted logistic regression for individual metabolites, permutation corrected least absolute shrinkage and selection operator (LASSO) algorithms, sparse partial least squares discriminant analysis (PLS-DA) algorithms, and random forest algorithms. Each method was performed with matching factors only and with matching plus both medication use (aspirin, statins, anti-diabetics and anti-hypertensives) and traditional CHD risk factors (smoking, systolic blood pressure, diabetes, total and HDL cholesterol). Replication in the validation set was defined as a logistic regression coefficient of p<0.05 for the metabolites selected by 3 or 4 methods (tier 1), or a FDR adjusted p<0.05 for metabolites selected by only 1 or 2 methods (tier 2). Results: Sixty-seven metabolites were selected in the discovery data set (30 tier 1 and 37 tier 2). Twenty-six successfully replicated in the validation data set (21 tier 1 and 5 tier 2), with 25 significant with adjusting for matching factors only and 11 significant after additionally adjusting for medications and CHD risk factors. Validated metabolites included amino acids, sugars, nucleosides, eicosanoids, plasmologens, polyunsaturated phospholipids and highly saturated triglycerides. These include novel metabolites as well as metabolites such as glutamate/glutamine, which have been shown in other populations. Conclusions: Multiple metabolites in important physiological pathways with robust associations for risk of CHD in women were identified and replicated. These results may offer insights into biological mechanisms of CHD as well as identify potential markers of risk.

Substance Use Relapse Among Veterans at Termination of Treatment for Substance Use Disorders

2021 ◽  
Author(s):  
Christian A Betancourt ◽  
Panagiota Kitsantas ◽  
Deborah G Goldberg ◽  
Beth A Hawks
Keyword(s):  
Risk Factors ◽  
Substance Use ◽  
Logistic Regression ◽  
Substance Use Disorders ◽  
Classification Tree ◽  
Treatment Completion ◽  
Classification Tree Analysis ◽  
Data Set ◽  
Tree Analysis ◽  
Substance Addiction

ABSTRACT Introduction Military veterans continue to struggle with addiction even after receiving treatment for substance use disorders (SUDs). Identifying factors that may influence SUD relapse upon receiving treatment in veteran populations is crucial for intervention and prevention efforts. The purpose of this study was to examine risk factors that contribute to SUD relapse upon treatment completion in a sample of U.S. veterans using logistic regression and classification tree analysis. Materials and Methods Data from the 2017 Treatment Episode Data Set—Discharge (TEDS-D) included 40,909 veteran episode observations. Descriptive statistics and multivariable logistic regression analysis were conducted to determine factors associated with SUD relapse after treatment discharge. Classification trees were constructed to identify high-risk subgroups for substance use after discharge from treatment for SUDs. Results Approximately 94% of the veterans relapsed upon discharge from outpatient or residential SUD treatment. Veterans aged 18-34 years old were significantly less likely to relapse than the 35-64 age group (odds ratio [OR] 0.73, 95% confidence interval [CI]: 0.66, 0.82), while males were more likely than females to relapse (OR 1.55, 95% CI: 1.34, 1.79). Unemployed veterans (OR 1.92, 95% CI: 1.67, 2.22) or veterans not in the labor force (OR 1.29, 95% CI: 1.13, 1.47) were more likely to relapse than employed veterans. Homeless vs. independently housed veterans had 3.26 (95% CI: 2.55, 4.17) higher odds of relapse after treatment. Veterans with one arrest vs. none were more likely to relapse (OR 1.52, 95% CI: 1.19, 1.95). Treatment completion was critical to maintain sobriety, as every other type of discharge led to more than double the odds of relapse. Veterans who received care at 24-hour detox facilities were 1.49 (95% CI: 1.23, 1.80) times more likely to relapse than those at rehabilitative/residential treatment facilities. Classification tree analysis indicated that homelessness upon discharge was the most important predictor in SUD relapse among veterans. Conclusion Aside from numerous challenges that veterans face after leaving military service, SUD relapse is intensified by risk factors such as homelessness, unemployment, and insufficient SUD treatment. As treatment and preventive care for SUD relapse is an active field of study, further research on SUD relapse among homeless veterans is necessary to better understand the epidemiology of substance addiction among this vulnerable population. The findings of this study can inform healthcare policy and practices targeting veteran-tailored treatment programs to improve SUD treatment completion and lower substance use after treatment.

Sign in / Sign up

Export Citation Format

Share Document