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Risk factors for hospitalization and medical intensive care unit (MICU) admission among HIV-infected Veterans.

ABSTRACT: OBJECTIVE:With improved survival of HIV-infected persons on antiretroviral therapy and growing prevalence of non-AIDS diseases, we asked whether the VACS Index, a composite measure of HIV-associated and general organ dysfunction predictive of all-cause mortality, predicts hospitalization and medical intensive care unit (MICU) admission. We also asked whether AIDS and non-AIDS conditions increased risk after accounting for VACS Index score. METHODS:We analyzed data from the Veterans Aging Cohort Study (VACS), a prospective study of HIV-infected Veterans receiving care between 2002 and 2008. Data were obtained from the electronic medical record, VA administrative databases, and patient questionnaires and were used to identify comorbidities and calculate baseline VACS Index scores. The primary outcome was first hospitalization within 2 years of VACS enrollment. We used multivariable Cox regression to determine risk factors associated with hospitalization and logistic regression to determine risk factors for MICU admission, given hospitalization. RESULTS:Of 3410 patients, 1141 were hospitalized within 2 years; 203 (17.8%)/1141 patients included an MICU admission. Median VACS Index scores were 25 (no hospitalization), 34 (hospitalization only), and 51 (MICU). In adjusted analyses, a 5-point increment in VACS Index score was associated with 10% higher risk of hospitalization and MICU admission. In addition to VACS Index score, Hispanic ethnicity, current smoking, hazardous alcohol use, chronic obstructive pulmonary disease, hypertension, diabetes, and prior AIDS-defining event predicted hospitalization. Among those hospitalized, VACS Index score, cardiac disease, and prior cancer predicted MICU admission. CONCLUSIONS:The VACS Index predicted hospitalization and MICU admission as did current smoking, hazardous alcohol use, and AIDS and certain non-AIDS diagnoses.

SUBMITTER: Akgun KM

PROVIDER: S-EPMC4182723 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Risk factors for hospitalization and medical intensive care unit (MICU) admission among HIV-infected Veterans.

Akgün Kathleen M KM Gordon Kirsha K Pisani Margaret M Fried Terri T McGinnis Kathleen A KA Tate Janet P JP Butt Adeel A AA Gibert Cynthia L CL Huang Laurence L Rodriguez-Barradas Maria C MC Rimland David D Justice Amy C AC Crothers Kristina K

Journal of acquired immune deficiency syndromes (1999) 20130101 1

<h4>Objective</h4>With improved survival of HIV-infected persons on antiretroviral therapy and growing prevalence of non-AIDS diseases, we asked whether the VACS Index, a composite measure of HIV-associated and general organ dysfunction predictive of all-cause mortality, predicts hospitalization and medical intensive care unit (MICU) admission. We also asked whether AIDS and non-AIDS conditions increased risk after accounting for VACS Index score.<h4>Methods</h4>We analyzed data from the Veteran ...[more]

PMID: 23111572

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Project description:BackgroundOpioid overdose (OD) and related deaths have significantly increased in the United States over the last 2 decades. Existing studies have mostly focused on demographic and clinical risk factors in noncritical care settings. Social and behavioral determinants of health (SBDH) are infrequently coded in the electronic health record (EHR) and usually buried in unstructured EHR notes, reflecting possible gaps in clinical care and observational research. Therefore, SBDH often receive less attention despite being important risk factors for OD. Natural language processing (NLP) can alleviate this problem.ObjectiveThe objectives of this study were two-fold: First, we examined the usefulness of NLP for SBDH extraction from unstructured EHR text, and second, for intensive care unit (ICU) admissions, we investigated risk factors including SBDH for nonfatal OD.MethodsWe performed a cross-sectional analysis of admission data from the EHR of patients in the ICU of Beth Israel Deaconess Medical Center between 2001 and 2012. We used patient admission data and International Classification of Diseases, Ninth Revision (ICD-9) diagnoses to extract demographics, nonfatal OD, SBDH, and other clinical variables. In addition to obtaining SBDH information from the ICD codes, an NLP model was developed to extract 6 SBDH variables from EHR notes, namely, housing insecurity, unemployment, social isolation, alcohol use, smoking, and illicit drug use. We adopted a sequential forward selection process to select relevant clinical variables. Multivariable logistic regression analysis was used to evaluate the associations with nonfatal OD, and relative risks were quantified as covariate-adjusted odds ratios (aOR).ResultsThe strongest association with nonfatal OD was found to be drug use disorder (aOR 8.17, 95% CI 5.44-12.27), followed by bipolar disorder (aOR 2.69, 95% CI 1.68-4.29). Among others, major depressive disorder (aOR 2.57, 95% CI 1.12-5.88), being on a Medicaid health insurance program (aOR 2.26, 95% CI 1.43-3.58), history of illicit drug use (aOR 2.09, 95% CI 1.15-3.79), and current use of illicit drugs (aOR 2.06, 95% CI 1.20-3.55) were strongly associated with increased risk of nonfatal OD. Conversely, Blacks (aOR 0.51, 95% CI 0.28-0.94), older age groups (40-64 years: aOR 0.65, 95% CI 0.44-0.96; >64 years: aOR 0.16, 95% CI 0.08-0.34) and those with tobacco use disorder (aOR 0.53, 95% CI 0.32-0.89) or alcohol use disorder (aOR 0.64, 95% CI 0.42-1.00) had decreased risk of nonfatal OD. Moreover, 99.82% of all SBDH information was identified by the NLP model, in contrast to only 0.18% identified by the ICD codes.ConclusionsThis is the first study to analyze the risk factors for nonfatal OD in an ICU setting using NLP-extracted SBDH from EHR notes. We found several risk factors associated with nonfatal OD including SBDH. SBDH are richly described in EHR notes, supporting the importance of integrating NLP-derived SBDH into OD risk assessment. More studies in ICU settings can help health care systems better understand and respond to the opioid epidemic.

Project description:ObjectiveTo assess the impact of intensive care unit bed availability, distractors and choice framing on intensive care unit admission decisions.MethodsThis study was a randomized factorial trial using patient-based vignettes. The vignettes were deemed archetypical for intensive care unit admission or refusal, as judged by a group of experts. Intensive care unit physicians were randomized to 1) an increased distraction (intervention) or a control group, 2) an intensive care unit bed scarcity or nonscarcity (availability) setting, and 3) a multiple-choice or omission (status quo) vignette scenario. The primary outcome was the proportion of appropriate intensive care unit allocations, defined as concordance with the allocation decision made by the group of experts.ResultsWe analyzed 125 physicians. Overall, distractors had no impact on the outcome; however, there was a differential drop-out rate, with fewer physicians in the intervention arm completing the questionnaire. Intensive care unit bed availability was associated with an inappropriate allocation of vignettes deemed inappropriate for intensive care unit admission (OR = 2.47; 95%CI 1.19 - 5.11) but not of vignettes appropriate for intensive care unit admission. There was a significant interaction with the presence of distractors (p = 0.007), with intensive care unit bed availability being associated with increased intensive care unit admission of vignettes inappropriate for intensive care unit admission in the distractor (intervention) arm (OR = 9.82; 95%CI 2.68 - 25.93) but not in the control group (OR = 1.02; 95%CI 0.38 - 2.72). Multiple choices were associated with increased inappropriate allocation in comparison to the omission group (OR = 5.18; 95%CI 1.37 - 19.61).ConclusionIntensive care unit bed availability and cognitive biases were associated with inappropriate intensive care unit allocation decisions. These findings may have implications for intensive care unit admission policies.

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Risk factors for hospitalization and medical intensive care unit (MICU) admission among HIV-infected Veterans.

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Risk factors for hospitalization and medical intensive care unit (MICU) admission among HIV-infected Veterans.

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