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PURPOSE - Several observational studies suggest that metformin reduces incidence cancer risk; however, many of these studies suffer from time-related biases and several cancer outcomes have not been investigated due to small sample sizes.
METHODS - We constructed a propensity score-matched retrospective cohort of 84,434 veterans newly prescribed metformin or a sulfonylurea as monotherapy. We used Cox proportional hazard regression to assess the association between metformin use compared to sulfonylurea use and incidence cancer risk for 10 solid tumors. We adjusted for clinical covariates including hemoglobin A1C, antihypertensive and lipid-lowering medications, and body mass index. Incidence cancers were defined by ICD-9-CM codes.
RESULTS - Among 42,217 new metformin users and 42,217 matched-new sulfonylurea users, we identified 2,575 incidence cancers. Metformin was inversely associated with liver cancer (adjusted hazard ratio [aHR] = 0.44, 95% CI 0.31, 0.64) compared to sulfonylurea. We found no association between metformin use and risk of incidence bladder, breast, colorectal, esophageal, gastric, lung, pancreatic, prostate, or renal cancer when compared to sulfonylurea use.
CONCLUSIONS - In this large cohort study that accounted for time-related biases, we observed no association between the use of metformin and most cancers; however, we found a strong inverse association between metformin and liver cancer. Randomized trials of metformin for prevention of liver cancer would be useful to verify these observations.
OBJECTIVES - We aimed to validate an algorithm using both primary discharge diagnosis (International Classification of Diseases Ninth Revision (ICD-9)) and diagnosis-related group (DRG) codes to identify hospitalisations due to decompensated heart failure (HF) in a population of patients with diabetes within the Veterans Health Administration (VHA) system.
DESIGN - Validation study.
SETTING - Veterans Health Administration-Tennessee Valley Healthcare System PARTICIPANTS: We identified and reviewed a stratified, random sample of hospitalisations between 2001 and 2012 within a single VHA healthcare system of adults who received regular VHA care and were initiated on an antidiabetic medication between 2001 and 2008. We sampled 500 hospitalisations; 400 hospitalisations that fulfilled algorithm criteria, 100 that did not. Of these, 497 had adequate information for inclusion. The mean patient age was 66.1 years (SD 11.4). Majority of patients were male (98.8%); 75% were white and 20% were black.
PRIMARY AND SECONDARY OUTCOME MEASURES - To determine if a hospitalisation was due to HF, we performed chart abstraction using Framingham criteria as the referent standard. We calculated the positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity for the overall algorithm and each component (primary diagnosis code (ICD-9), DRG code or both).
RESULTS - The algorithm had a PPV of 89.7% (95% CI 86.8 to 92.7), NPV of 93.9% (89.1 to 98.6), sensitivity of 45.1% (25.1 to 65.1) and specificity of 99.4% (99.2 to 99.6). The PPV was highest for hospitalisations that fulfilled both the ICD-9 and DRG algorithm criteria (92.1% (89.1 to 95.1)) and lowest for hospitalisations that fulfilled only DRG algorithm criteria (62.5% (28.4 to 96.6)).
CONCLUSIONS - Our algorithm, which included primary discharge diagnosis and DRG codes, demonstrated excellent PPV for identification of hospitalisations due to decompensated HF among patients with diabetes in the VHA system.
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
BACKGROUND - Acute kidney injury (AKI) is common and associated with poor outcomes. Heart failure is a leading cause of cardiovascular disease among patients with chronic kidney disease. The relationship between AKI and heart failure remains unknown and may identify a novel mechanistic link between kidney and cardiovascular disease.
STUDY DESIGN - Observational study.
SETTING & PARTICIPANTS - We studied a national cohort of 300,868 hospitalized US veterans (2004-2011) without a history of heart failure.
PREDICTOR - AKI was the predictor and was defined as a 0.3-mg/dL or 50% increase in serum creatinine concentration from baseline to the peak hospital value. Patients with and without AKI were matched (1:1) on 28 in- and outpatient covariates using optimal Mahalanobis distance matching.
OUTCOMES - Incident heart failure was defined as 1 or more hospitalization or 2 or more outpatient visits with a diagnosis of heart failure within 2 years through 2013.
RESULTS - There were 150,434 matched pairs in the study. Patients with and without AKI during the index hospitalization were well matched, with a median preadmission estimated glomerular filtration rate of 69mL/min/1.73m. The overall incidence rate of heart failure was 27.8 (95% CI, 19.3-39.9) per 1,000 person-years. The incidence rate was higher in those with compared with those without AKI: 30.8 (95% CI, 21.8-43.5) and 24.9 (95% CI, 16.9-36.5) per 1,000 person-years, respectively. In multivariable models, AKI was associated with 23% increased risk for incident heart failure (HR, 1.23; 95% CI, 1.19-1.27).
LIMITATIONS - Study population was primarily men, reflecting patients seen at Veterans Affairs hospitals.
CONCLUSIONS - AKI is an independent risk factor for incident heart failure. Future studies to identify underlying mechanisms and modifiable risk factors are needed.
Copyright © 2017 National Kidney Foundation, Inc. All rights reserved.
RATIONALE - The epidemiology and prognostic impact of increased pulmonary pressure among HIV-infected individuals in the antiretroviral therapy era is not well described.
OBJECTIVES - To examine the prevalence, clinical features, and outcomes of increased echocardiographic pulmonary pressure in HIV-infected and -uninfected individuals.
METHODS - This study evaluated 8,296 veterans referred for echocardiography with reported pulmonary artery systolic pressure (PASP) estimates from the Veterans Aging Cohort study, an observational cohort of HIV-infected and -uninfected veterans matched by age, sex, race/ethnicity, and clinical site. The primary outcome was adjusted mortality by HIV status.
MEASUREMENTS AND MAIN RESULTS - PASP was reported in 2,831 HIV-infected and 5,465 HIV-uninfected veterans (follow-up [mean ± SD], 3.8 ± 2.6 yr). As compared with uninfected veterans, HIV-infected veterans with HIV viral load greater than 500 copies/ml (odds ratio, 1.27; 95% confidence interval [CI], 1.05-1.54) and those with CD4 cell count less than 200 cells/μl (odds ratio, 1.28; 95% CI, 1.02-1.60) had a higher prevalence of PASP greater than or equal to 40 mm Hg. As compared with uninfected veterans with a PASP less than 40 mm Hg, HIV-infected veterans with a PASP greater than or equal to 40 mm Hg had an increased risk of death (adjusted hazard ratio, 1.78; 95% CI, 1.57-2.01). This risk persisted even among participants without prevalent comorbidities (adjusted hazard ratio, 3.61; 95% CI, 2.17-6.01). The adjusted risk of mortality in HIV-infected veterans was higher at all PASP values than in uninfected veterans, including at values currently considered to be normal.
CONCLUSIONS - HIV-infected people with high HIV viral loads or low CD4 cell counts have a higher prevalence of increased PASP than uninfected people. Mortality risk in HIV-infected veterans increases at lower values of PASP than previously recognized and is present even among those without prevalent comorbidities. These findings may inform clinical decision-making regarding screening and surveillance of pulmonary hypertension in HIV-infected individuals.
Acute kidney injury (AKI) is associated with subsequent chronic kidney disease (CKD), but the mechanism is unclear. To clarify this, we examined the association of AKI and new-onset or worsening proteinuria during the 12 months following hospitalization in a national retrospective cohort of United States Veterans hospitalized between 2004-2012. Patients with and without AKI were matched using baseline demographics, comorbidities, proteinuria, estimated glomerular filtration rate, blood pressure, angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker (ACEI/ARB) use, and inpatient exposures linked to AKI. The distribution of proteinuria over one year post-discharge in the matched cohort was compared using inverse probability sampling weights. Subgroup analyses were based on diabetes, pre-admission ACEI/ARB use, and AKI severity. Among the 90,614 matched AKI and non-AKI pairs, the median estimated glomerular filtration rate was 62 mL/min/1.73m. The prevalence of diabetes and hypertension were 48% and 78%, respectively. The odds of having one plus or greater dipstick proteinuria was significantly higher during each month of follow-up in patients with AKI than in patients without AKI (odds ratio range 1.20-1.39). Odds were higher in patients with Stage II or III AKI (odds ratios 1.32-1.81) than in Stage I AKI (odds ratios 1.18-1.32), using non-AKI as the reference group. Results were consistent regardless of diabetes status or baseline ACEI/ARB use. Thus, AKI is a risk factor for incident or worsening proteinuria, suggesting a possible mechanism linking AKI and future CKD. The type of proteinuria, physiology, and clinical significance warrant further study as a potentially modifiable risk factor in the pathway from AKI to CKD.
Published by Elsevier Inc.
BACKGROUND - Medications that impact insulin sensitivity or cause weight gain may increase heart failure risk. Our aim was to compare heart failure and cardiovascular death outcomes among patients initiating sulfonylureas for diabetes mellitus treatment versus metformin.
METHODS AND RESULTS - National Veterans Health Administration databases were linked to Medicare, Medicaid, and National Death Index data. Veterans aged ≥18 years who initiated metformin or sulfonylureas between 2001 and 2011 and whose creatinine was <1.4 (females) or 1.5 mg/dL (males) were included. Each metformin patient was propensity score-matched to a sulfonylurea initiator. The outcome was hospitalization for acute decompensated heart failure as the primary reason for admission or a cardiovascular death. There were 126 867 and 79 192 new users of metformin and sulfonylurea, respectively. Propensity score matching yielded 65 986 per group. Median age was 66 years, and 97% of patients were male; hemoglobin A 6.9% (6.3, 7.7); body mass index 30.7 kg/m (27.4, 34.6); and 6% had heart failure history. There were 1236 events (1184 heart failure hospitalizations and 52 cardiovascular deaths) among sulfonylurea initiators and 1078 events (1043 heart failure hospitalizations and 35 cardiovascular deaths) among metformin initiators. There were 12.4 versus 8.9 events per 1000 person-years of use (adjusted hazard ratio 1.32, 95%CI 1.21, 1.43). The rate difference was 4 heart failure hospitalizations or cardiovascular deaths per 1000 users of sulfonylureas versus metformin annually.
CONCLUSIONS - Predominantly male patients initiating treatment for diabetes mellitus with sulfonylurea had a higher risk of heart failure and cardiovascular death compared to similar patients initiating metformin.
© 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.
Objective - Predictive analytics create opportunities to incorporate personalized risk estimates into clinical decision support. Models must be well calibrated to support decision-making, yet calibration deteriorates over time. This study explored the influence of modeling methods on performance drift and connected observed drift with data shifts in the patient population.
Materials and Methods - Using 2003 admissions to Department of Veterans Affairs hospitals nationwide, we developed 7 parallel models for hospital-acquired acute kidney injury using common regression and machine learning methods, validating each over 9 subsequent years.
Results - Discrimination was maintained for all models. Calibration declined as all models increasingly overpredicted risk. However, the random forest and neural network models maintained calibration across ranges of probability, capturing more admissions than did the regression models. The magnitude of overprediction increased over time for the regression models while remaining stable and small for the machine learning models. Changes in the rate of acute kidney injury were strongly linked to increasing overprediction, while changes in predictor-outcome associations corresponded with diverging patterns of calibration drift across methods.
Conclusions - Efficient and effective updating protocols will be essential for maintaining accuracy of, user confidence in, and safety of personalized risk predictions to support decision-making. Model updating protocols should be tailored to account for variations in calibration drift across methods and respond to periods of rapid performance drift rather than be limited to regularly scheduled annual or biannual intervals.
© The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: firstname.lastname@example.org
BACKGROUND - Type 2 diabetes patients often initiate treatment with a sulfonylurea and subsequently intensify their therapy with insulin. However, information on optimal treatment regimens for these patients is limited.
OBJECTIVE - To compare risk of cardiovascular disease (CVD) and hypoglycemia between sulfonylurea initiators who switch to or add insulin.
DESIGN - This was a retrospective cohort assembled using national Veterans Health Administration (VHA), Medicare, and National Death Index databases.
PARTICIPANTS - Veterans who initiated diabetes treatment with a sulfonylurea between 2001 and 2008 and intensified their regimen with insulin were followed through 2011.
MAIN MEASURES - The association between insulin versus sulfonylurea + insulin and time to CVD or hypoglycemia were evaluated using Cox proportional hazard models in a 1:1 propensity score-matched cohort. CVD included hospitalization for acute myocardial infarction or stroke, or cardiovascular mortality. Hypoglycemia included hospitalizations or emergency visits for hypoglycemia, or outpatient blood glucose measurements <60 mg/dL. Subgroups included age < 65 and ≥ 65 years and estimated glomerular filtration rate ≥ 60 and < 60 ml/min.
KEY FINDINGS - There were 1646 and 3728 sulfonylurea monotherapy initiators who switched to insulin monotherapy or added insulin, respectively. The 1596 propensity score-matched patients in each group had similar baseline characteristics at insulin initiation. The rate of CVD per 1000 person-years among insulin versus sulfonylurea + insulin users were 49.3 and 56.0, respectively [hazard ratio (HR) 0.85, 95 % confidence interval (CI) 0.64, 1.12]. Rates of first and recurrent hypoglycemia events per 1000 person-years were 74.0 and 100.0 among insulin users compared to 78.9 and 116.8 among sulfonylurea plus insulin users, yielding HR (95 % CI) of 0.94 (0.76, 1.16) and 0.87 (0.69, 1.10), respectively. Subgroup analysis results were consistent with the main findings.
CONCLUSIONS - Compared to sulfonylurea users who added insulin, those who switched to insulin alone had numerically lower CVD and hypoglycemia events, but these differences in risk were not statistically significant.
RATIONALE - The incidence and risk factors of post-traumatic stress disorder (PTSD) related to the intensive care unit (ICU) experience have not been reported in a mixed veteran and civilian cohort.
OBJECTIVES - To describe the incidence and risk factors for ICU-related PTSD in veterans and civilians.
METHODS - This is a prospective, observational, multicenter cohort enrolling adult survivors of critical illness after respiratory failure and/or shock from three Veterans Affairs and one civilian hospital. After classifying those with/without preexisting PTSD (i.e., PTSD before hospitalization), we then assessed all subjects for ICU-related PTSD at 3 and 12 months post hospitalization.
MEASUREMENTS AND MAIN RESULTS - Of 255 survivors, 181 and 160 subjects were assessed for ICU-related PTSD at 3- and 12-month follow-up, respectively. A high probability of ICU-related PTSD was found in up to 10% of patients at either follow-up time point, whether assessed by PTSD Checklist Event-Specific Version (score ≥ 50) or item mapping using the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). In the multivariable regression, preexisting PTSD was independently associated with ICU-related PTSD at both 3 and 12 months (P < 0.001), as was preexisting depression (P < 0.03), but veteran status was not a consistent independent risk factor for ICU-related PTSD (3-month P = 0.01, 12-month P = 0.48).
CONCLUSIONS - This study found around 1 in 10 ICU survivors experienced ICU-related PTSD (i.e., PTSD anchored to their critical illness) in the year after hospitalization. Preexisting PTSD and depression were strongly associated with ICU-related PTSD.