Sitagliptin and risk of heart failure hospitalization in patients with type 2 diabetes on dialysis: A population-based cohort study.
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ABSTRACT:
SUBMITTER: Hung YC
PROVIDER: S-EPMC4962317 | biostudies-literature | 2016 Jul
REPOSITORIES: biostudies-literature
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Sitagliptin and risk of heart failure hospitalization in patients with type 2 diabetes on dialysis: A population-based cohort study.
Hung Yi-Chih YC Lin Che-Chen CC Huang Wei-Lun WL Chang Man-Ping MP Chen Ching-Chu CC
Scientific reports 20160727
The incidence of heart failure hospitalization (HHF) after taking sitagliptin in type 2 diabetes (T2DM) patients with end stage renal disease (ESRD) on dialysis is unclear. In this population-based cohort study, we identified individuals with T2DM and ESRD on dialysis who were treated with sitagliptin between 2009 and 2011 and randomly selected a control cohort matched by age, sex, duration of T2DM, hypertension medications, use of statin and aspirin, sulfonylureas, glinides, and insulin usage, ...[more]
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Project description:BackgroundAntidiabetic therapies have shown disparate effects on hospitalization for heart failure (HHF) in clinical trials. This study developed a prediction model for HHF in type 2 diabetes mellitus (T2DM) using real world data to identify patients at high risk for HHF.HypothesisType 2 diabetics at high risk for HHF can be identified using information generated during usual clinical care.MethodsThis electronic medical record- (EMR-) based retrospective cohort study included patients with T2DM free of HF receiving healthcare through a single, large integrated healthcare system. The primary endpoint was HHF, defined as a hospital admission with HF as the primary diagnosis. Cox regression identified the strongest predictors of HHF from 80 candidate predictors derived from EMRs. High risk patients were defined according to the 90th percentile of estimated risk.ResultsAmong 54,452 T2DM patients followed on average 6.6 years, estimated HHF rates at 1, 3, and 5 years were 0.3%, 1.1%, and 2.0%. The final 9-variable model included: age, coronary artery disease, blood urea nitrogen, atrial fibrillation, hemoglobin A1c, blood albumin, systolic blood pressure, chronic kidney disease, and smoking history (c = 0.782). High risk patients identified by the model had a >5% probability of HHF within 5 years.ConclusionsThe proposed model for HHF among T2DM demonstrated strong predictive capacity and may help guide therapeutic decisions.
| S-EPMC7068070 | biostudies-literature
Project description:While home dialysis is being promoted, there are few comparative effectiveness studies of home-based modalities to guide patient decisions. To address this, we matched 1116 daily home hemodialysis (DHD) patients by propensity scores to 2784 contemporaneous USRDS patients receiving home peritoneal dialysis (PD), and compared hospitalization rates from cardiovascular, infectious, access-related or bleeding causes (prespecified composite), and modality failure risk. We performed similar analyses for 1187 DHD patients matched to 3173 USRDS patients receiving in-center conventional hemodialysis (CHD). The composite hospitalization rate was significantly lower with DHD than with PD (0.93 vs. 1.35/patient-year, hazard ratio=0.73 (95% CI=0.67-0.79)). DHD patients spent significantly fewer days in hospital than PD patients (5.2 vs. 9.2 days/patient-year), and significantly more DHD patients remained admission-free (52% DHD vs. 32% PD). In contrast, there was no significant difference in hospitalizations between DHD and CHD (DHD vs. CHD: 0.93 vs. 1.10/patient-year, hazard ratio 0.92 (0.85-1.00)). Cardiovascular hospitalizations were lower with DHD than with CHD (0.68 (0.61-0.77)), while infectious and access hospitalizations were higher (1.15 (1.04-1.29) and 1.25 (1.08-1.43), respectively). Significantly more PD than DHD patients switched back to in-center HD (44% vs. 15%; 3.4 (2.9-4.0)). In this prevalent cohort, home DHD was associated with fewer admissions and hospital days than PD, and a substantially lower risk of modality failure.
| S-EPMC4526768 | biostudies-other
Project description:BACKGROUND:To examine the effects of the DPP-4i sitagliptin on CV outcomes during and after incident MI in the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS). METHODS:TECOS randomized 14,671 participants with type 2 diabetes and atherosclerotic cardiovascular disease (ASCVD) to sitagliptin or placebo, in addition to usual care. For those who had a within-trial MI, we analyzed case fatality, and for those with a nonfatal MI, we examined a composite cardiovascular (CV) outcome (CV death or hospitalization for heart failure [hHF]) by treatment group, using Cox proportional hazards models left-censored at the time of the first within-trial MI, without and with adjustment for potential confounders, in intention-to-treat analyses. RESULTS:During TECOS, 616 participants had ≥ 1 MI (sitagliptin group 300, placebo group 316, HR 0.95, 95% CI 0.81-1.11, P = 0.49), of which 25 were fatal [11 and 14, respectively]). Of the 591 patients with a nonfatal MI, 87 (15%) died subsequently, with 66 (11%) being CV deaths, and 57 (10%) experiencing hHF. The composite outcome occurred in 58 (20.1%; 13.9 per 100 person-years) sitagliptin group participants and 50 (16.6%; 11.7 per 100 person-years) placebo group participants (HR 1.21, 95% CI 0.83-1.77, P = 0.32, adjusted HR 1.23, 95% CI 0.83-1.82, P = 0.31). On-treatment sensitivity analyses also showed no significant between-group differences in post-MI outcomes. CONCLUSIONS:In patients with type 2 diabetes and ASCVD experiencing an MI, sitagliptin did not reduce subsequent risk of CV death or hHF, contrary to expectations derived from preclinical animal models. Trial registration clinicaltrials.gov no. NCT00790205.
| S-EPMC6719352 | biostudies-literature
Project description:BackgroundObesity and type 2 diabetes are well-known risk factors for heart failure (HF). Although obesity has increased in type 1 diabetes, studies regarding HF in this population are scarce. Therefore, we investigated the impact of body fat distribution on the risk of HF hospitalization or death in adults with type 1 diabetes at different stages of diabetic nephropathy (DN).MethodsFrom 5401 adults with type 1 diabetes in the Finnish Diabetic Nephropathy Study, 4668 were included in this analysis. The outcome was HF hospitalization or death identified from the Finnish Care Register for Health Care or the Causes of Death Register until the end of 2017. DN was based on urinary albumin excretion rate. A body mass index (BMI) ≥ 30 kg/m2 defined general obesity, whilst WHtR ≥ 0.5 central obesity. Multivariable Cox regression was used to explore the associations between central obesity, general obesity and the outcome. Then, subgroup analyses were performed by DN stages. Z statistic was used for ranking the association.ResultsDuring a median follow-up of 16.4 (IQR 12.4-18.5) years, 323 incident cases occurred. From 308 hospitalizations due to HF, 35 resulted in death. Further 15 deaths occurred without previous hospitalization. The WHtR showed a stronger association with the outcome [HR 1.51, 95% CI (1.26-1.81), z = 4.40] than BMI [HR 1.05, 95% CI (1.01-1.08), z = 2.71]. HbA1c [HR 1.35, 95% CI (1.24-1.46), z = 7.19] was the most relevant modifiable risk factor for the outcome whereas WHtR was the third. Individuals with microalbuminuria but no central obesity had a similar risk of the outcome as those with normoalbuminuria. General obesity was associated with the outcome only at the macroalbuminuria stage.ConclusionsCentral obesity associates with an increased risk of heart failure hospitalization or death in adults with type 1 diabetes, and WHtR may be a clinically useful screening tool.
| S-EPMC8314504 | biostudies-literature
Project description:Background and Objective: It has been suggested to avoid cilostazol, the first-line therapy for peripheral arterial disease, in patients with congestive heart failure (HF). The objective of this study was to evaluate the risk of hospitalization for heart failure (HHF) associated with cilostazol use in the patients of diabetes mellitus. Methods: This case-crossover study retrieved records on diabetic patients > 20 years of age who were hospitalized for heart failure during the period of 2009-2011 from the Taiwan National Health Insurance Database. The "current" period was defined as 1-30 days prior to HHF whereas the 91-120 days prior to HHF served as the "reference" period. The exposure status just preceding the event is compared with exposure of the same person in one or more referent remote to the event. Adjusted odds ratios (OR) were used to estimate time-varying discordant exposure by the ratio of the number exposed to cilostazol only during the case period to the number exposed to cilostazol only during the control period. Results: A total of 47,506 diabetic patients were included in the analysis (average age: 72.7 ± 12.4, percentage of males: 48%). A total of 399 patients (0.84%) received cilostazol only in the current period, and 252 (0.53%) received cilostazol only in the reference period. After adjustment for other medications, a significant association was found between cilostazol and HHF (OR: 1.35, 95% CI: 1.14-1.59). After further adjustment for time-varying co-morbidities the ORs remained essentially the same. Sensitivity analyses using different definitions of control period (ranging from 31-60, 61-90, to 121-150 days before index date) yielded adjusted ORs of 1.43 (95% CI: 1.14-1.79), 1.31 (95% CI: 1.09-1.57) and 1.23 (95% CI: 1.06-1.44), respectively suggesting the robustness of our study findings. Conclusion: Use of cilostazol may be positively related to the risk of HHF. Further studies are warranted to explore the underlying mechanisms and to confirm the association.
| S-EPMC6330376 | biostudies-literature
Project description:BackgroundPrior studies suggest that the relationship between hypothyroidism and mortality is dependent on underlying cardiovascular risk. Little is known about the association of hypothyroidism with hospitalization risk, and how these associations are modified by cardiovascular status.MethodsThis study examined the association of thyroid status, defined by serum thyrotropin (TSH), with hospitalization risk among patients who received care at a large university-based tertiary care center between 1990 and 2015. Thyroid status was categorized as hypothyroidism versus euthyroidism (TSH >4.7 vs. 0.3-4.7?mIU/L, respectively). The relationship between thyroid status and hospitalization risk stratified by cardiovascular status was examined using multivariable Cox models.ResultsAmong 52,856 patients who met eligibility criteria, 49,791 (94.2%) had euthyroidism and 3065 (5.8%) had hypothyroidism. In analyses stratified by congestive heart failure (CHF) status, compared to euthyroidism, hypothyroidism was associated with higher risk of hospitalization in those with CHF but slightly lower risk in those without CHF (adjusted hazard ratio [aHRs]?=?1.86 [confidence interval (CI) 1.17-2.94] and HR?=?0.95 [CI 0.92-0.99], respectively; p?=?0.006). In sensitivity analyses accounting for death as a competing event, underlying coronary artery disease modified the hypothyroidism-hospitalization relationship, such that stronger associations were observed among those with versus without coronary artery disease. In competing risk analyses, hypothyroidism was associated with higher versus lower risk of hospitalization among those with versus without cerebrovascular disease, respectively.ConclusionsHypothyroidism is associated with higher hospitalization risk among patients with underlying cardiovascular disease. Future studies are needed to determine whether correction of thyroid status with replacement therapy ameliorates hospitalization risk in this population.
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Project description:ObjectiveTo characterize the absolute risks for older patients of readmission to hospital and death in the year after hospitalization for heart failure, acute myocardial infarction, or pneumonia.DesignRetrospective cohort study.Setting4767 hospitals caring for Medicare fee for service beneficiaries in the United States, 2008-10.ParticipantsMore than 3 million Medicare fee for service beneficiaries, aged 65 years or more, surviving hospitalization for heart failure, acute myocardial infarction, or pneumonia.Main outcome measuresDaily absolute risks of first readmission to hospital and death for one year after discharge. To illustrate risk trajectories, we identified the time required for risks of readmission to hospital and death to decline 50% from maximum values after discharge; the time required for risks to approach plateau periods of minimal day to day change, defined as 95% reductions in daily changes in risk from maximum daily declines after discharge; and the extent to which risks are higher among patients recently discharged from hospital compared with the general elderly population.ResultsWithin one year of hospital discharge, readmission to hospital and death, respectively, occurred following 67.4% and 35.8% of hospitalizations for heart failure, 49.9% and 25.1% for acute myocardial infarction, and 55.6% and 31.1% for pneumonia. Risk of first readmission had declined 50% by day 38 after hospitalization for heart failure, day 13 after hospitalization for acute myocardial infarction, and day 25 after hospitalization for pneumonia; risk of death declined 50% by day 11, 6, and 10, respectively. Daily change in risk of first readmission to hospital declined 95% by day 45, 38, and 45; daily change in risk of death declined 95% by day 21, 19, and 21. After hospitalization for heart failure, acute myocardial infarction, or pneumonia, the magnitude of the relative risk for hospital admission over the first 90 days was 8, 6, and 6 times greater than that of the general older population; the relative risk of death was 11, 8, and 10 times greater.ConclusionsRisk declines slowly for older patients after hospitalization for heart failure, acute myocardial infarction, or pneumonia and is increased for months. Specific risk trajectories vary by discharge diagnosis and outcome. Patients should remain vigilant for deterioration in health for an extended time after discharge. Health providers can use knowledge of absolute risks and their changes over time to better align interventions designed to reduce adverse outcomes after discharge with the highest risk periods for patients.
| S-EPMC4353309 | biostudies-literature
Project description:Background Clinical prediction models have been developed for hospitalization for heart failure in type 2 diabetes. However, a systematic evaluation of these models' performance, applicability, and clinical impact is absent. Methods and Results We searched Embase, MEDLINE, Web of Science, Google Scholar, and Tufts' clinical prediction registry through February 2021. Studies needed to report the development, validation, clinical impact, or update of a prediction model for hospitalization for heart failure in type 2 diabetes with measures of model performance and sufficient information for clinical use. Model assessment was done with the Prediction Model Risk of Bias Assessment Tool, and meta-analyses of model discrimination were performed. We included 15 model development and 3 external validation studies with data from 999 167 people with type 2 diabetes. Of the 15 models, 6 had undergone external validation and only 1 had low concern for risk of bias and applicability (Risk Equations for Complications of Type 2 Diabetes). Seven models were presented in a clinically useful manner (eg, risk score, online calculator) and 2 models were classified as the most suitable for clinical use based on study design, external validity, and point-of-care usability. These were Risk Equations for Complications of Type 2 Diabetes (meta-analyzed c-statistic, 0.76) and the Thrombolysis in Myocardial Infarction Risk Score for Heart Failure in Diabetes (meta-analyzed c-statistic, 0.78), which was the simplest model with only 5 variables. No studies reported clinical impact. Conclusions Most prediction models for hospitalization for heart failure in patients with type 2 diabetes have potential concerns with risk of bias or applicability, and uncertain external validity and clinical impact. Future research is needed to address these knowledge gaps.
| S-EPMC9238543 | biostudies-literature
Project description:Background: The association between metabolic syndrome and the development of heart failure (HF) with preserved ejection fraction (HFpEF) has not been completely clarified. Aim: To evaluate the association between metabolic syndrome and the risk of HF hospitalization for patients with HFpEF. Methods: Patient data were obtained from the American cohort of the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) trial database. Data for the primary outcome (hospitalization for HF) and secondary outcomes (all-cause mortality, cardiovascular mortality, and all-cause hospitalization) were collected, and hazard ratios (HRs) for the patients with and without metabolic syndrome were analyzed by applying a multivariable Cox proportional hazard model. Results: Among the 1,548 total participants, 1,197 had metabolic syndrome. The patients with metabolic syndrome exhibited worse heart function and a lower quality of life than those without metabolic syndrome. During the 3.3 years of follow-up, 351 patients were hospitalized for HF. After a multivariable adjustment, the risk of hospitalization for HF and all-cause hospitalization (adjusted HR = 1.42, 95% CI: 1.01-2.00; p = 0.042 and adjusted HR = 1.27; 95% CI: 1.04-1.54; p = 0.017, respectively) were independently associated with HFpEF for the patients with metabolic syndrome. In addition, the risks of HF hospitalization and all-cause hospitalization among 267 propensity score-matched patients were higher for patients with metabolic syndrome (HR = 1.53, 95% CI = 1.05-2.23, and p = 0.025 and HR = 1.34, 95% CI = 1.08-1.67, and p = 0.009, respectively). Conclusion: The risks of HF hospitalization and all-cause hospitalization were higher for patients with HFpEF having metabolic syndrome than for those without metabolic syndrome.
| S-EPMC8476762 | biostudies-literature
Project description:OBJECTIVE:To develop and validate a novel, machine learning-derived model to predict the risk of heart failure (HF) among patients with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS:Using data from 8,756 patients free at baseline of HF, with <10% missing data, and enrolled in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, we used random survival forest (RSF) methods, a nonparametric decision tree machine learning approach, to identify predictors of incident HF. The RSF model was externally validated in a cohort of individuals with T2DM using the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). RESULTS:Over a median follow-up of 4.9 years, 319 patients (3.6%) developed incident HF. The RSF models demonstrated better discrimination than the best performing Cox-based method (C-index 0.77 [95% CI 0.75-0.80] vs. 0.73 [0.70-0.76] respectively) and had acceptable calibration (Hosmer-Lemeshow statistic ?2 = 9.63, P = 0.29) in the internal validation data set. From the identified predictors, an integer-based risk score for 5-year HF incidence was created: the WATCH-DM (Weight [BMI], Age, hyperTension, Creatinine, HDL-C, Diabetes control [fasting plasma glucose], QRS Duration, MI, and CABG) risk score. Each 1-unit increment in the risk score was associated with a 24% higher relative risk of HF within 5 years. The cumulative 5-year incidence of HF increased in a graded fashion from 1.1% in quintile 1 (WATCH-DM score ?7) to 17.4% in quintile 5 (WATCH-DM score ?14). In the external validation cohort, the RSF-based risk prediction model and the WATCH-DM risk score performed well with good discrimination (C-index = 0.74 and 0.70, respectively), acceptable calibration (P ?0.20 for both), and broad risk stratification (5-year HF risk range from 2.5 to 18.7% across quintiles 1-5). CONCLUSIONS:We developed and validated a novel, machine learning-derived risk score that integrates readily available clinical, laboratory, and electrocardiographic variables to predict the risk of HF among outpatients with T2DM.
| S-EPMC7364669 | biostudies-literature