Clinical prediction of incident heart failure risk: a systematic review and meta-analysis.
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ABSTRACT:
SUBMITTER: Yang H
PROVIDER: S-EPMC4395833 | biostudies-other | 2015
REPOSITORIES: biostudies-other
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Project description:Patients recovered from COVID-19 have an increased incidence of cardiovascular disease and heart structural changes. The aim of the present manuscript is to assess the risk of incident heart failure (HF) after COVID-19 infection. Data were obtained searching MEDLINE and Scopus for all studies published at any time up to September 1, 2022 reporting the risk of incident HF in COVID-19 recovered patients. The cumulative post-COVID-19 incidence and risk of incident HF were pooled using a random effects model and presented with the corresponding 95% confidence interval (CI). Statistical heterogeneity was measured using the Higgins I2 statistic. Overall, 21,463,173 patients (mean age 54.5 years, 58.7% males) were analyzed. Among them, 1,628,424 had confirmed COVID-19 infection while the remaining 19,834,749 represented the controls. The mean length of follow-up was 9.2 months. A random effect model revealed a pooled incidence of post COVID-19 HF in 1.1% of cases (95% CI: 0.7-1.6, I2: 99.8%). Moreover, recovered COVID-19 patients showed an increased risk of incident HF (HR: 1.90, 95% CI: 1.54-3.24, p < 0.0001, I2 = 96.5%) in the same follow-up period. Meta-regression showed a direct relationship for the risk of incident HF using age (p = 0.001) and hypertension (HT) (p = 0.02) as moderators, while an inverse association was observed when the follow-up length was adopted as moderating variable (p = 0.01). COVID-19 survivors had an additional 90% risk of developing HF after COVID-19 infection in the long-term period. This risk was directly related with age and previous history of HT especially in the early post-acute phase of the infection.
| S-EPMC9792307 | biostudies-literature
Project description:BackgroundThe association between the development of heart failure (HF) and use of nonsteroidal anti-inflammatory drugs (NSAIDs) is not well established.HypothesisUse of NSAIDs may increase the risk of incident HF.MethodsWe conducted a systematic review and meta-analysis of observational studies that reported odds ratio, relative risk, hazard ratio, or standardized incidence ratio comparing risk of incident HF in NSAID users vs nonusers. Pooled risk ratios (RR) and 95% confidence intervals (CI) for all NSAIDs and both subclasses (conventional NSAIDs and highly selective cyclooxygenase-2 inhibitors [COXIBs]) were calculated using a random-effect, generic inverse variance method.ResultsSeven studies with 7,543,805 participants were identified and included in our data analysis. Use of NSAIDs was associated with a significantly higher risk of developing HF, with a pooled RR of 1.17 (95% CI: 1.01-1.36). Subgroup analysis showed a significantly elevated risk among users of conventional NSAIDs (RR: 1.35, 95% CI: 1.15-1.57) but not users of COXIBs (RR: 1.03, 95% CI: 0.92-1.16).ConclusionsA significantly elevated risk of incident HF was observed among users of NSAIDs.
| S-EPMC6490752 | 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:BackgroundThe relationship between resting heart rate (RHR) and incident heart failure (HF) has been questioned.Methods and resultsRHR was assessed at baseline in 7073 participants in 3 prospective cohorts (Cardiovascular Health Study, Health ABC study and Kuopio Ischemic Heart Disease Study) that recorded 1189 incident HF outcomes during 92 702 person-years of follow-up. Mean age of participants was 67 (9.9) years and mean RHR was 64.6 (11.1) bpm. Baseline RHR correlated (P<0.001) positively with body mass index (r=0.10), fasting glucose (r=0.18), and C-reactive protein (r=0.20); and inversely with serum creatinine (r=-0.05) and albumin (r=-0.05). Baseline RHR was non-linearly associated with HF risk. The age and sex-adjusted hazard ratio for HF comparing the top (>72 bpm) versus the bottom (<57 bpm) quartile of baseline RHR was 1.48 (95% confidence interval [CI] 1.26 to 1.74) and was modestly attenuated (1.30, 95% CI 1.10 to 1.53) with further adjustment for body mass index, history of diabetes, hypertension, smoking status, serum creatinine, and left ventricular hypertrophy. These findings remained consistent in analyses accounting for incident coronary heart disease, excluding individuals with prior cardiovascular events, or those taking beta-blockers; and in subgroups defined by several individual participant characteristics. In a pooled random effects meta-analysis of 7 population-based studies (43 051 participants and 3476 HF events), the overall hazard ratio comparing top versus bottom fourth of RHR was 1.40 (95% CI: 1.19 to 1.64).ConclusionsThere is a non-linear association between RHR and incident HF. Further research is needed to understand the physiologic foundations of this association.
| S-EPMC4330063 | biostudies-literature
Project description:Importance:Fear of dementia is pervasive in older people with cognitive concerns. Much research is devoted to finding prognostic markers for dementia risk. Studies suggest apathy in older people may be prodromal to dementia and could be a relevant, easily measurable predictor of increased dementia risk. However, evidence is fragmented and methods vary greatly between studies. Objective:To systematically review and quantitatively synthesize the evidence for an association between apathy in dementia-free older individuals and incident dementia. Data Sources:Two reviewers conducted a systematic search of Medline, Embase, and PsychINFO databases. Study Selection:Inclusion criteria were (1) prospective cohort studies, (2) in general populations or memory clinic patients without dementia, (3) with clear definitions of apathy and dementia, and (4) reporting on the association between apathy and incident dementia. Data Extraction and Synthesis:PRISMA and MOOSE guidelines were followed. Data were extracted by 1 reviewer and checked by a second. Main Outcomes and Measures:Main outcomes were pooled crude risk ratios, maximally adjusted reported hazard ratios (HR), and odds ratios (OR) using DerSimonian-Laird random effects models. Results:The mean age of the study populations ranged from 69.2 to 81.9 years (median, 71.6 years) and the percentage of women ranged from 35% to 70% (median, 53%). After screening 2031 titles and abstracts, 16 studies comprising 7365 participants were included. Apathy status was available for 7299 participants. Studies included populations with subjective cognitive concerns (n = 2), mild cognitive impairment (n = 11), cognitive impairment no dementia (n = 1), or mixed cognitive and no cognitive impairment (n = 2). Apathy was present in 1470 of 7299 participants (20.1%). Follow-up ranged from 1.2 to 5.4 years. In studies using validated apathy definitions (n = 12), the combined risk ratio of dementia for patients with apathy was 1.81 (95% CI, 1.32-2.50; I2 = 76%; n = 12), the hazard ratio was 2.39 (95% CI, 1.27-4.51; I2 = 90%; n = 7), and the odds ratio was 17.14 (95% CI, 1.91-154.0; I2 = 60%; n = 2). Subgroup analyses, meta-regression, and individual study results suggested the association between apathy and dementia weakened with increasing follow-up time, age, and cognitive impairment. Meta-regression adjusting for apathy definition and follow-up time explained 95% of heterogeneity in mild cognitive impairment. Conclusions and Relevance:Apathy was associated with an approximately 2-fold increased risk of dementia in memory clinic patients. Moderate publication bias may have inflated some of these estimates. Apathy deserves more attention as a relevant, cheap, noninvasive, and easily measureable marker of increased risk of incident dementia with high clinical relevance, particularly because these vulnerable patients may forgo health care.
| S-EPMC6233800 | biostudies-other
Project description:Heart failure (HF) is a major public health problem. Early identification of at-risk individuals could allow for interventions that reduce morbidity or mortality. The community-based FINRISK Microbiome DREAM challenge (synapse.org/finrisk) evaluated the use of machine learning approaches on shotgun metagenomics data obtained from fecal samples to predict incident HF risk over 15 years in a population cohort of 7231 Finnish adults (FINRISK 2002, n=559 incident HF cases). Challenge participants used synthetic data for model training and testing. Final models submitted by seven teams were evaluated in the real data. The two highest-scoring models were both based on Cox regression but used different feature selection approaches. We aggregated their predictions to create an ensemble model. Additionally, we refined the models after the DREAM challenge by eliminating phylum information. Models were also evaluated at intermediate timepoints and they predicted 10-year incident HF more accurately than models for 5- or 15-year incidence. We found that bacterial species, especially those linked to inflammation, are predictive of incident HF. This highlights the role of the gut microbiome as a potential driver of inflammation in HF pathophysiology. Our results provide insights into potential modeling strategies of microbiome data in prospective cohort studies. Overall, this study provides evidence that incorporating microbiome information into incident risk models can provide important biological insights into the pathogenesis of HF.
| S-EPMC10593042 | biostudies-literature
Project description:AimsSarcopenia has been found to be frequently associated with co-morbidity among patients with heart failure (HF). However, there remain insufficient data to accurately estimate the global prevalence of sarcopenia in HF. Therefore, the purpose of this research was to conduct a systematic review and meta-analysis to estimate the current overall prevalence of sarcopenia in patients with HF.Methods and resultsWe searched relevant databases for studies published up to 13 July 2020, assessing sarcopenia in vpatients with HF. After careful screening, data of included articles were extracted with a predesigned Excel form. Then the pooled prevalence of sarcopenia in patients with HF was calculated using the random-effects model. The Q test was used to assess the heterogeneity, and I2 statistic was calculated to quantify and evaluate the heterogeneity. Subgroup analyses were conducted to determine potential sources of heterogeneity. A total of 2852 articles were initially identified, and after removing duplicate publications and applying the selection criteria, we reviewed 79 full-text articles. Finally, 11 articles (n = 1742 patients with HF) were included in this systematic review and meta-analysis. The pooled prevalence of sarcopenia in patients with HF was 34% [95% confidence interval (CI): 22-47%, I2 = 96.59%] and ranged from 10% to 69%. However, substantial heterogeneity between studies (I2 = 96.59%, P < 0.001) was observed. There was no significant heterogeneity between subgroups by sex (P = 0.803) or the method used to define sarcopenia (P = 0.307). While the heterogeneity between subgroups by population setting was statistically significant (P < 0.001), the pooled prevalence of sarcopenia was 55% (95% CI: 43-66%) for hospitalized patients with HF and 26% (95% CI: 16-37%) for ambulatory patients.ConclusionsSarcopenia was a common condition in patients with HF, and the prevalence of hospitalized patients was higher than for ambulatory patients. Early detection of sarcopenia was therefore important in patients with HF, and it was important to implement interventions so that physical therapists or managerial dieticians can easily be introduced into clinical practice.
| S-EPMC8006658 | biostudies-literature
Project description:ObjectiveTo determine the association between self reported job insecurity and incident coronary heart disease.DesignA meta-analysis combining individual level data from a collaborative consortium and published studies identified by a systematic review.Data sourcesWe obtained individual level data from 13 cohort studies participating in the Individual-Participant-Data Meta-analysis in Working Populations Consortium. Four published prospective cohort studies were identified by searches of Medline (to August 2012) and Embase databases (to October 2012), supplemented by manual searches.Review methodsProspective cohort studies that reported risk estimates for clinically verified incident coronary heart disease by the level of self reported job insecurity. Two independent reviewers extracted published data. Summary estimates of association were obtained using random effects models.ResultsThe literature search yielded four cohort studies. Together with 13 cohort studies with individual participant data, the meta-analysis comprised up to 174,438 participants with a mean follow-up of 9.7 years and 1892 incident cases of coronary heart disease. Age adjusted relative risk of high versus low job insecurity was 1.32 (95% confidence interval 1.09 to 1.59). The relative risk of job insecurity adjusted for sociodemographic and risk factors was 1.19 (1.00 to 1.42). There was no evidence of significant differences in this association by sex, age (<50 v ≥ 50 years), national unemployment rate, welfare regime, or job insecurity measure.ConclusionsThe modest association between perceived job insecurity and incident coronary heart disease is partly attributable to poorer socioeconomic circumstances and less favourable risk factor profiles among people with job insecurity.
| S-EPMC3738256 | biostudies-literature
Project description:Objectives: A systematic review and meta-analysis was performed to evaluate the potential prognostic role of serum uric acid (SUA) in patients with chronic heart failure (CHF). Methods: The Embase, PubMed, Web of Science and Cochrane Library databases were searched up to 5 April 2021 for relevant publications. Random effects model was used to pool data. STATA15.0 software was used to perform meta-analysis. Heterogeneity was assessed using the Cochran Q statistic (significance level of P < 0.10) and I 2 statistics (significance level of 50%). Results: Ultimately, 18 publications reporting adverse events in CHF patients were included. The results indicate reveal associations between a high level of SUA and the risk of all-cause mortality (HR 2.24, 95% CI 1.49-3.37), cardiovascular mortality (HR 1.14, 95% CI 1.06-1.23), and the composite of death or cardiac events (HR 1.26, 95% CI 1.01-1.56) in CHF patients. A 1 mg/dL increase in serum uric acid led to 4% (HR 1.04, 95% CI 1.02-1.05) and 9% (HR 1.09, 95% CI 1.03-1.17) increases in the risk of all-cause mortality and the composite endpoint of death or cardiac events in CHF patients, respectively. Conclusion: Serum uric acid is positively associated with the risk of adverse events in CHF patients. This study protocol has been registered at PROSPERO as CRD42021247084 (https://www.crd.york.ac.uk/PROSPERO). Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO.
| S-EPMC8715937 | biostudies-literature
Project description:BACKGROUND:The ability to predict risk allows healthcare providers to propose which patients might benefit most from certain therapies, and is relevant to payers' demands to justify clinical and economic value. To understand the robustness of risk prediction models for heart failure (HF), we conducted a systematic literature review to (1) identify HF risk-prediction models, (2) assess statistical approach and extent of validation, (3) identify common variables, and (4) assess risk of bias (ROB). METHODS:Literature databases were searched from March 2013 to May 2018 to identify risk prediction models conducted in an out-of-hospital setting in adults with HF. Distinct risk prediction variables were ranked according to outcomes assessed and incorporation into the studies. ROB was assessed using Prediction model Risk Of Bias ASsessment Tool (PROBAST). RESULTS:Of 4720 non-duplicated citations, 40 risk-prediction publications were deemed relevant. Within the 40 publications, 58 models assessed 55 (co)primary outcomes, including all-cause mortality (n = 17), cardiovascular death (n = 9), HF hospitalizations (n = 15), and composite endpoints (n = 14). Few publications reported detail on handling missing data (n = 11; 28%). The discriminatory ability for predicting all-cause mortality, cardiovascular death, and composite endpoints was generally better than for HF hospitalization. 105 distinct predictor variables were identified. Predictors included in >5 publications were: N-terminal prohormone brain-natriuretic peptide, creatinine, blood urea nitrogen, systolic blood pressure, sodium, NYHA class, left ventricular ejection fraction, heart rate, and characteristics including male sex, diabetes, age, and BMI. Only 11/58 (19%) models had overall low ROB, based on our application of PROBAST. In total, 26/58 (45%) models discussed internal validation, and 14/58 (24%) external validation. CONCLUSIONS:The majority of the 58 identified risk-prediction models for HF present particular concerns according to ROB assessment, mainly due to lack of validation and calibration. The potential utility of novel approaches such as machine learning tools is yet to be determined. REGISTRATION NUMBER:The SLR was registered in Prospero (ID: CRD42018100709).
| S-EPMC6961879 | biostudies-literature