scholarly journals Temporal trends in mortality and readmission after acute heart failure: A systematic review and meta‐regression in the past four decades

2021 ◽  
Author(s):  
Antoine Kimmoun ◽  
Koji Takagi ◽  
Emmanuel Gall ◽  
Shiro Ishihara ◽  
Pierre Hammoum ◽  
...  
Keyword(s):  
Heart Failure ◽  
Systematic Review ◽  
Acute Heart Failure ◽  
Temporal Trends ◽  
The Past ◽  
Meta Regression

Similar hemodynamic decongestion with vasodilators and inotropes: systematic review, meta-analysis, and meta-regression of 35 studies on acute heart failure

2016 ◽  
Vol 105 (12) ◽  
pp. 971-980 ◽  
Author(s):  
Shiro Ishihara ◽  
Etienne Gayat ◽  
Naoki Sato ◽  
Mattia Arrigo ◽  
Said Laribi ◽  
...  
Keyword(s):  
Heart Failure ◽  
Systematic Review ◽  
Acute Heart Failure ◽  
Meta Analysis ◽  
Meta Regression

Temporal trends in the outcomes of acute heart failure: between consolatory evidences and real progress

2021 ◽  
Vol 23 (3) ◽  
pp. 432-435
Author(s):  
Ovidiu Chioncel ◽  
Andrew P. Ambrosy ◽  
Aldo P. Maggioni
Keyword(s):  
Heart Failure ◽  
Acute Heart Failure ◽  
Temporal Trends ◽  
Real Progress

A Systematic Review and Meta-regression of Temporal Trends in Adult CD4+ Cell Count at Presentation to HIV Care, 1992-2011

2013 ◽  
Vol 57 (7) ◽  
pp. 1027-1037 ◽  
Author(s):  
C. R. Lesko ◽  
S. R. Cole ◽  
A. Zinski ◽  
C. Poole ◽  
M. J. Mugavero
Keyword(s):  
Systematic Review ◽  
Cell Count ◽  
Temporal Trends ◽  
Hiv Care ◽  
Cd4 Cell Count ◽  
Meta Regression ◽  
Cd4 Cell

scholarly journals Temporal trends in sperm count: a systematic review and meta-regression analysis

2017 ◽  
Vol 23 (6) ◽  
pp. 646-659 ◽  
Author(s):  
Hagai Levine ◽  
Niels Jørgensen ◽  
Anderson Martino-Andrade ◽  
Jaime Mendiola ◽  
Dan Weksler-Derri ◽  
...  
Keyword(s):  
Systematic Review ◽  
Regression Analysis ◽  
Sperm Count ◽  
Temporal Trends ◽  
Meta Regression ◽  
Meta Regression Analysis

scholarly journals Risk Prediction Models for Patients With Acute Heart Failure: A Protocol for Systematic Review, Critical Appraisal, and Meta-Analysis

2021 ◽  
Author(s):  
Xuecheng Zhang ◽  
Kehua Zhou ◽  
Jingjing Zhang ◽  
Ying Chen ◽  
Hengheng Dai ◽  
...  
Keyword(s):  
Heart Failure ◽  
Systematic Review ◽  
Prediction Model ◽  
Acute Heart Failure ◽  
Risk Prediction ◽  
Methodological Quality ◽  
Critical Appraisal ◽  
Prediction Models ◽  
Cochrane Library ◽  
Risk Prediction Models

Abstract Background Nearly a third of patients with acute heart failure (AHF) die or are readmitted within three months after discharge, accounting for the majority of costs associated with heart failure-related care. A considerable number of risk prediction models, which predict outcomes for mortality and readmission rates, have been developed and validated for patients with AHF. These models could help clinicians stratify patients by risk level and improve decision making, and provide specialist care and resources directed to high-risk patients. However, clinicians sometimes reluctant to utilize these models, possibly due to their poor reliability, the variety of models, and/or the complexity of statistical methodologies. Here, we describe a protocol to systematically review extant risk prediction models. We will describe characteristics, compare performance, and critically appraise the reporting transparency and methodological quality of risk prediction models for AHF patients. Method Embase, Pubmed, Web of Science, and the Cochrane Library will be searched from their inception onwards. A back word will be searched on derivation studies to find relevant external validation studies. Multivariable prognostic models used for AHF and mortality and/or readmission rate will be eligible for review. Two reviewers will conduct title and abstract screening, full-text review, and data extraction independently. Included models will be summarized qualitatively and quantitatively. We will also provide an overview of critical appraisal of the methodological quality and reporting transparency of included studies using the Prediction model Risk of Bias Assessment Tool(PROBAST tool) and the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis(TRIPOD statement). Discussion The result of the systematic review could help clinicians better understand and use the prediction models for AHF patients, as well as make standardized decisions about more precise, risk-adjusted management. Systematic review registration : PROSPERO registration number CRD42021256416.

Prediction of Early Adverse Events in Emergency Department Patients With Acute Heart Failure: A Systematic Review

2018 ◽  
Vol 34 (2) ◽  
pp. 168-179 ◽  
Author(s):  
Allison M. Michaud ◽  
Shannon I.A. Parker ◽  
Heather Ganshorn ◽  
Justin A. Ezekowitz ◽  
Andrew D. McRae
Keyword(s):  
Heart Failure ◽  
Systematic Review ◽  
Emergency Department ◽  
Adverse Events ◽  
Acute Heart Failure ◽  
Emergency Department Patients
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