Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/26679
Title: Reported methods for handling missing change standard deviations in meta-analyses of exercise therapy interventions in patients with heart failure: A systematic review
Contributor(s): Pearson, Melissa J  (author); Smart, Neil A  (author)orcid 
Publication Date: 2018-10-18
Open Access: Yes
DOI: 10.1371/journal.pone.0205952Open Access Link
Handle Link: https://hdl.handle.net/1959.11/26679
Abstract: Background: Well-constructed systematic reviews and meta-analyses are key tools in evidenced-based healthcare. However, a common problem with performing a meta-analysis is missing data, such as standard deviations (SD). An increasing number of methods are utilised to calculate or impute missing SDs, allowing these studies to be included in analyses. The aim of this review was to investigate the methods reported and utilised for handling missing change SDs in meta-analyses, using the topic of exercise therapy in heart failure patients as a model. Methods: A systematic search of PubMed, EMBASE and Cochrane Library from 1 January 2014 to 31st March 2018 was conducted for meta-analyses of exercise based trials in heart failure. Studies were eligible to be included if they performed a meta-analysis of change in exercise capacity in heart failure patients after a training intervention. Results: Twenty two publications performed a meta-analysis on the effect of exercise therapy on exercise capacity in heart failure patients. Eleven (50%) publications did not directly report the approach for dealing with missing change SDs. Approaches reported and utilised to deal with missing change SDs included imputation, actual and approximate algebraic recalculation using study level summary statistics and exclusion of studies. Conclusion: Change SDs are often not reported in trial papers and while in the first instance meta-analysts should attempt to obtain missing data from trial authors, this information is frequently not forthcoming. Meta-analysts are then forced to make a decision on how these trials and missing data are to be handled. Whilst not one approach is favoured for dealing with this matter, authors need to clearly report the approach to be utilised for missing change SDs. Where change SDs are imputed meta-analyst are encouraged to explore several options and have a sound rationale as to the choice, and where data is imputed, sensitivity analysis should be conducted.
Publication Type: Journal Article
Source of Publication: PLoS One, 13(10), p. 1-14
Publisher: Public Library of Science
Place of Publication: United States of America
ISSN: 1932-6203
Fields of Research (FoR) 2008: 110602 Exercise Physiology
110201 Cardiology (incl. Cardiovascular Diseases)
Fields of Research (FoR) 2020: 320101 Cardiology (incl. cardiovascular diseases)
Socio-Economic Objective (SEO) 2008: 920103 Cardiovascular System and Diseases
Socio-Economic Objective (SEO) 2020: 200101 Diagnosis of human diseases and conditions
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

Files in This Item:
2 files
File Description SizeFormat 
Show full item record

SCOPUSTM   
Citations

9
checked on Mar 16, 2024

Page view(s)

1,492
checked on May 7, 2023
Google Media

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons