Home > Journals > Minerva Anestesiologica > Past Issues > Minerva Anestesiologica 2019 April;85(4) > Minerva Anestesiologica 2019 April;85(4):433-42

CURRENT ISSUE
 

JOURNAL TOOLS

eTOC
To subscribe
Submit an article
Recommend to your librarian
 

ARTICLE TOOLS

Publication history
Reprints
Permissions
Cite this article as

 

REVIEW   Freefree

Minerva Anestesiologica 2019 April;85(4):433-42

DOI: 10.23736/S0375-9393.19.13267-1

Copyright © 2019 EDIZIONI MINERVA MEDICA

language: English

What have we learned from network meta-analyses applied to critical care?

Orville V. BAEZ-PRAVIA 1, Lara MONTES-ANDUJAR 2, 3, Justo MENÉNDEZ 2, 3, Pablo CARDINAL-FERNÁNDEZ 2, 4

1 Intensive Care Unit, HM Sanchinarro University Hospital, Madrid, Spain; 2 Department of Emergency Medicine, HM Sanchinarro University Hospital, Madrid, Spain; 3 CEU San Pablo University, Madrid, Spain; 4 HM Research Foundation, HM Hospitals, Madrid, Spain



It is widely accepted in modern medicine that medical decisions must be supported by scientific evidence. Identifying the best intervention when several options are available constitute a great challenge for every clinician. Traditional meta-analysis (TMA) allows summarizing evidence from studies that compare the same two interventions for one event (head to head studies or direct comparisons). Network meta-analysis (NMA) is a relatively new procedure that allows to compare multiple interventions for one event, even when non-head to head studies have been conducted (indirect evidence). Other advantages of NMA include increasing the accuracy of the results and ranking all the interventions according to their effectiveness. These features are of paramount importance as: 1) they summarize information from events (e.g. diseases or outcomes) that has more than two possible interventions (e.g. treatments or procedures); 2) they strengthen the level of guideline recommendations; and 3) they identify new hypotheses based on indirect comparison. As this is a narrative review, all manuscripts have been selected from PubMed according to our best knowledge with the aim to illustrate different features, options or applications of NMA in critical care. First, we provide a description of the usefulness, interpretation, assumptions and main plots related to NMAs. Second, we analyzed some examples of NMAs related to critical care medicine. Third, we include a pragmatic approach about how results from NMAs can improve the clinical practice as well an R script with a database to conduct an NMAs and reproduce figures and tables that have been shown here. As a conclusion, NMA is an established, robust, objective and reproducible statistic technique that has been applied to several critical care areas. Clinical practice guidelines have started to include NMA evidence to support their recommendations. In future years, it seems highly probable that this technique will increase it applicability in almost all areas of critical care medicine.


KEY WORDS: Network meta-analysis; Respiratory care units; Epidemiology; Evidence-based medicine

top of page