Raw data for a systematic review of statistical methodologies to evaluate progression of chronic kidney disease using electronic healthcare records

Cleary, F, Nitsch, D and Prieto, D. 2021. Raw data for a systematic review of statistical methodologies to evaluate progression of chronic kidney disease using electronic healthcare records. [Online]. London School of Hygiene & Tropical Medicine, London, United Kingdom. Available from: https://doi.org/10.17037/DATA.00002628.

Cleary, F, Nitsch, D and Prieto, D. Raw data for a systematic review of statistical methodologies to evaluate progression of chronic kidney disease using electronic healthcare records [Internet]. London School of Hygiene & Tropical Medicine; 2021. Available from: https://doi.org/10.17037/DATA.00002628.

Cleary, F, Nitsch, D and Prieto, D (2021). Raw data for a systematic review of statistical methodologies to evaluate progression of chronic kidney disease using electronic healthcare records. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002628.

Description

Data collected as part of a systematic review of published research on chronic kidney disease progression using electronic healthcare records. Eligible studies were located by searching 4 databases (Medline, Embase, Global Health and Web of Science). In total, 80 research studies are described in the dataset. Each row presents an individual study, providing information on the study population, study methodology, the investigators’ handling of data quality issues, and other key information. Please consult the Methods section for further information.

Methods

Description of data capture

We searched for eligible studies in 4 databases (Medline, Embase, Global Health and Web of Science) available as of August 2021. The systematic review had one lead reviewer and two supporting reviewers. The lead reviewer was responsible for extracting data from all eligible research articles, capturing all items required to be summarised in the review, which included items related to study population, study methodology and handling of data quality issues. In addition, key items that were the subject of this review were validated by supporting reviewers who independently extracted the following items for all articles: (1) measure of change in renal function; (2) statistical methods used in analysis of changes in renal function; and (3) definitions of progression of CKD, if any. Any disagreements on key items were discussed and decisions agreed.

Data capture method

Aggregation

Data Collection Period

From	To
7 May 2020	30 September 2021

Date (Date submitted to LSHTM repository)

15 November 2021

Language(s) of written materials

English

People & Groups

Data Creators	Cleary, F, Nitsch, D and Prieto, D
LSHTM Faculty/Department	Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology
Participating Institutions	London School of Hygiene & Tropical Medicine, London, United Kingdom

Projects

Funders

Project	Funder	Grant Number	Funder URI
A systematic review of statistical methodology used to evaluate progression of chronic kidney disease using electronic healthcare records	Medical Research Council	MR/N013638/1	http://dx.doi.org/10.13039/501100000265