Identification of incident CKD stage 3 in research studies
Morgan E Grams1, Casey M Rebholz2, Blaithin McMahon1
1Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, MD.
Insights
Supplementing laboratory data with hospitalization records improves chronic kidney disease (CKD) identification in epidemiologic studies. This approach enhances disease capture between study visits, especially for older patients with diabetes or existing CKD.
Area of Science:
- Epidemiologic research
- Nephrology
- Public health surveillance
Background:
- Chronic kidney disease (CKD) diagnosis in research typically relies on laboratory tests at scheduled visits.
- Patients with incident CKD may miss visits, potentially biasing study findings.
- This study assesses loss to follow-up by CKD status and the utility of diagnostic codes.
Purpose of the Study:
- To quantify loss to follow-up in relation to chronic kidney disease (CKD) status.
- To evaluate if incorporating diagnostic code data improves the capture of incident CKD cases.
Main Methods:
- Prospective cohort study of 11,560 participants in the Atherosclerosis Risk in Communities (ARIC) Study (1996-2013).
- Incident CKD stage 3 defined by a ≥25% decline in estimated glomerular filtration rate (eGFR) or hospitalization diagnostic codes.
- Validation of diagnostic codes using a subset of hospitalizations (n=2,540).
Main Results:
- Incident CKD stage 3 identified in 1,172 participants via visit-based definition and 1,078 via hospitalization-based definition.
- Sensitivity of hospitalization-based CKD definition was 35.5% (95% CI, 31.6%-39.7%); specificity was 95.7% (95% CI, 94.2%-96.8%).
- Higher sensitivity observed with later time periods, older age, and prevalent diabetes or CKD.
Conclusions:
- The sensitivity of CKD diagnosis using only hospitalization codes is low but improves with specific patient factors.
- Supplementing visit-based definitions with hospitalization data enhances CKD identification between scheduled study visits.
- This combined approach is valuable for capturing incident disease in longitudinal epidemiologic studies.
Background:
In epidemiologic research, incident chronic kidney disease (CKD) commonly is determined by laboratory tests performed at planned study visits. Given the morbidity and mortality associated with CKD, persons with incident disease may be less likely to attend scheduled visits, affecting observed associations. The objective of this study was to quantify loss to follow-up by CKD status and determine whether supplementation with diagnostic code data improves capture of incident CKD.
Study Design:
Prospective cohort study.
Setting & Participants:
11,560 participants in the Atherosclerosis Risk in Communities (ARIC) Study underwent continuous surveillance for hospitalizations and death from baseline visit (1996-1999) to follow-up visit (2011-2013). A subset of hospitalizations in Washington County, MD, was used in diagnostic code validation (n=2,540).
Predictor:
Baseline demographics and comorbid conditions.
Outcomes:
Incident CKD stage 3 ascertained by follow-up visit (visit-based definition) or hospitalization surveillance (hospitalization-based definition).
Measurements:
Visit-based definition: ≥25% decline from baseline estimated glomerular filtration rate to <60 mL/min/1.73 m2 at follow-up visit; hospitalization-based definition: hospitalization CKD diagnostic code.
Results:
Of 11,560 participants, 5,951 attended the follow-up visit and 9,264 were hospitalized. Never-hospitalized participants were younger, more often female, and had fewer comorbid conditions; 73.5% attended the follow-up visit. Incident CKD stage 3 occurred in 1,172 participants by the visit-based definition (251 were never hospitalized) and 1,078 participants by the hospitalization-based definition (237 attended the follow-up study visit). Sensitivity of the hospitalization-based CKD definition was 35.5% (95% CI, 31.6%-39.7%); specificity was 95.7% (95% CI, 94.2%-96.8%). Sensitivity was higher with later time period, older participant age, and baseline prevalent diabetes and CKD.
Limitations:
A subset of hospitalizations was used for validation; 15-year gap between study visits.
Conclusions:
The sensitivity of diagnostic code-identified CKD is low and varies by certain factors; however, supplementing a visit-based definition with hospitalization information can increase disease identification during periods of follow-up without study visits.
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