Evidence map›Paper›PMID 38799784›Full record

ArticleKidney medicine2024

Cystatin C Use for CKD Detection in the Veterans Health Administration System: A Qualitative Study of Barriers and Facilitators.

Julio A Lamprea-Montealegre, Abigail Shapiro, Natalie A B Bontrager, Dena E Rifkin, Simerjot K Jassal, Lucile Parker Gregg, Sankar D Navaneethan, Krista Navarra, Michael G Shlipak, Michelle M Estrella and 1 more

Abstract read
In one paragraph

Article in Kidney medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Julio A Lamprea-MontealegreDepartment of Medicine, University of California, San Francisco, CA.
Abigail ShapiroDurham VA Health Care System, Durham, NC.
Natalie A B BontragerCenter of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System, Durham, NC.
Dena E RifkinUniversity of California, San Diego, La Jolla, CA.
Simerjot K JassalUniversity of California, San Diego, La Jolla, CA.
Lucile Parker GreggBaylor College of Medicine, Michael E. DeBakey VA Medical Center, Houston, TX.
Sankar D NavaneethanBaylor College of Medicine, Michael E. DeBakey VA Medical Center, Houston, TX.
Krista NavarraDepartment of Medicine, University of California, San Francisco, CA.
Michael G ShlipakDepartment of Medicine, University of California, San Francisco, CA.
Michelle M EstrellaDepartment of Medicine, University of California, San Francisco, CA.
Virginia WangDurham VA Health Care System, Durham, NC.

Funding

Closing the Cardio-Renal Preventive Treatment Gap Among Patients with Type 2 Diabetes Mellitus and Chronic Kidney Disease: An Implementation Science ApproachR00HL157721 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Julio Alejandro Lamprea Montealegre · 2024 to 2026
$732k
Closing the Cardio-Renal Preventive Treatment Gap Among Patients with Type 2 Diabetes Mellitus and Chronic Kidney Disease: An Implementation Science ApproachK99HL157721 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LAMPREA MONTEALEGRE, JULIO ALEJANDRO · 2022 to 2023
$296k
Association of diuretics with change in extracellular volume, natriuretic peptides, symptoms, and cardiovascular outcomes in CKDIK2CX002368 · VA · MICHAEL E DEBAKEY VA MEDICAL CENTER · PI Lucile Parker Gregg · 2022 to 2027
–
CSRD VA IK2 CX002368NHLBI NIH HHS K99 HL157721NHLBI NIH HHS R00 HL157721
6 · The paper itself

Abstract

Rationale & Objective: The measurement of cystatin C has been recommended to enhance chronic kidney disease (CKD) detection and risk stratification in clinical practice. This study gathered insights into the perceptions and experiences of clinical staff regarding the use of cystatin C in CKD detection within the Veterans Health Administration (VHA) system. Study Design: A qualitative approach was employed to explore barriers and facilitators of clinical staff regarding the use of cystatin C in CKD detection within the VHA system. The Organizational Theory of Implementation Effectiveness informed the development of a semistructured interview guide. Setting & Participants: Health care providers, nurses, and clinical pharmacists from the VHA systems in San Francisco, San Diego, and Houston were interviewed between October 2021 and May 2022. Exposures: Participants' experiences with cystatin C testing. Outcomes: Perceived barriers and facilitators to cystatin C testing. Analytical Approach: Participant responses from individual interviews were analyzed by a multidisciplinary team using rapid qualitative analysis methods. Results: Fourteen in-depth interviews were conducted across the 3 VHA systems. Ten of 11 providers worked in primary care. Five key barriers to using cystatin C for CKD detection were identified. These included lack of patient awareness of CKD testing, lack of provider awareness about cystatin C, knowledge barriers about cystatin C testing, unclear roles and ownership of CKD detection, and lack of clinic support to enhance CKD detection. Suggested interventions to overcome these barriers included educational and training programs, improved clinic workflows, and electronic health record aids to support CKD detection and use of cystatin C. Limitations: The results may not be generalizable to other health care systems outside the VHA. Conclusions: The findings indicate a need for targeted interventions such as educational and training programs, improved clinical workflows, and electronic health record aids to address barriers limiting the use of cystatin C in clinical practice for enhanced CKD detection.

Indexed as

CKD detectioncystatin CVHA system

Identifiers

PMID38799784
PMCPMC11127258

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.