Evidence map›Paper›PMID 35982411›Full record

ArticleBMC nephrology2022

Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate.

Reyhaneh Zafarnejad, Steven Dumbauld, Diane Dumbauld, Mohammad Adibuzzaman, Paul Griffin, Edwin Rutsky

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Reyhaneh ZafarnejadDepartment of Industrial Engineering, Penn State University, 310 Leonhard Bldg., University Park, PA, 16803, USA.
Steven DumbauldRegenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, IN, USA.
Diane DumbauldGood Samaritan Hospital FHC, Cincinnati, OH, USA.
Mohammad AdibuzzamanDepartment of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University, Portland, OR, USA.
Paul GriffinDepartment of Industrial Engineering, Penn State University, 310 Leonhard Bldg., University Park, PA, 16803, USA. pmg14@psu.edu.
Edwin RutskyDivision of Nephrology, University of Alabama at Birmingham, Birmingham, AL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe electronic health record (EHR), utilized to apply statistical methodology, assists provider decision-making, including during the care of chronic kidney disease (CKD) patients. When estimated glomerular filtration (eGFR) decreases, the rate of that change adds meaning to a patient's single eGFR and may represent severity of renal injury. Since the cumulative sum chart technique (CUSUM), often used in quality control and surveillance, continuously checks for change in a series of measurements, we selected this statistical tool to detect clinically relevant eGFR decreases and developed CUSUM

methodsIn a retrospective analysis we applied an age adjusted CUSUM

resultsSignaling occurred by CUSUM

conclusionsCUSUM

Indexed as

Kidney Failure, ChronicRenal Insufficiency, ChronicDisease ProgressionGlomerular Filtration RateHumansKidneyRetrospective StudiesChronic Kidney Disease (CKD)CUSUM chartEarly detectionElectronic Health Record (EHR)End Stage Kidney Disease (ESKD)

Identifiers

PMID35982411
PMCPMC9389810

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Registered trials

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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.