Evidence map›Paper›PMID 39762534›Full record

ArticleClinical and experimental nephrology2025

Development and validation of an algorithm for identifying patients undergoing dialysis from patients with advanced chronic kidney disease.

Takahiro Imaizumi, Takashi Yokota, Kouta Funakoshi, Kazushi Yasuda, Akiko Hattori, Akemi Morohashi, Tatsumi Kusakabe, Masumi Shojima, Sayoko Nagamine, Toshiaki Nakano and 13 more

Abstract readValidation StudyMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical and experimental nephrology, 2025. 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

23 authors.

Takahiro ImaizumiDepartment of Nephrology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 464-8550, Japan.
Takashi YokotaInstitute of Health Science Innovation for Medical Care, Hokkaido University Hospital, Sapporo, Japan.
Kouta FunakoshiKyusyu University Hospital, Fukuoka, Japan.
Kazushi YasudaDepartment of Nephrology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 464-8550, Japan.
Akiko HattoriDepartment of Nephrology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 464-8550, Japan.
Akemi MorohashiDepartment of Advanced Medicine, Nagoya University Hospital, Nagoya, Japan.
Tatsumi KusakabeInstitute of Health Science Innovation for Medical Care, Hokkaido University Hospital, Sapporo, Japan.
Masumi ShojimaDepartment of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Sayoko NagamineDepartment of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Toshiaki NakanoDepartment of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Yong HuangDivision of Medical Informatics, Okayama University Hospital, Okayama, Japan.
Hiroshi MorinagaDepartment of Comprehensive Therapy for Chronic Kidney Disease, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
Miki OhtaClinical Research Promotion Center, The University of Tokyo Hospital, Tokyo, Japan.
Satomi NagashimaDepartment of Healthcare Information Management, The University of Tokyo Hospital, Tokyo, Japan.
Ryusuke InoueMedical Information Technology Center, Tohoku University Hospital, Sendai, Japan.
Naoki NakamuraMedical Information Technology Center, Tohoku University Hospital, Sendai, Japan.
Hideki OtaMedical Information Technology Center, Tohoku University Hospital, Sendai, Japan.
Tatsuya MaruyamaClinical Research Promotion Center, The University of Tokyo Hospital, Tokyo, Japan.
Hideo GobaraDivision of Medical Informatics, Okayama University Hospital, Okayama, Japan.
Akira EndohDepartment of Medical Informatics, Hokkaido University Hospital, Sapporo, Japan.
Masahiko AndoDepartment of Nephrology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 464-8550, Japan.
Yoshimune ShiratoriMedical IT Center, Nagoya University Hospital, Nagoya, Japan.
Shoichi MaruyamaDepartment of Nephrology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 464-8550, Japan. marus@med.nagoya-u.ac.jp.ORCID http://orcid.org/0000-0002-8858-632X

Funding

Japan Agency for Medical Research and Development JP17lk1503001Japan Agency for Medical Research and Development JP17lk1503005Japan Agency for Medical Research and Development JP17lk1503006Japan Agency for Medical Research and Development JP17lk1503010Japan Agency for Medical Research and Development JP18lk1503007Japan Agency for Medical Research and Development JP18lk1503012
6 · The paper itself

Abstract

backgroundIdentifying patients on dialysis among those with an estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m

methodsWe collected clinical data of patients with an eGFR < 15 mL/min/1.73 m

resultsWe collected data from 1142 patients, with 640 (56%) currently undergoing hemodialysis or peritoneal dialysis (PD), including 426 of 763 patients in the derivation cohort and 214 of 379 patients in the validation cohort. The prescription of PD solutions perfectly identified patients undergoing dialysis. After excluding patients prescribed PD solutions, seven laboratory parameters were included in the algorithm. The areas under the receiver operation characteristic curve were 0.95 and 0.98 and the positive and negative predictive values were 90.9% and 91.4% in the derivation cohort and 96.2% and 94.6% in the validation cohort, respectively. The calibrations were almost linear.

conclusionsWe identified patients on dialysis among those with an eGFR < 15 ml/min/1.73 m

Indexed as

AlgorithmsKidneyRenal DialysisRenal Insufficiency, ChronicAgedElectronic Health RecordsFemaleGlomerular Filtration RateHumansJapanMaleMiddle AgedPeritoneal DialysisPredictive Value of TestsReproducibility of ResultsRetrospective StudiesAlgorithmChronic kidney diseaseClassificationDialysis

Identifiers

PMID39762534
PMCPMC12049401

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.