Evidence map›Paper›PMID 40720441›Full record

Observational studyPloS one2025

Identification of risk factors and development of a predictive model in patients using cefmetazole for international normalized ratio elevation.

Takaya Namiki, Yuta Yokoyama, Motonori Kimura, Shogo Fukuda, Shoji Seyama, Osamu Iketani, Masaru Samura, Haruki Ishikawa, Aya Jibiki, Hitoshi Kawazoe and 6 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in PloS one, 2025. 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

16 authors.

Takaya NamikiDivision of Pharmaceutical Care Sciences, Keio University Graduate School of Pharmaceutical Sciences, Tokyo, Japan.
Yuta YokoyamaDivision of Pharmaceutical Care Sciences, Keio University Graduate School of Pharmaceutical Sciences, Tokyo, Japan.ORCID https://orcid.org/0000-0001-9359-9945
Motonori KimuraDepartment of Pharmacy, Keio University Hospital, Tokyo, Japan.
Shogo FukudaDepartment of Pharmacy, Keio University Hospital, Tokyo, Japan.
Shoji SeyamaDivision of Infectious Diseases and Infection Control, Keio University Hospital, Tokyo, Japan.
Osamu IketaniDivision of Academic Research Support, Keio University Hospital, Tokyo, Japan.
Masaru SamuraDepartment of Pharmacy, Yokohama General Hospital, Kanagawa, Japan.
Haruki IshikawaDepartment of Pharmacy, Keio University Hospital, Tokyo, Japan.
Aya JibikiDivision of Pharmaceutical Care Sciences, Center for Social Pharmacy and Pharmaceutical Care Sciences, Keio University Faculty of Pharmacy, Tokyo, Japan.
Hitoshi KawazoeDivision of Pharmaceutical Care Sciences, Keio University Graduate School of Pharmaceutical Sciences, Tokyo, Japan.
Hisakazu OhtaniDepartment of Pharmacy, Keio University Hospital, Tokyo, Japan.
Naoki HasegawaDepartment of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan.
Kazuaki MatsumotoDivision of Pharmacodynamics, Keio University Faculty of Pharmacy, Tokyo, Japan.
Hideki HashiDepartment of Pharmacy, Tokyo Bay Urayasu Ichikawa Medical Center, Chiba, Japan.
Sayo SuzukiDivision of Pharmaceutical Care Sciences, Keio University Graduate School of Pharmaceutical Sciences, Tokyo, Japan.ORCID https://orcid.org/0000-0003-3094-104X
Tomonori NakamuraDivision of Pharmaceutical Care Sciences, Keio University Graduate School of Pharmaceutical Sciences, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient risk factors related to coagulopathy and bleeding when using cefmetazole (CMZ) have not yet been identified, and no models exist to predict side effects during CMZ treatment. Moreover, reports that examine which patients should be careful when using CMZ to ensure safety are lacking. Our objective was to understand risk factors for elevated international normalized ratio (INR) in patients using CMZ and to develop a predictive model for INR elevation using a risk score to enable safe administration of CMZ. This multicenter, retrospective, and observational study was conducted in Tokyo Bay Urayasu Ichikawa Medical Center and Keio University Hospital using data from patients being treated with CMZ. Patients were classified into INR-elevated or non-INR-elevated groups. Univariate and multivariate analyses were performed to calculate the adjusted odds ratios (aOR) and 95% confidence intervals (CI). The actual probability of an elevated INR and probability of an elevated INR predicted by the regression β coefficients were calculated and classified into four categories according to the risk score. Binomial logistic regression analysis revealed that liver disorder (aOR, 5.65; 95% CI, 1.69-18.91; risk scores, 2), nutritional risk (aOR, 6.32; 95% CI, 3.14-12.74; risk scores, 2), no-diabetes mellitus (aOR, 4.53; 95% CI, 1.34-15.26; risk scores, 2), and warfarin use (aOR, 98.44; 95% CI, 7.05-1375.50; risk scores, 5) were significantly associated with INR elevation. The predicted incidence probabilities of INR elevation were < 5% (low risk), 5- < 30% (medium risk), 30- < 90% (high risk), and ≥ 90% (very high risk). The model validity showed a good fit (AUC, 0.79; 95% CI, 0.73-0.85, P < 0.001). We identified risk factors that contribute to INR elevation and constructed a model to predict INR elevation using the risk score. Using this predictive model enables the appropriate use of CMZ in a safe manner.

Indexed as

Anti-Bacterial AgentsInternational Normalized RatioAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsAnti-Bacterial Agents

Identifiers

PMID40720441
PMCPMC12303349

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.