Evidence map›Paper›PMID 40075546›Full record

ArticleJournal of pharmaceutical health care and sciences2025

Development and validation of a population pharmacokinetic model of vancomycin for patients of advanced age.

Keisuke Takada, Masaru Samura, Yuki Igarashi, Ayako Suzuki, Tomoyuki Ishigo, Satoshi Fujii, Yuta Ibe, Hiroaki Yoshida, Hiroaki Tanaka, Fumiya Ebihara and 13 more

Abstract read
In one paragraph

Article in Journal of pharmaceutical health care and sciences, 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

23 authors.

Keisuke TakadaDivision of Pharmacodynamics, Keio University Faculty of Pharmacy, 1-5-30 Shibakoen, Minato-Ku, Tokyo, 105-8512, Japan.
Masaru SamuraDivision of Pharmacodynamics, Keio University Faculty of Pharmacy, 1-5-30 Shibakoen, Minato-Ku, Tokyo, 105-8512, Japan. masaru.samura@gmail.com.
Yuki IgarashiDivision of Pharmacodynamics, Keio University Faculty of Pharmacy, 1-5-30 Shibakoen, Minato-Ku, Tokyo, 105-8512, Japan.
Ayako SuzukiDepartment of Pharmacy, Showa University Fujigaoka Hospital, 1-30 Fujigaoka, Aoba-Ku, Yokohama-Shi, Kanagawa, 227-8501, Japan.
Tomoyuki IshigoDepartment of Pharmacy, Sapporo Medical University Hospital, 291 Nishi 16-Chome, Minami 1-Jo, Chuo-Ku, Sapporo-Shi, Hokkaido, 060-8543, Japan.
Satoshi FujiiDepartment of Pharmacy, Sapporo Medical University Hospital, 291 Nishi 16-Chome, Minami 1-Jo, Chuo-Ku, Sapporo-Shi, Hokkaido, 060-8543, Japan.
Yuta IbeDepartment of Pharmacy, Sapporo Medical University Hospital, 291 Nishi 16-Chome, Minami 1-Jo, Chuo-Ku, Sapporo-Shi, Hokkaido, 060-8543, Japan.
Hiroaki YoshidaDepartment of Pharmacy, Kyorin University Hospital, 6-20-2 Shinkawa, Mitaka-Shi, Tokyo, 181-8611, Japan.
Hiroaki TanakaDepartment of Pharmacy, Kyorin University Hospital, 6-20-2 Shinkawa, Mitaka-Shi, Tokyo, 181-8611, Japan.
Fumiya EbiharaDepartment of Pharmacy, Tokyo Women's Medical University Hospital, 8-1 Kawada-Cho, Shinjuku-Ku, Tokyo, 162-8666, Japan.
Takumi MaruyamaDepartment of Pharmacy, Tokyo Women's Medical University Hospital, 8-1 Kawada-Cho, Shinjuku-Ku, Tokyo, 162-8666, Japan.
Yukihiro HamadaDepartment of Pharmacy, Kochi Medical School Hospital, 185-1 Okochokohasu, Nankoku-Shi, Kochi, 783-8505, Japan.
Toshiaki KomatsuDepartment of Pharmacy, Kitasato University Hospital, 1-15-1 Kitasato, Minami-Ku, Sagamihara-Shi, Kanagawa, 252-0375, Japan.
Atsushi TomizawaDepartment of Pharmacy, Kitasato University Hospital, 1-15-1 Kitasato, Minami-Ku, Sagamihara-Shi, Kanagawa, 252-0375, Japan.
Akitoshi TakumaDepartment of Pharmacy, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-Chuo, Tsuzuki-Ku, Yokohama-Shi, Kanagawa, 224-0032, Japan.
Hiroaki ChibaDepartment of Pharmacy, Tohoku Kosai Hospital, 2-3-11 Kokubuncho, Aoba-Ku, Sendai-Shi, Miyagi, 980-0803, Japan.
Yusuke YagiDepartment of Pharmacy, Kochi Medical School Hospital, 185-1 Okochokohasu, Nankoku-Shi, Kochi, 783-8505, Japan.
Yoshifumi NishiCenter for Pharmacist Education, School of Pharmacy, Nihon University, 7-7-1 Narashinodai, Funabashi-Shi, Chiba, 274-0063, Japan.
Yuki EnokiDivision of Pharmacodynamics, Keio University Faculty of Pharmacy, 1-5-30 Shibakoen, Minato-Ku, Tokyo, 105-8512, Japan.
Kazuaki TaguchiDivision of Pharmacodynamics, Keio University Faculty of Pharmacy, 1-5-30 Shibakoen, Minato-Ku, Tokyo, 105-8512, Japan.
Koji TanikawaDepartment of Pharmacy, Yokohama General Hospital, 2201-5 Kuroganecho, Aoba-Ku, Yokohama City, Kanagawa, 225-0025, Japan.
Hiroyuki KunishimaDepartment of Infectious Diseases, St. Marianna University School of Medicine Hospital, 2-16-1 Sugao, Miyamae-Ku, Kawasaki City, Kanagawa, 216-8511, Japan.
Kazuaki MatsumotoDivision of Pharmacodynamics, Keio University Faculty of Pharmacy, 1-5-30 Shibakoen, Minato-Ku, Tokyo, 105-8512, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPopulation pharmacokinetic (PPK) models of vancomycin (VCM) commonly use creatinine clearance (CLcr) as a covariate for clearance (CL). However, relying on CLcr in patients of advanced age may lead to inaccuracies in estimating VCM clearance. Therefore, this study aimed to develop and validate a new PPK model specifically for patients aged 75 years and older.

methodsPPK analysis was performed based on the blood concentrations of VCM (n = 159 patients). The predictive performance of the developed model was compared with that of previous models using mean absolute error (MAE) and mean squared error (MSE) for another dataset.

resultsThe PPK analysis optimized a two-compartment model using CLcr and the Alb levels as covariates at the central compartment of VCM clearance. The final model was as follows: CL (L/h) = 1.96 × (CLcr/3.09)

conclusionThe PPK model of VCM for patients of advanced age was optimized by adding the Alb levels and CLcr as covariates for CL. The predictive accuracy of the PPK model for patients with an SCr of < 0.6 mg/dL tended to be higher than those of previous models based just on CLcr. Thus, dosage is suggested to be adjusted based on CLcr and Alb levels for patients with an SCr of < 0.6 mg/dL.

Indexed as

Patients of advanced agePopulation pharmacokineticsSerum albuminVancomycin

Identifiers

PMID40075546
PMCPMC11900651

What Socratic holds

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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 Socratic graph.