Evidence map›Paper›PMID 32133326›Full record

ArticleTranslational and clinical pharmacology2017

Relationship between body weight and postmenstrual age in a Korean pediatric population.

Jinju Guk, Dongwoo Chae, Kyungsoo Park

Abstract read
In one paragraph

Article in Translational and clinical pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

3 authors.

Jinju GukDepartment of Pharmacology, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea.
Dongwoo ChaeDepartment of Pharmacology, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea.
Kyungsoo ParkDepartment of Pharmacology, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Weight is a covariate representative of body size and is known to influence drug disposition. Recently, with increased use of allometric scaling, this variable has become more significant in accounting for variability in pharmacokinetic parameters. In adults, weight can be considered as a time invariant covariate because physical development is complete. As a result, when weight is missing in data, the typical or median value (say, 70 kg) could be imputed. On the contrary, weight continuously changes with age in the pediatric population. In this case, it is more appropriate to consider different median weight for each age group. We constructed a prediction model for weight using postmenstrual age (PMA) with the data consisting of 83,014 Korean pediatric patients. Weight, PMA, and gender information were collected from electronic medical records. Sigmoid models multiplied by exponential or logistic function were tested for basic model structure. Covariate effects on model parameters were then investigated using selection criteria of p < 0.001. All analyses were performed using NONMEM 7.3.0 and R3.2.0. The sigmoid model multiplied by logistic function best described the data and there was a significant difference between boys and girls in model parameters. It is expected that the results obtained in this work can be used for imputation of missing weights in pediatrics when PMA is available. In addition, the developed model can be used for clinical studies in children under 12 years old whose weight change rapidly with age and for model building in dealing with time varying body weight as a covariate.

Indexed as

Body weightPediatric populationPostmenstrual agePrediction model

Identifiers

PMID32133326
PMCPMC7042011

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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.