Evidence map›Paper›PMID 26801317›Full record

ArticleThe AAPS journal2016

Prediction of Human Glomerular Filtration Rate from Preterm Neonates to Adults: Evaluation of Predictive Performance of Several Empirical Models.

Iftekhar Mahmood, Carl-Michael Staschen

Abstract readEvaluation Study
In one paragraph

Article in The AAPS journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. A comparison of different methods for the first-in-pediatric dose selection.Journal of clinical and translational research · 2022
    Article
  5. Article
  6. Article
  7. 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

2 authors.

Iftekhar MahmoodDivision of Hematology Clinical Review Branch, Office of Blood Review & Research (OBRR), Center for Biologic Evaluation and Research, Food & Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993-0002, USA. Iftekhar.mahmood@fda.hhs.gov.
Carl-Michael StaschenDivision of Hematology Clinical Review Branch, Office of Blood Review & Research (OBRR), Center for Biologic Evaluation and Research, Food & Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993-0002, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study was to evaluate the predictive performance of several allometric empirical models (body weight dependent, age dependent, fixed exponent 0.75, a data-dependent single exponent, and maturation models) to predict glomerular filtration rate (GFR) in preterm and term neonates, infants, children, and adults without any renal disease. In this analysis, the models were developed from GFR data obtained from inulin clearance (preterm neonates to adults; n = 93) and the predictive performance of these models were evaluated in 335 subjects (preterm neonates to adults). The primary end point was the prediction of GFR from the empirical allometric models and the comparison of the predicted GFR with measured GFR. A prediction error within ±30% was considered acceptable. Overall, the predictive performance of the four models (BDE, ADE, and two maturation models) for the prediction of mean GFR was good across all age groups but the prediction of GFR in individual healthy subjects especially in neonates and infants was erratic and may be clinically unacceptable.

Indexed as

Empirical ResearchModels, BiologicalAdolescentAdultAge FactorsChildChild, PreschoolFemaleGlomerular Filtration RateHumansInfant, NewbornInfant, PrematureMaleMiddle AgedPredictive Value of TestsallometryGFRpediatrics

Identifiers

PMID26801317
PMCPMC4779094

What OpenQuestion holds

Textmetadata
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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.