Evidence map›Paper›PMID 33668911›Full record

ReviewPharmaceutics2021

What is the Best Predictor of Phenobarbital Pharmacokinetics to Use for Initial Dosing in Neonates?

Martin Šíma, Danica Michaličková, Ondřej Slanař

Open access · goldAbstract readReview
In one paragraph

Review in Pharmaceutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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, 6 citations in OpenAlex.

  1. A Review of Neonatal Selective Serotonin Reuptake Inhibitor Withdrawal Syndrome.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2025
    Article
  2. Article
  3. Review
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 at 1 institution in 1 country.

Martin ŠímaDepartment of Pharmacology, First Faculty of Medicine, Charles University, 110 00 Prague, Czech Republic.ORCID 0000-0002-6541-738X
Danica MichaličkováDepartment of Pharmacology, First Faculty of Medicine, Charles University, 110 00 Prague, Czech Republic.
Ondřej SlanařDepartment of Pharmacology, First Faculty of Medicine, Charles University, 110 00 Prague, Czech Republic.
Charles University · CZ

Funding

Univerzita Karlova v Praze Progres Q25
6 · The paper itself

Abstract

Phenobarbital is a first-line treatment of various seizure types in newborns. Dosage individualization maximizing the proportion of patients with drug levels in therapeutic range or sufficient treatment response is still challenging. The aim of this review was to summarize the available evidence on phenobarbital pharmacokinetics in neonates and to identify its possible covariates suitable for individualization of initial drug dosing. Several covariates have been considered: body weight and height, body surface area, gestational and postnatal age, laboratory parameters of renal and hepatic functions, asphyxia, therapeutic hypothermia, extracorporeal membrane oxygenation (ECMO), drug interactions, and genetic polymorphisms. The most frequently studied and well-founded covariate for the estimation of phenobarbital dosing is actual body weight. Loading dose of 15-20 mg/kg followed by a maintenance dose of 3-5 mg/kg/day seems to be accurate. However, the evidence for the other covariates with respect to dosing individualization is not sufficient. Doses at the lower limit of suggested range should be preferred in patients with severe asphyxia, while the upper limit of the range should be targeted in neonates receiving ECMO support.

Indexed as

asphyxiadosingneonatespharmacokineticsphenobarbital

Identifiers

PMID33668911
PMCPMC7996486
OpenAlexW3130462379

What OpenQuestion 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 OpenQuestion graph.