Evidence map›Paper›PMID 23797949›Full record

ArticleJournal of inherited metabolic disease2014

Usefulness of biochemical parameters in decision-making on the start of emergency treatment in patients with propionic acidemia.

Tamaris Zwickler, Alina Riderer, Gisela Haege, Georg F Hoffmann, Stefan Kölker, Peter Burgard

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Article in Journal of inherited metabolic disease, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Tamaris Zwickler
Alina Riderer
Gisela Haege
Georg F Hoffmann
Stefan Kölker
Peter Burgard

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecurrent acute and life-threatening metabolic decompensations are thought to be the major cause of mortality and morbidity in patients with propionic acidemia (PA). Since metabolic decompensations in these patients usually develop gradually, there is considerable uncertainty about the beginning and when emergency treatment should be initiated. The major aim of this study was to evaluate the usefulness of biochemical parameters for improving decision-making on the start of emergency treatment.

methodsWe analysed data of 16 PA patients continuously followed in our centre. Metabolic decompensation was defined clinically by the occurrence of at least one of three alarming symptoms: vomiting, food refusal or impaired consciousness. Thirty-eight biochemical parameters were analysed.

resultsA total of 259 metabolic decompensations were documented and compared with 625 routine visits. Among the symptoms used to clinically define metabolic decompensations, vomiting was most frequent (87 %). In total, 19 biochemical parameters differentiated between metabolic decompensations and routine visits. Among them ammonia, acid-base balance and anion gap were most reliable to identify a metabolic decompensation, and to estimate its severity. A comparative analysis of patients with PA and methylmalonic acidemia during metabolic decompensation showed similar results.

conclusionsAmmonia, acid-base balance and anion gap are important biochemical parameters to identify an (impending) metabolic decompensation and to assess its severity in PA patients. The identified biochemical parameters should be integrated in an algorithm for clinical decision-making on emergency treatment and should be tested in a prospective trial.

Indexed as

Decision MakingEmergency TreatmentAcid-Base EquilibriumAdolescentAdultAmino Acid Metabolism, Inborn ErrorsAmmoniaAppetiteChildChild, PreschoolDecision Support TechniquesHumansPropionatesPropionic AcidemiaUnconsciousnessVomitingAmmoniaPropionates

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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.