Evidence map›Paper›PMID 36645795›Full record

ArticleBMJ paediatrics open2022

Prediction models for SIRS, sepsis and associated organ dysfunctions in paediatric intensive care: study protocol for a diagnostic test accuracy study.

Julia Böhnke, Nicole Rübsamen, Marcel Mast, Henning Rathert, ELISE Study Group, André Karch, Thomas Jack, Antje Wulff

Open access · diamondAbstract read
In one paragraph

Article in BMJ paediatrics open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 47% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Pooled it
  2. 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

8 authors at 3 institutions in 3 countries.

Julia Böhnke *Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany boehnkej@uni-muenster.de.ORCID 0000-0003-1249-4581
Nicole Rübsamen *Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.ORCID 0000-0003-2198-5577
Marcel MastPeter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Hannover, Germany.ORCID 0000-0001-6478-2230
Henning RathertDepartment of Pediatric Cardiology and Intensive Care Medicine, Hannover Medical School, Hannover, Germany.ORCID 0000-0001-9610-0257
ELISE Study Group
André KarchInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.ORCID 0000-0003-3014-8543
Thomas Jack *Department of Pediatric Cardiology and Intensive Care Medicine, Hannover Medical School, Hannover, Germany.ORCID 0000-0003-0576-327X
Antje Wulff *Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Hannover, Germany.ORCID 0000-0002-2550-2627
University of Münster · DECarl von Ossietzky Universität Oldenburg · DEMedizinische Hochschule Hannover · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSystemic inflammatory response syndrome (SIRS), sepsis and associated organ dysfunctions are life-threating conditions occurring at paediatric intensive care units (PICUs). Early recognition and treatment within the first hours of onset are critical. However, time pressure, lack of personnel resources, and the need for complex age-dependent diagnoses impede an accurate and timely diagnosis by PICU physicians. Data-driven prediction models integrated in clinical decision support systems (CDSS) could facilitate early recognition of disease onset.

objectivesTo estimate the sensitivity and specificity of previously developed prediction models (index tests) for the detection of SIRS, sepsis and associated organ dysfunctions in critically ill children up to 12 hours before reference standard diagnosis is possible. METHODS AND ANALYSIS: We conduct a monocentre, prospective diagnostic test accuracy study. Clinicians in the PICU of the tertiary care centre Hannover Medical School, Germany, continuously screen and recruit patients until the adaptive sample size (originally intended sample size of 500 patients) is enrolled. Eligible are children (0-17 years, all sexes) who stay in the PICU for ≥12 hours and for whom an informed consent is given. All eligible patients are independently assessed for SIRS, sepsis and organ dysfunctions using corresponding predictive and knowledge-based CDSS models. The knowledge-based CDSS models serve as imperfect reference standards. The assessments are used to estimate the sensitivities and specificities of each predictive model using a clustered nonparametric approach (main analysis). Subgroup analyses ('age groups', 'sex' and 'age groups by sex') are predefined. ETHICS AND DISSEMINATION: This study obtained ethics approval from the Hannover Medical School Ethics Committee (No. 10188_BO_SK_2022). Results will be disseminated as peer-reviewed publications, at scientific conferences, and to patients in an appropriate dissemination approach. TRIAL REGISTRATION NUMBER: This study was registered with the German Clinical Trial Register (DRKS00029071) on 2022-05-23. PROTOCOL VERSION: 10188_BO_SK_2022_V.2.0-20220330_4_Studienprotokoll.

Indexed as

SepsisSystemic Inflammatory Response SyndromeChildCritical CareDiagnostic Tests, RoutineHumansMultiple Organ FailureProspective StudiesAdolescent HealthInformation TechnologyTechnology

Identifiers

PMID36645795
PMCPMC9621157
OpenAlexW4307639577

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.