Evidence map›Paper›PMID 35547543›Full record

ArticleFrontiers in pediatrics2022

Integrating Clinical Signs at Presentation and Clinician's Non-analytical Reasoning in Prediction Models for Serious Bacterial Infection in Febrile Children Presenting to Emergency Department.

Urzula Nora Urbane, Eva Petrosina, Dace Zavadska, Jana Pavare

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pediatrics, 2022. 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
1.4field-weighted citation impact, top 19% 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, 9 citations in OpenAlex.

  1. Response to: Comment on "Integrating Human Intuition into Prediction Algorithms for Improved Surgical Risk Stratification".Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024
    Article
  2. Comment on: "Integrating Human Intuition into Prediction Algorithms for Improved Surgical Risk Stratification".Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024
    Article
  3. Identifying serious bacterial illness in children: is it time to show the red card to NICE's red flags?The British journal of general practice : the journal of the Royal College of General Practitioners · 2023
    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

4 authors at 2 institutions in 1 country.

Urzula Nora UrbaneDepartment of Pediatrics, Riga Stradins University, Riga, Latvia.
Eva PetrosinaStatistics Unit, Riga Stradins University, Riga, Latvia.
Dace ZavadskaDepartment of Pediatrics, Riga Stradins University, Riga, Latvia.
Jana PavareDepartment of Pediatrics, Riga Stradins University, Riga, Latvia.
Children's Clinical University Hospital · LVRiga Stradiņš University · LV

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Development and validation of clinical prediction model (CPM) for serious bacterial infections (SBIs) in children presenting to the emergency department (ED) with febrile illness, based on clinical variables, clinician's "gut feeling," and "sense of reassurance. Materials and Methods: Febrile children presenting to the ED of Children's Clinical University Hospital (CCUH) between April 1, 2017 and December 31, 2018 were enrolled in a prospective observational study. Data on clinical signs and symptoms at presentation, together with clinician's "gut feeling" of something wrong and "sense of reassurance" were collected as candidate variables for CPM. Variable selection for the CPM was performed using stepwise logistic regression (forward, backward, and bidirectional); Akaike information criterion was used to limit the number of parameters and simplify the model. Bootstrapping was applied for internal validation. For external validation, the model was tested in a separate dataset of patients presenting to six regional hospitals between January 1 and March 31, 2019. Results: The derivation cohort consisted of 517; 54% ( Conclusion: Both CPMs had moderate ability to predict SBI and acceptable performance in the validation cohort. Adding variables "gut feeling" and "sense of reassurance" in CPM2 improved its ability to predict SBI. More validation studies are needed for the assessment of applicability to all febrile patients presenting to ED.

Indexed as

fevergut feelingnon-analytical reasoningprediction modelserious bacterial infection

Identifiers

PMID35547543
PMCPMC9082163
OpenAlexW4224864095

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.