Evidence map›Paper›PMID 28514310›Full record

Observational studyMedicine2017

Development and validation of a mortality risk model for pediatric sepsis.

Mengshi Chen, Xiulan Lu, Li Hu, Pingping Liu, Wenjiao Zhao, Haipeng Yan, Liang Tang, Yimin Zhu, Zhenghui Xiao, Lizhang Chen and 1 more

Abstract readObservational StudyValidation Study
In one paragraph

Observational study in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 3 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

11 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Guideline
  4. Article
  5. Article
  6. Review
  7. Article
  8. Presepsin: Hope in the Quest for the Holy Grail.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2022
    Article
  9. Observational
  10. Article
  11. Observational
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

11 authors.

Mengshi ChenHunan Children's Hospital, Ziyuan RD Department of Epidemiology and Health Statistics, School of Public Health, Central South University, Changsha, Hunan Beijing Center for Diseases Prevention and Control, Beijing, P. R. China.
Xiulan Lu
Li Hu
Pingping Liu
Wenjiao Zhao
Haipeng Yan
Liang Tang
Yimin Zhu
Zhenghui Xiao
Lizhang Chen
Hongzhuan Tan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial.We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities.According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively.The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients.

Indexed as

Risk AssessmentAdolescentArea Under CurveBiomarkersChildChild, PreschoolElectronic Health RecordsFemaleHumansInfantLogistic ModelsMaleMultivariate AnalysisRespiration, ArtificialSepsisBiomarkers

Identifiers

PMID28514310
PMCPMC5440147

What OpenQuestion holds

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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.