Evidence map›Paper›PMID 29953028›Full record

Observational studyMedicine2018

An assessment of a pediatric early warning system score in severe hand-foot-and-mouth disease children: To detect clinical deterioration in hospitalized children.

Lu Mei, Xin Song, Yan Kong, Guiling Yu

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 31% 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, 3 citations in OpenAlex.

  1. Article
  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

4 authors at 2 institutions in 1 country.

Lu MeiQingdao Women and Children's Hospital Qingdao Municipal Center For Disease Control and Prevention Qingdao Institute of Preventive Medicine, Qingdao, P.R. China.
Xin Song
Yan Kong
Guiling Yu
Qingdao University · CNQingdao Municipal Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of deteriorating severe hand, foot, and mouth disease (HFMD) children for referral to intensive care remains problematic.The medical records of 2382 hospitalized children with severe HFMD from May 2013 to September 2015 were retrospectively reviewed. A Pediatric Early Warning System (PEWS) score was designed based on study parameters on admission, evaluated in a logistic regression model, and subsequently validated with different cut-off scores, to predict the risk for clinical deterioration.After admission, 191 cases were transferred to the pediatric intensive care unit (PICU) and 2191 were admitted to the infectious disease department. Of which, 116 cases were subsequently transferred to PICU, with younger age, consciousness levels of sluggishness, lethargy or drowsiness, rashes with vesicles on the hands or feet, moderate or high fever, increased or disordered lung marking or pulmonary infiltration, abnormal heart rate, fasting plasma glucose, blood platelet, and C-reactive protein. A corresponding 10-component PEWS score >7 was significantly associated with subsequent transfer to PICU.A 10-component PEWS score >7 has good specificity but poor sensitivity for identifying severe HFMD children vulnerable to clinical deterioration.

Indexed as

Child, HospitalizedClinical DeteriorationIntensive Care Units, PediatricSeverity of Illness IndexAdolescentAge FactorsAlgorithmsAnimalsBlood GlucoseChildChild, PreschoolConsciousnessC-Reactive ProteinFemaleFoot-and-Mouth DiseaseHeart RateBlood GlucoseC-Reactive Protein

Identifiers

PMID29953028
PMCPMC6039599
OpenAlexW2811269854

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.