Evidence map›Paper›PMID 31221885›Full record

ArticleBMJ open2019

A prospective study of consecutive emergency medical admissions to compare a novel automated computer-aided mortality risk score and clinical judgement of patient mortality risk.

Muhammad Faisal, Binish Khatoon, Andy Scally, Donald Richardson, Sally Irwin, Rachel Davidson, David Heseltine, Alison Corlett, Javed Ali, Rebecca Hampson and 5 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMJ open, 2019. 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
0.6field-weighted citation impact, top 30% 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, 6 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

15 authors at 3 institutions in 2 countries.

Muhammad FaisalFaculty of Health Studies, University of Bradford, Bradford, UK.
Binish KhatoonFaculty of Health Studies, University of Bradford, Bradford, UK.
Andy ScallySchool of Clinical Therapies, University College Cork National University of Ireland, Cork, Ireland.
Donald RichardsonRenal Unit, York Teaching Hospital NHS Foundation Trust, York, UK.
Sally IrwinYork Teaching Hospital NHS Foundation Trust, York, UK.
Rachel DavidsonYork Teaching Hospital NHS Foundation Trust, York, UK.
David HeseltineYork Teaching Hospital NHS Foundation Trust, York, UK.
Alison CorlettYork Teaching Hospital NHS Foundation Trust, York, UK.
Javed AliYork Teaching Hospital NHS Foundation Trust, York, UK.
Rebecca HampsonYork Teaching Hospital NHS Foundation Trust, York, UK.
Sandeep KesavanYork Teaching Hospital NHS Foundation Trust, York, UK.
Gerry McGonigalYork Teaching Hospital NHS Foundation Trust, York, UK.
Karen GoodmanYork Teaching Hospital NHS Foundation Trust, York, UK.
Michael HarknessYork Teaching Hospital NHS Foundation Trust, York, UK.
Mohammed MohammedFaculty of Health Studies, University of Bradford, Bradford, UK.
York Teaching Hospital NHS Foundation Trust · GBUniversity of Bradford · GBNational University of Ireland · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo compare the performance of a validated automatic computer-aided risk of mortality (CARM) score versus medical judgement in predicting the risk of in-hospital mortality for patients following emergency medical admission.

designA prospective study.

settingConsecutive emergency medical admissions in York hospital.

participantsElderly medical admissions in one ward were assigned a risk of death at the first post-take ward round by consultant staff over a 2-week period. The consultant medical staff used the same variables to assign a risk of death to the patient as the CARM (age, sex, National Early Warning Score and blood test results) but also had access to the clinical history, examination findings and any immediately available investigations such as ECGs. The performance of the CARM versus consultant medical judgement was compared using the c-statistic and the positive predictive value (PPV).

resultsThe in-hospital mortality was 31.8% (130/409). For patients with complete blood test results, the c-statistic for CARM was 0.75 (95% CI: 0.69 to 0.81) versus 0.72 (95% CI: 0.66 to 0.78) for medical judgements (p=0.28). For patients with at least one missing blood test result, the c-statistics were similar (medical judgements 0.70 (95% CI: 0.60 to 0.81) vs CARM 0.70 (95% CI: 0.59 to 0.80)). At a 10% mortality risk, the PPV for CARM was higher than medical judgements in patients with complete blood test results, 62.0% (95% CI: 51.2 to 71.9) versus 49.2% (95% CI: 39.8 to 58.5) but not when blood test results were missing, 50.0% (95% CI: 24.7 to 75.3) versus 53.3% (95% CI: 34.3 to 71.7).

conclusionsCARM is comparable with medical judgements in discriminating in-hospital mortality following emergency admission to an elderly care ward. CARM may have a promising role in supporting medical judgements in determining the patient's risk of death in hospital. Further evaluation of CARM in routine practice is required.

Indexed as

JudgmentAgedClinical CompetenceClinical Decision-MakingConsultantsDecision Making, Computer-AssistedEmergenciesEmergency Service, HospitalEnglandFemaleHospital MortalityHumansMaleMedical Staff, HospitalPatient AdmissionProspective Studiescomputer-aided risk scoreemergency medical admissionmedical judgementmortality

Identifiers

PMID31221885
PMCPMC6589037
OpenAlexW2949804601

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.