Evidence map›Paper›PMID 26239468›Full record

ArticleJournal of clinical medicine2015

Pattern of Investigation Reflects Risk Profile in Emergency Medical Admissions.

Seán Cournane, Declan Byrne, Deirdre O'Riordan, Niall Sheehy, Bernard Silke

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

5 authors.

Seán CournaneDepartment of Medical Physics and Bioengineering, St James's Hospital, Dublin 8, Ireland. scournane@stjames.ie.
Declan ByrneDepartment of Internal Medicine, St James's Hospital, Dublin 8, Ireland. declangbyrne@gmail.com.
Deirdre O'RiordanDepartment of Internal Medicine, St James's Hospital, Dublin 8, Ireland. doriordan@stjames.ie.
Niall SheehyDiagnostic Imaging Department, St. James's Hospital, Dublin 8, Ireland. nsheehy@stjames.ie.
Bernard SilkeDepartment of Internal Medicine, St James's Hospital, Dublin 8, Ireland. bernardsilke@physicians.ie.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Demand for hospital resources may increase over time; we have examined all emergency admissions (51,136 episodes) from 2005 to 2013 for underlying trends and whether resource utilization and clinical risk are correlated. We used logistic regression of the resource indicator against 30-day in-hospital mortality and adjusted this risk estimate for other outcome predictors. Generally, resource indicators predicted an increased risk of a 30-day in-hospital death. For CT Brain the Odds Ratio (OR) was 1.37 (95% CI: 1.27, 1.50), CT Abdomen 3.48 (95% CI: 3.02, 4.02) and CT Chest, Thorax, Abdomen and Pelvis 2.50 (95% CI: 2.10, 2.97). Services allied to medicine including Physiotherapy 2.57 (95% CI: 2.35, 2.81), Dietetics 2.53 (95% CI: 2.27, 2.82), Speech and Language 5.29 (95% CI: 4.57, 6.05), Occupational Therapy 2.65 (95% CI: 2.38, 2.94) and Social Work 1.65 (95% CI: 1.48, 1.83) all predicted an increased risk. The in-hospital 30-day mortality increased with resource utilization, from 4.7% (none) to 27.0% (five resources). In acute medical illness, the use of radiological investigations and allied professionals increased over time. Resource utilization was calibrated from case complexity/30-day in-hospital mortality suggesting that complexity determined the need for and validated the use of these resources.

Indexed as

emergency medical admissionsin-hospital mortalityresource utilization

Identifiers

PMID26239468
PMCPMC4470220

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.