Evidence map›Paper›PMID 36962763›Full record

ArticlePLOS global public health2022

Implementation of a COVID-19 screening tool in a southern Nigerian tertiary health facility.

Esohe O Ogboghodo, Iriagbonse I Osaigbovo, Darlington E Obaseki, Micah T N Iduitua, Doris Asamah, Emmanuel Oduware, Benson U Okwara

Erratum issuedOpen access · goldFull text read
In one paragraph

Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 39% 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, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Esohe O OgboghodoDepartment of Public Health and Community Medicine, University of Benin Teaching Hospital, Benin City, Edo State, Nigeria.ORCID https://orcid.org/0000-0001-6421-6626
Iriagbonse I OsaigbovoDepartment of Medical Microbiology, University of Benin Teaching Hospital, Benin City, Edo State, Nigeria.ORCID https://orcid.org/0000-0001-8111-0743
Darlington E ObasekiChief Medical Director's Office, University of Benin Teaching Hospital, Benin City, Edo State, Nigeria.ORCID https://orcid.org/0000-0001-8222-1592
Micah T N IduituaAccident and Emergency Department, University of Benin Teaching Hospital, Benin City, Edo State, Nigeria.ORCID https://orcid.org/0000-0003-4095-0484
Doris AsamahDepartment of Nursing Services, University of Benin Teaching Hospital, Benin City, Edo State, Nigeria.
Emmanuel OduwareDepartment of Family Medicine, University of Benin Teaching Hospital, Benin City, Edo State, Nigeria.ORCID https://orcid.org/0000-0002-7315-2393
Benson U OkwaraDepartment of Internal Medicine, University of Benin Teaching Hospital, Benin City, Edo State, Nigeria.ORCID https://orcid.org/0000-0002-9410-2299
University of Benin Teaching Hospital · NG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Screening for coronavirus disease 2019 (COVID-19) in emergency rooms of health facilities during outbreaks prevents nosocomial transmission. However, effective tools adapted for use in African countries are lacking. This study appraised an indigenous screening and triage tool for COVID-19 deployed at the medical emergency room of a Nigerian tertiary facility and determined the predictors of a positive molecular diagnostic test for COVID-19. A cross-sectional study of all patients seen between May and July 2020 at the Accident and Emergency of the University of Benin Teaching Hospital was conducted. Patients with any one of the inputs- presence of COVID-19 symptoms, history of international travel, age 60 years and above, presence of comorbidities and oxygen saturation < 94%- were stratified as high-risk and subjected to molecular testing for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Data was obtained from the screening record book patterned after a modified screening tool for COVID-19, deidentified and entered into IBM-SPSS version 25.0. Binary logistic regression was conducted to determine significant predictors of a positive SARS-CoV-2 test. The level of significance was set at p < 0.05. In total, 1,624 patients were screened. Mean age (standard deviation) was 53.9±18.0 years and 651 (40.1%) were 60 years and above. One or more symptoms of COVID-19 were present in 586 (36.1%) patients. Overall, 1,116 (68.7%) patients were designated high risk and tested for SARS-CoV-2, of which 359 (32.2%) were positive. Additional inputs, besides symptoms, increased COVID-19 detection by 108%. Predictors of a positive test were elderly age [AOR = 1.545 (1.127-2.116)], co-morbidity [AOR = 1.811 (1.296-2.530)] and oxygen saturation [AOR = 3.427 (2.595-4.528)]. This protocol using additional inputs such as oxygen saturation improved upon symptoms-based screening for COVID-19. Models incorporating identified predictors will be invaluable in resource limited settings.

Identifiers

PMID36962763
PMCPMC10021546
OpenAlexW4293150141

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read30
identifiers read4
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.