Evidence map›Paper›PMID 33183252›Full record

ArticleBMC infectious diseases2020

Period prevalence and identification challenges of viral haemorrhagic fever suspect cases in a tertiary referral hospital in Guinea: a cross-sectional, retrospective study of triage and emergency room patient profiles.

Manuel Raab, Lisa M Pfadenhauer, Vinh-Kim Nguyen, Dansira Doumbouya, Michael Hoelscher, Guenter Froeschl

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.1field-weighted citation impact, top 41% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

6 authors at 4 institutions in 3 countries.

Manuel RaabDivision of Infectious Diseases and Tropical Medicine, University Hospital (LMU), Leopoldstr. 5, 80802, Munich, Germany. manuel.j.raab@gmail.com.ORCID http://orcid.org/0000-0002-4247-9588
Lisa M PfadenhauerInstitute of Medical Informatics, Biometry and Epidemiology, Pettenkofer School of Public Health, Ludwig Maximilian University Munich, Marchioninistr, 15, 81377, Munich, Germany.
Vinh-Kim NguyenDepartment of Anthropology and Sociology, The Graduate Institute (IHEID), Rue Eugene-Rigot 2, Case postale 1672, 1211, Geneva 1, Switzerland.
Dansira DoumbouyaPaediatric Service, Hôpital Régional de N'zérékoré, Nzérékoré, Guinea.
Michael HoelscherDivision of Infectious Diseases and Tropical Medicine, University Hospital (LMU), Leopoldstr. 5, 80802, Munich, Germany.
Guenter FroeschlDivision of Infectious Diseases and Tropical Medicine, University Hospital (LMU), Leopoldstr. 5, 80802, Munich, Germany.
LMU Klinikum · DEGraduate Institute of International and Development Studies · CHHôpital régional · CHLudwig-Maximilians-Universität München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA functioning Viral Haemorrhagic Fever (VHF) surveillance system in countries at risk for outbreaks can reduce early transmission in case of an outbreak. Surveillance performance depends on the application of suspect case definitions in daily clinical practice. Recommended suspect case criteria during outbreaks are designed for high sensitivity and include general symptoms, pyrexia, haemorrhage, epidemiological link and unexplained death in patients. Non-outbreak criteria are narrower, relying on the persistence of fever and the presence of haemorrhagic signs.

methodsThis study ascertains VHF suspect case prevalence based on outbreak and non-outbreak criteria in a Guinean regional hospital for a period of three months. The study further describes clinical trajectories of patients who meet non-outbreak VHF suspect case criteria in order to discuss challenges in their identification. We used cross-sectional data collection at triage and emergency room to record demographic and clinical data of all admitted patients during the study period. For the follow-up study with description of diagnostic trajectories of VHF suspect cases, we used retrospective chart review.

resultsThe most common symptoms of all patients upon admission were fever, tiredness/weakness and abdominal pain. 686 patients met EVD outbreak criteria, ten adult patients and two paediatric patients met study-specific non-outbreak VHF suspect case criteria. None of the suspect cases was treated as VHF suspect case and none tested positive for malaria upon admission. Their most frequent discharge diagnosis was unspecific gastrointestinal infection. The most common diagnostic measures were haemoglobin level and glycaemia for both adults and for children; of the requested examinations for hospitalized suspect cases, 36% were not executed or obtained. Half of those patients self-discharged against medical advice.

conclusionsOur study shows that the number of VHF suspect cases may vary greatly depending on which suspect case criteria are applied. Identification of VHF suspect cases seems challenging in clinical practice. We suggest that this may be due to the low use of laboratory diagnostics to support certain diagnoses and the non-application of VHF suspect case definitions in clinical practice. Future VHF suspect case management should aim to tackle such challenges in comparable hospital settings.

Indexed as

Disease OutbreaksEmergency Service, HospitalTertiary Care CentersAdolescentAdultChildChild, PreschoolCross-Sectional StudiesEbolavirusFemaleFeverFollow-Up StudiesGuineaHemorrhagic Fever, EbolaHumansInfantEbolaGuineaInfection prevention and controlScreeningTertiary hospitalViral Haemorrhagic feverWest Africa

Identifiers

PMID33183252
PMCPMC7663860
OpenAlexW3103583082

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.