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Record W3114209404 · doi:10.4103/cjrm.cjrm_76_20

Challenges in managing febrile patients in a rural emergency room during the COVID-19 pandemic

2020· article· en· W3114209404 on OpenAlexvenueno aff
Hanna Moon, Jooyoung Moon

Bibliographic record

VenueCanadian Journal of Rural Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsTriagePandemicMedicineCoronavirus disease 2019 (COVID-19)Medical emergencyPresentation (obstetrics)PneumoniaEmergency departmentIntensive care medicineNursingInfectious disease (medical specialty)PathologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Dear Editor, In a recent letter, Schiller and Blau addressed challenges in clinical decision-making amidst the COVID-19 pandemic.[1] The atypical presentation of diseases such as pneumonia certainly adds to the already-difficult problems of diagnostic ambiguities in testing limited environments. This concern can be more broadly applied to all febrile diseases that may or may not be associated with respiratory diseases, especially in hospitals serving medically underserved areas. In such hospitals, there is often a lack of appropriate medical equipment or personnel necessary to properly diagnose and treat a febrile patient. During the current pandemic, it has become necessary to triage, identify and isolate all questionable febrile patients and manage them in a separate, enclosed area until they are tested negative for the coronavirus.[2] However, in a hospital which lacks capabilities, it is nearly impossible to provide quality care in a well-isolated, enclosed setting. In the case of Sungju Moogang Hospital, a 55-bed rural hospital located in Sungju, South Korea, the emergency room has experienced multiple cases of febrile patients who had to be referred to tertiary medical centres due to insufficient means of appropriate testing and management. One such adolescent patient informed us that her fever of 40°C was likely due to another flare of haemophagocytic lymphohistiocytosis, which she had been diagnosed with several years prior. The parents requested a course of immunosuppressants as had been done at a university hospital, but we could not proceed any further because she did not bring any medical certificates and had no pertinent information in our hospital records. In addition, she was a candidate for COVID-19 screening because of a recent travel history, but we did not have the rapid testing equipment at hand. We decided to refer her to a tertiary medical centre where she received the diagnosis and was later informed that she subsequently underwent testing for COVID-19 and received appropriate immunosuppressant therapy to control her symptoms. In other cases where we were able to identify a patient's source of fever as more simple causes such as enterocolitis or pyelonephritis, we provided appropriate treatment within our emergency room. Studies have found that viral respiratory infections such as the coronavirus are associated with many other diseases, many of which are immune related.[3,4] As such, it is imperative that frontline medical workers not get caught up with Bayesian thinking and properly assess all febrile patients for potentially less common aetiologies. The challenges faced by hospitals serving underserved populations are inarguably greater during this pandemic, so great precaution should be taken to avoid missed or late diagnosis for potentially more serious conditions. Financial support and sponsorship: Nil. Conflicts of interest: There are no conflicts of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.300
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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