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Record W4310945043 · doi:10.2196/36023

Clinical Outcomes After Use of Inhaled Corticosteroids or Oral Steroids in a COVID-19 Telemedicine Clinic Cohort: Retrospective Chart Review

2022· article· en· W4310945043 on OpenAlexvenueno aff
Michele Cellai, Jodi Roberts, Miranda A. Moore, Nikhila Gandrakota

Bibliographic record

VenueJMIR Formative Research · 2022
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
FundersEmory University
KeywordsMedicineReferralRetrospective cohort studyTelemedicineEmergency medicineMedical recordAdverse effectPopulationVeterans AffairsAsthmaCoronavirus disease 2019 (COVID-19)CohortPediatricsHealth careIntensive care medicineInternal medicineFamily medicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: COVID-19 concerns remain among health care providers, as there are few outpatient treatment options. In the early days of the pandemic, treatment options for nonhospitalized patients were limited, and symptomatic treatment and home-grown guidelines that used recommendations from the Global Initiative for Asthma Management and Treatment were used. OBJECTIVE: The possibility that inhaled corticosteroids (ICS) might reduce the risk of respiratory symptoms and promote recovery was the impetus for this review, as it has already been shown that in the nonhospitalized patient population, oral corticosteroids (OCS) in the acute phase could have an adverse effect on recovery. We investigated if (1) patients treated with ICS were less likely to require referral to a post-COVID-19 clinic or pulmonary specialist than patients without ICS treatment or with OCS therapy, and (2) if OCS use was associated with worse health outcomes. METHODS: In a retrospective chart review, we identified all patients with acute illness due to COVID-19 that were followed and managed by a telemedicine clinic team between June and December 2020. The data were electronically pulled from electronic medical records through April 2021 and reviewed to determine which patients eventually required referral to a post-COVID-19 clinic or pulmonary specialist due to persistent respiratory symptoms of COVID-19. The data were then analyzed to compare outcomes between patients prescribed OCS and those prescribed ICS. We specifically looked at patients treated acutely with ICS or OCS that then required referral to a pulmonary specialist or post-COVID-19 clinic. We excluded any patients with a history of chronic OCS or ICS use for any reason. RESULTS: Prescribing ICS during the acute phase did not reduce the possibility of developing persistent symptoms. There was no difference in the referral rate to a pulmonary specialist or post-COVID-19 clinic between patients treated with OCS versus ICS. However, our data may not be generalizable to other populations, as it represents a patient population enrolled in a telemedicine program at a single center. CONCLUSIONS: We found that ICS, as compared to OCS, did not reduce the risk of developing persistent respiratory symptoms. This finding adds to the body of knowledge that ICS and OCS medications remain potent treatments in patients with acute and postacute COVID-19 seen in an outpatient setting.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.130
GPT teacher head0.508
Teacher spread0.378 · 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 source (direct Gemma or distilled Codex), 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
Published2022
Admission routes1
Has abstractyes

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