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Record W4311732856 · doi:10.1093/ofid/ofac492.1287

1460. Respiratory Syncytial Virus (RSV)-Related Clinical Events among a Medicare-Insured Population in the United States

2022· article· en· W4311732856 on OpenAlexaff
Jessica K. DeMartino, Marie‐Hélène Lafeuille, Bruno Émond, Carmine Rossi, Jingru Wang, Stephanie Liu, Patrick Lefèbvre, Girishanthy Krishnarajah

Bibliographic record

VenueOpen Forum Infectious Diseases · 2022
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsMedicinePneumoniaInternal medicineAsthmaHeart failureCOPDBronchiolitisPopulationPediatricsRespiratory system

Abstract

fetched live from OpenAlex

Abstract Background RSV is a contagious pathogen that is often underrecognized in older adults. While the general burden of RSV has previously been assessed, little is known on the frequency and factors associated with RSV-related clinical events in older adults. Methods Patients ≥60 years old with a diagnosis code for RSV (index date) and ≥6 months of enrollment pre-index (baseline) were analyzed using claims data from the 100% Medicare database (2007-2019). The following RSV-related clinical events were assessed during the up-to-6-month post-index period: acute respiratory failure, chronic respiratory disease (asthma or chronic obstructive pulmonary disease), congestive heart failure, dyspnea, hypoxia, non-RSV lower/upper respiratory tract infection, and pneumonia. Patients were at risk of developing each clinical event if they did not already have the event at baseline. A stepwise Poisson regression model was used to identify baseline predictors of having ≥1 clinical event. Results A total of 175,392 patients were included (mean age: 79.0 years, 64.8% female, 78.4% white, 76.9% had ≥1 RSV-related clinical event at baseline). During the up-to-6-month period following RSV infection, 47.9% had ≥1 incident RSV-related clinical event (Figure). The mean (median) time to a clinical event was 1.0 (0.1) month. Having an event was more likely for patients with baseline conditions (coronary artery disease, diabetes, or one of the above RSV-related clinical events [except pneumonia and asthma]) or with chemotherapy, chest x-ray, organ transplant, anti-asthmatic use, or bronchodilator use at baseline (incidence rate ratio [IRR] range=1.06 [bronchodilators] to 1.80 [chest x-ray], all P< .05); having an event was less likely for patients with one of the following: lower age, female gender, baseline influenza or RSV test, baseline use of antibiotics, or baseline use of influenza agents (IRR range=0.63 [antibiotics] to 0.92 [baseline RSV test], all P< .05). FigureRSV-related clinical events among Medicare beneficiaries ≥60 years old Conclusion Almost half of patients ≥60 years old had an RSV-related clinical event within 1 month of RSV infection; patients with pre-existing conditions (≥75% of patients) were at higher risk of an event. These findings highlight that many older adults with RSV experience significant clinical events that burden both the patient and the healthcare system. Disclosures Jessica K. K. DeMartino, PhD, Janssen Scientific Affairs, LLC: Employee of Janssen Scientific Affairs, LLC Marie-Hélène Lafeuille, MSc, Janssen Scientific Affairs, LLC: Advisor/Consultant Bruno Emond, MSc, Janssen Scientific Affairs, LLC: Advisor/Consultant Carmine Rossi, PhD, Janssen Scientific Affairs, LLC: Advisor/Consultant Jingru Wang, BA, Janssen Scientific Affairs, LLC: Advisor/Consultant Stephanie Liu, MS, Janssen Scientific Affairs, LLC: Advisor/Consultant Patrick Lefebvre, MSc, Janssen Scientific Affairs, LLC: Advisor/Consultant Girishanthy Krishnarajah, MBA, Janssen Scientific Affairs, LLC: Employee of Janssen Scientific Affairs, LLC.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.407
Teacher spread0.359 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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