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Record W4323921386 · doi:10.1093/cid/ciad143

Post-Acute Sequelae After Severe Acute Respiratory Syndrome Coronavirus 2 Infection by Viral Variant and Vaccination Status: A Multicenter Cross-Sectional Study

2023· article· en· W4323921386 on OpenAlexaff
Christian R. Kahlert, Carol Strahm, Sabine Güsewell, Alexia Cusini, Stephan Goppel, Elisabeth Möller, Jens Carsten Möller, Manuela Ortner, Markus Ruetti, Reto Stocker, Danielle Vuichard‐Gysin, Allison McGeer, Lorenz Risch, Andrée Friedl, Matthias Schlegel, Pietro Vernazza, Stefan P. Kuster, Philipp Köhler, Thomas Egger, Fabian Grässli, Joelle Keller, Simone Kessler, Onício Leal Neto, Eva Lemmenmeier, Dorette Meier Kleeb, Maja Müller, Vaxhid Musa, Philip Rieder, Hans-Ruedi Schmid, Matthias von Kietzell, Benedikt Wiggli

Bibliographic record

VenueClinical Infectious Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsSinai Health System
Fundersnot available
KeywordsMedicineVaccinationConfidence intervalInternal medicineSerologyConfoundingCohortCohort studyProspective cohort studyCross-sectional studyPneumoniaPediatricsImmunologyAntibodyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Disentangling the effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and vaccination on the occurrence of post-acute sequelae of SARS-CoV-2 (PASC) is crucial to estimate and reduce the burden of PASC. METHODS: We performed a cross-sectional analysis (May/June 2022) within a prospective multicenter healthcare worker (HCW) cohort in north-eastern Switzerland. HCWs were stratified by viral variant and vaccination status at time of their first positive SARS-CoV-2 nasopharyngeal swab. HCWs without positive swab and with negative serology served as controls. The sum of 18 self-reported PASC symptoms was modeled with univariable and multivariable negative-binomial regression to analyze the association of mean symptom number with viral variant and vaccination status. RESULTS: Among 2912 participants (median age: 44 years; 81.3% female), PASC symptoms were significantly more frequent after wild-type infection (estimated mean symptom number: 1.12; P < .001; median time since infection: 18.3 months), after Alpha/Delta infection (0.67 symptoms; P < .001; 6.5 months), and after Omicron BA.1 infections (0.52 symptoms; P = .005; 3.1 months) versus uninfected controls (0.39 symptoms). After Omicron BA.1 infection, the estimated mean symptom number was 0.36 for unvaccinated individuals versus 0.71 with 1-2 vaccinations (P = .028) and 0.49 with ≥3 prior vaccinations (P = .30). Adjusting for confounders, only wild-type (adjusted rate ratio [aRR]: 2.81; 95% confidence interval [CI]: 2.08-3.83) and Alpha/Delta infections (aRR: 1.93; 95% CI: 1.10-3.46) were significantly associated with the outcome. CONCLUSIONS: Previous infection with pre-Omicron variants was the strongest risk factor for PASC symptoms among our HCWs. Vaccination before Omicron BA.1 infection was not associated with a clear protective effect against PASC symptoms in this population.

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)0.002
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.405
Teacher spread0.375 · 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

Citations56
Published2023
Admission routes1
Has abstractyes

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