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Record W4399898841 · doi:10.1016/j.ijregi.2024.100394

Prospective cohort study of patient demographics, viral agents, seasonality, and outcomes of influenza-like illness in Mexico in the late H1N1-pandemic and post-pandemic years (2010-2014)

2024· article· en· W4399898841 on OpenAlexaff
Arturo Galindo‐Fraga, Paola del Carmen Guerra-de-Blas, Ana A. Ortiz‐Hernández, Kevin Rubenstein, Ana M. Ortega‐Villa, Alejandra Ramírez‐Venegas, Rafael Valdez-Vázquez, Sarbelio Moreno‐Espinosa, Beatriz Llamosas‐Gallardo, Santiago Pérez-Patrigeón, Daniel E. Noyola, Martín Magaña-Aquino, Ana Vilardell-Dávila, M. Lourdes Guerrero, John H. Powers, John H. Beigel, Guillermo M. Ruiz‐Palacios

Bibliographic record

VenueIJID Regions · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsQueen's University
FundersHospital Infantil de México Federico GómezNational Institute of Allergy and Infectious DiseasesInstituto de Seguriidad y Servicios Sociales de los Trabadores del EstadoInstituto Mexicano del Seguro SocialMinistry of Health MexicoNational Cancer InstituteU.S. Department of Health and Human ServicesNational Institutes of HealthUniversidad Autónoma de San Luis PotosíConsejo Nacional de Ciencia y TecnologíaLeidosInstituto Nacional de Pediatria
KeywordsRhinovirusMedicinePandemicInfluenza-like illnessVaccinationProspective cohort studyCohortCohort studyInternal medicinePediatricsVirologyVirusDiseaseInfectious disease (medical specialty)Coronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

Objectives: Influenza-like illness (ILI) caused by respiratory viruses results in various respiratory clinical manifestations. The ILI002 prospective observational cohort study aimed to describe viral agents, seasonality, and outcomes of patients with ILI during four seasons in the influenza H1N1-pandemic and post-pandemic years (2010-2014). Methods: Patients from six Mexican hospitals were enrolled from April 2010 to March 2014. Clinical data and nasopharyngeal swabs were obtained and tested for viral respiratory pathogens by real-time reverse-transcription polymerase chain reaction. Results: Of the 5662 enrolled participants, 64.9% were adults and 35.1% were children. Among the 5629 participants with single-pathogen detection, rhinovirus (20.2%), influenza virus (11.2%), respiratory syncytial virus (RSV) (7.2%), and coronavirus (6.8%) were the most frequent pathogens. Co-infection occurred in 14.5% of cases; 49.3% of participants required hospitalization, particularly in RSV cases (42.9% adults, 89.6% children). The mortality rate was 2.8% higher among older adult participants and those with comorbidities. Influenza H1N1 had the highest mortality rate, yet almost half of the deceased had no pathogen. Rhinovirus persisted year-round, while influenza, coronavirus, and RSV peaked during cooler months. Conclusions: Analyses showed that some viruses causing ILI may lead to severe disease and hospitalization irrespective of comorbidities. These findings may help in decision-making about public health policies on prevention measures, vaccination, treatment, and administration of health care.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.000
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 score0.003
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.036
GPT teacher head0.359
Teacher spread0.323 · 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

Labeled directly by 2 models reading the full record.

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

Citations3
Published2024
Admission routes1
Has abstractyes

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