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Record W4392114117 · doi:10.46234/ccdcw2024.029

Experts’ Consensus on the Management of Respiratory Disease Syndemic

2024· article· en· W4392114117 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChina CDC Weekly · 2024
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMinistry of Education and Child Care
FundersChinese Academy of Medical SciencesNational Natural Science Foundation of China
KeywordsSyndemicDisease managementMedicineIntensive care medicineDiseaseInternal medicinePublic healthPathology

Abstract

fetched live from OpenAlex

The global burden of respiratory diseases is a significant and increasing threat to individuals worldwide.In 2017, there were 544.9 million cases of chronic respiratory diseases, a 39.8% increase since 1990 (1).These diseases were the third leading cause of global mortality in 2017, accounting for 7.0% of all deaths, an 18.0% increase compared to 1990.In addition to chronic respiratory diseases, acute infectious respiratory diseases, including influenza, coronavirus diseases 2019 (COVID-19), and respiratory syncytial virus, pose significant public health concerns and cause both short-term and longterm health damages (2-3).The presence of complex coexisting diseases in the respiratory system further complicates treatment and increases the burden of disease.To effectively address these challenges, it is crucial to implement a comprehensive and robust management approach.A syndemic refers to the co-occurrence of multiple diseases or health conditions within a population, where biological or behavioral factors worsen the negative health impacts of these conditions (4).Syndemic theory suggests that the combined presence of diseases, along with social and environmental factors, synergistically affects population health.This theory provides a valuable framework for understanding and addressing respiratory disease syndemics.Managing respiratory diseases from a syndemic perspective necessitates a deep understanding of the intricate interplay between biological, social, and environmental factors that contribute to the occurrence and progression of these diseases.By adopting a syndemic approach, the focus shifts from managing individual diseases to a collaborative model that prioritizes population-level interventions, including proactive diagnosis, comprehensive assessment of disease severity, and integrated management of conditions associated with respiratory diseases.The expert consensus on managing respiratory disease syndemics aims to support research and practical interventions in addressing these complex respiratory health challenges.

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.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.314
Teacher spread0.283 · 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