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Record W2980647784 · doi:10.1111/irv.12686

Estimates for quality of life loss due to Respiratory Syncytial Virus

2019· article· en· W2980647784 on OpenAlexaff
David Hodgson, Katherine E. Atkins, Marc Baguelin, Jasmina Panovska‐Griffiths, Dominic Thorrington, Albert Jan van Hoek, Hongxin Zhao, Ellen Fragaszy, Andrew Hayward, Richard Pebody

Bibliographic record

VenueInfluenza and Other Respiratory Viruses · 2019
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsCentre for Global Health Research
FundersNational Institute for Health and Care Research
KeywordsMedicinePediatricsQuality of life (healthcare)Quality-adjusted life yearCost effectiveness

Abstract

fetched live from OpenAlex

Abstract Background In children aged <5 years in whom severe respiratory syncytial virus (RSV) episodes predominantly occur, there are currently no appropriate standardised instruments to estimate quality of life years (QALY) loss. Objectives We estimated the age‐specific QALY loss due to RSV by developing a regression model which predicts the QALY loss without the use of standardised instruments. Methods We conducted a surveillance study which targeted confirmed RSV episodes in children aged <5 years (confirmed cases) and their household members who experienced symptoms of RSV during the same time (suspected cases). All participants were asked to complete questions regarding their health during the infection, with the suspected cases additionally providing health‐related quality of life (HR‐QoL) loss estimates by completing EQ‐5D‐3L‐Y or EQ‐5D‐3L instruments. We used the responses from the suspected cases to calibrate a regression model which estimates the HR‐QoL and QALY loss due to infection. Findings For confirmed RSV cases in children under 5 years of age who sought health care, our model predicted a QALY loss per RSV episode of 3.823 × 10 −3 (95% CI 0.492‐12.766 × 10 −3 ), compared with 3.024 × 10 −3 (95% CI 0.329‐10.098 × 10 −3 ) for under fives who did not seek health care. Quality of life years loss per episode was less for older children and adults, estimated as 1.950 × 10 −3 (0.185‐9.578 × 10 −3 ) and 1.543 × 10 −3 (0.136‐6.406 × 10 −3 ) for those who seek or do not seek health care, respectively. Conclusion Evaluations of potential RSV vaccination programmes should consider their impact across the whole population, not just young child children.

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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.218
GPT teacher head0.465
Teacher spread0.248 · 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 teacher head, not a consensus.

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

Citations48
Published2019
Admission routes1
Has abstractyes

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