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Vaccines for preventing influenza in healthy adults

2007· review· en· W4210979995 on OpenAlexaff
Vittorio Demicheli, Carlo Di Pietrantonj, Tom Jefferson, Alessandro Rivetti, Daniela Rivetti

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2007
Typereview
Languageen
Field
Topic
Canadian institutionsCochrane
Fundersnot available
KeywordsMedicineInfluenza vaccineClinical trialCochrane LibraryPlaceboRandomized controlled trialMEDLINEVaccinationMeta-analysisInternal medicinePediatricsImmunologyAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Different types of influenza vaccines are currently produced world-wide. Healthy adults are at present targeted only in North America. Despite the publication of a large number of clinical trials, there is still substantial uncertainty about the clinical effectiveness of influenza vaccines and this has a negative impact on their acceptance and uptake. OBJECTIVES: To identify, retrieve and assess all studies evaluating the effects (efficacy, effectiveness and harms) of vaccines against influenza in healthy adults. SEARCH STRATEGY: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library, Issue 4, 2005) which contains the Cochrane Acute Respiratory Infections Group trials register; MEDLINE (January 1966 to January 2006); and EMBASE (1990 to January 2006). We wrote to vaccine manufacturers and first or corresponding authors of studies in the review. SELECTION CRITERIA: Any randomised or quasi-randomised studies comparing influenza vaccines in humans with placebo, no intervention. Live, attenuated, or killed vaccines or fractions of them administered by any route, irrespective of antigenic configuration were assessed. Only studies assessing protection from exposure to naturally occurring influenza in healthy individuals aged 16 to 65 years were considered. Comparative non-randomised studies were included if they assessed evidence of the possible association between influenza vaccines and serious harms. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed trial quality and extracted data. MAIN RESULTS: Forty-eight reports were included: 38 (57 sub-studies) were clinical trials providing data about effectiveness, efficacy and harms of influenza vaccines and involved 66,248 people; 8 were comparative non-randomised studies and tested the association of the vaccines with serious harms; 2 were reports of harms which could not be introduced in the data analysis. Inactivated parenteral vaccines were 30% effective (95% CI 17% to 41%) against influenza-like illness, and 80% (95% CI 56% to 91%) efficacious against influenza when the vaccine matched the circulating strain and circulation was high, but decreased to 50% (95% CI 27% to 65%) when it did not. Excluding the studies of the 1968 to 1969 pandemic, effectiveness was 15% (95% CI 9% to 22%) and efficacy was 73% (95% CI 53% to 84%). Vaccination had a modest effect on time off work, but there was insufficient evidence to draw conclusions on hospital admissions or complication rates. Inactivated vaccines caused local tenderness and soreness and erythema. Spray vaccines had more modest performance. Monovalent whole-virion vaccines matching circulating viruses had high efficacy (VE 93%, 95% CI 69% to 98%) and effectiveness (VE 66%, 95% CI 51% to 77%) against the 1968 to 1969 pandemic. AUTHORS' CONCLUSIONS: Influenza vaccines are effective in reducing cases of influenza, especially when the content predicts accurately circulating types and circulation is high. However, they are less effective in reducing cases of influenza-like illness and have a modest impact on working days lost. There is insufficient evidence to assess their impact on complications. Whole-virion monovalent vaccines may perform best in a pandemic.

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)0.013
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0070.005
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.216
GPT teacher head0.464
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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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Citations143
Published2007
Admission routes1
Has abstractyes

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