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Zinc for prevention and treatment of the common cold

2024· review· en· W4396774089 on OpenAlexaff
Daryl Nault, Taryn A Machingo, Andrea Goldstein Shipper, Daniel A. Antiporta, Candyce Hamel, Sahar Nourouzpour, Menelaos Konstantinidis, Erica Phillips, Elizabeth A Lipski, L. Susan Wieland

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2024
Typereview
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsInstitute for Clinical Evaluative SciencesToronto General HospitalUniversity of TorontoSickKids FoundationHospital for Sick ChildrenPublic Health Ontario
Fundersnot available
KeywordsCommon coldZincMedicineMaterials scienceMetallurgyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: The common cold is an acute, self-limiting viral respiratory illness. Symptoms include nasal congestion and mucus discharge, sneezing, sore throat, cough, and general malaise. Given the frequency of colds, they are a public health burden and a significant cause of lost work productivity and school absenteeism. There are no established interventions to prevent colds or shorten their duration. However, zinc supplements are commonly recommended and taken for this purpose. OBJECTIVES: To assess the effectiveness and safety of zinc for the prevention and treatment of the common cold. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, CINAHL, and LILACS to 22 May 2023, and searched Web of Science Core Collection and two trials registries to 14 June 2023. We also used reference checking, citation searching, and contact with study authors to identify additional studies. SELECTION CRITERIA: We included randomised controlled trials (RCTs) in children or adults that tested any form of zinc against placebo to prevent or treat the common cold or upper respiratory infection (URTI). We excluded zinc interventions in which zinc was combined with other minerals, vitamins, or herbs (e.g. a multivitamin, or mineral supplement containing zinc). DATA COLLECTION AND ANALYSIS: We used the Cochrane risk of bias tool to assess risks of bias, and GRADE to assess the certainty of the evidence. We independently extracted data. When necessary, we contacted study authors for additional information. We assessed zinc (type and route) with placebo in the prevention and treatment of the common cold. Primary outcomes included the proportion of participants developing colds (for analyses of prevention trials only), duration of cold (measured in days from start to resolution of the cold), adverse events potentially due to zinc supplements (e.g. unpleasant taste, loss of smell, vomiting, stomach cramps, and diarrhoea), and adverse events considered to be potential complications of the common cold (e.g. respiratory bacterial infections). MAIN RESULTS: = 44%; 2084 participants, 16 studies; moderate-certainty evidence); no treatment study provided information on serious adverse events. No study provided clear information about adverse events considered to be potential complications of the common cold. AUTHORS' CONCLUSIONS: The findings suggest that zinc supplementation may have little or no effect on the prevention of colds but may reduce the duration of ongoing colds, with an increase in non-serious adverse events. Overall, there was wide variation in interventions (including concomitant therapy) and outcomes across the studies, as well as incomplete reporting of several domains, which should be considered when making conclusions about the efficacy of zinc for the common cold.

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)0.006
metaresearch head score (Gemma)0.014
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 score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0050.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.191
GPT teacher head0.459
Teacher spread0.268 · 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".

Quick stats

Citations16
Published2024
Admission routes1
Has abstractyes

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