MétaCan
Menu
Back to cohort
Record W7127319698 · doi:10.48036/apims.v21i4.1513

Role of Probiotics in the Prevention of Recurrent Upper Respiratory Tract Infections in the Pediatric Age Group

2025· article· W7127319698 on OpenAlexaff
N Waraich, Muhammad Omer Tufail, Zainab Abbasi, Muhammad Umer Farooq

Bibliographic record

VenueAnnals of PIMS-Shaheed Zulfiqar Ali Bhutto Medical University · 2025
Typearticle
Language
FieldHealth Professions
TopicPediatric health and respiratory diseases
Canadian institutionsKinectrics (Canada)
Fundersnot available
KeywordsRespiratory tract infectionsUpper respiratory tract infectionUpper respiratory infectionsRespiratory infectionInformed consentRespiratory tract

Abstract

fetched live from OpenAlex

Objectives: To determine the role of probiotics in prevention of recurrent upper respiratory tract infection in children. Methodology: This quasi-experimental study was conducted at Pediatrics department of Combined Military Hospital, Quetta, Pakistan from October 2024 to April 2025 after taking parental informed consent and ethical approval from institution. A total of 64 children with recurrent upper respiratory tract infection were included, selected through non-probability consecutive sampling technique, who were divided into Group-P (probiotic) and Group-S (no probiotics) containing 32 children each. Children were followed up after three months to assess for recurrence. Analysis of data was performed through Statistical Package for Social Sciences (SPSS) software version 22. Results: Median age was 5.00 (3.00) years. There were 45 (70.30%) male and 19 (29.70%) female patients. Median number of episodes of URTI in three months at the end of study in Group-P was 1.00 (2.00) while in Group-S it was 2.00 (3.00), (p = 0.136). Frequency of recurrence of URTI in Group-P (n = 32) at three months follow up was 9 (28.13%) while in Group-S (n = 32), it was 17 (53.13%), (p = 0.042). Conclusion: Probiotics can effectively prevent recurrent upper respiratory tract infection in 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)0.009
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.073
GPT teacher head0.391
Teacher spread0.319 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of PIMS-Shaheed Zulfiqar Ali Bhutto Medical UniversitySame topicPediatric health and respiratory diseasesFrench-language works237,207