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Record W4386548381 · doi:10.2196/46375

Pediatric Tui Na for Feeding Intolerance in Premature Infants: Protocol for a Systematic Review and Meta-Analysis

2023· review· en· W4386548381 on OpenAlexvenueno aff
Zirong Bai, Xiaoxiao Lyu, Yichuan Tang, Meng Wang

Bibliographic record

VenueJMIR Research Protocols · 2023
Typereview
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsnot available
FundersNanjing UniversityNanjing University of Chinese Medicine
KeywordsCINAHLMEDLINEMedicineCochrane LibraryRandomized controlled trialSystematic reviewProtocol (science)ScopusPediatricsAlternative medicineInternal medicinePsychological interventionNursingPathology

Abstract

fetched live from OpenAlex

Background Feeding intolerance (FI), frequently resulting from gastrointestinal immaturity, is prevalent among premature infants. Current practices are gradually prioritizing nonpharmacological treatments, such as massage or “Tui na,” considering the potential side effects of prolonged medication use. Pediatric Tui na, a specialized massage therapy based on traditional Chinese medicine, has been widely studied for treating FI in premature infants. However, to our knowledge, no systematic review specifically focusing on the effectiveness and safety of traditional Chinese medicine–based pediatric Tui na for FI in premature infants has been published yet. Objective This study aims to develop a protocol for a systematic review and meta-analysis for evaluating the safety and efficacy of pediatric Tui na for premature infants with FI. Methods We will perform a comprehensive search in the following databases: Springer, Cochrane Library, Embase, MEDLINE, Clarivate Analytics, Physiotherapy Evidence Database (PEDro), CINAHL, PubMed, Scopus, World Health Organization (WHO) International Clinical Trials Registry Platform, and Chinese biomedical databases (Wanfang database, the China National Knowledge Infrastructure, Chinese Scientific Journals Database, and Chinese Biomedical Literature Databases), limited to studies published in Chinese and English languages between January 2000 and January 2023. The search strategy will use MeSH (Medical Subject Headings) terms and database-specific keywords. A total of 2 independent reviewers will initially screen the studies based on titles and abstracts, followed by a full-text evaluation of the eligible studies. Studies will include any nonrandomized controlled trials, nonrandomized clinical studies, randomized controlled trials, and quasi-experimental studies wherein the treatment group involves premature infants with FI given pediatric Tui na. Primary outcomes will be necrotizing enterocolitis, gastric residual volume, emesis, and stool blood. Secondary outcomes will be abdominal distension weight gain, time to achieve full enteral feeding, any adverse effects associated with pediatric Tui na, and length of hospital stay. The Cochrane Collaboration Risk of Bias Tool will be used to assess the risk of bias and methodological quality. Funnel plots will be used for evaluating publication bias. Meta-analysis will be conducted using the Review Manager software (version 5.4; Cochrane Collaboration). Subgroup analyses will be considered according to treatment received, country or setting, sex, and birth weight of premature infants (if heterogeneity is high, I2≥50%). Results This is a systematic review and meta-analysis protocol, so the results are not yet available. The protocol has been registered with PROSPERO (CRD42023390021). We are currently in the study selection phase. Results are expected to be completed by the end of 2023. Conclusions Following this protocol, a comprehensive and rigorous literature synthesis will be developed to assess the impact of pediatric Tui na treatment on premature infants with FI, enabling the determination of its efficacy and safety. Trial Registration PROSPERO CRD42023390021; https://tinyurl.com/bdf4kn23 International Registered Report Identifier (IRRID) PRR1-10.2196/46375

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)0.076
metaresearch head score (Gemma)0.093
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.076
Threshold uncertainty score0.401

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0760.093
Meta-epidemiology (narrow)0.0060.005
Meta-epidemiology (broad)0.0240.029
Bibliometrics0.0100.010
Science and technology studies0.0030.003
Scholarly communication0.0070.007
Open science0.0060.004
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0640.006

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 head0.559
GPT teacher head0.653
Teacher spread0.094 · 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
GenreProtocol

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

Citations3
Published2023
Admission routes1
Has abstractyes

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