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Record W4403010339 · doi:10.1097/ms9.0000000000002450

Effectiveness of hypertonic saline with or without hyaluronic acid among patients with cystic fibrosis: a systematic review and meta-analysis

2024· review· en· W4403010339 on OpenAlexaboutno aff
Zarghuna Khan, Muhammad Omar Naeem, Anam Amin, Laraib Amin, Abdullah Shah, Saad Ul Khaliq, Aima Azhar, Sana Naz, Syed Muhammad Shujauddin, Muhammad Arshad, Sarosh J. Ali, Emad U. Sajid, Sayed Jawad

Bibliographic record

VenueAnnals of Medicine and Surgery · 2024
Typereview
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTolerabilityHypertonic salineAdverse effectMeta-analysisRelative riskInternal medicineSubgroup analysisCystic fibrosisSystematic reviewGastroenterologySurgeryMEDLINEConfidence interval

Abstract

fetched live from OpenAlex

Background: The clinical effectiveness of hypertonic saline (HS) in individuals with cystic fibrosis (CF) can be compromised by adverse effects. The objective of this study was to examine the efficacy of hyaluronic acid (HA) in mitigating these negative occurrences. Methods: A comprehensive review of the literature was carried out using three electronic databases: Medline, Cochrane Central, and Embase. This systematic review and meta-analysis investigate the efficacy of hypertonic saline (HS) with and without hyaluronic acid (HA) in treating cystic fibrosis. Primary outcomes include the incidence of cough, throat irritation, unpleasant taste, and changes in FEV1. Our findings suggest that adding HA to HS significantly reduces adverse effects and enhances patient tolerability, marking a potential improvement in cystic fibrosis therapy. Risk ratios (RRs) and mean differences (MDs) with 95% CI were used to present evaluations. The quality of RCTs was evaluated using the Cochrane Risk of Bias Tool (CRBT). The quality of the observational study was evaluated using the Newcastle–Ottawa Scale. Results: From the 1960 articles retrieved from the initial search, five relevant studies (n=236 patients) were included in the final analysis. Compared with patients only on HS, patients with HS and HA were significantly less likely to experience cough (RR: 0.45; 95% CI, 0.28–0.72, P=0.001), throat irritation (RR: 0.43; 95% CI, 0.22–0.81, P=0.009), and unpleasant smell (RR: 0.43; 95% CI, 0.23–0.80, P=0.09). In addition, patients with HS with HA had significantly less forced expiratory volume (FEV1) (MD: −2.97; 95% CI, −3.79–−2.15, P=0.52), compared to patients only on HS. Patients on HA + HS had significantly lower rates of cough (RR: 0.45; 95% CI, 0.28–0.72, P=0.001), throat irritation (RR: 0.43; 95% CI, 0.22–0.81, P=0.009), and bad smell (RR: 0.43; 95% CI, 0.23–0.80, P=0.09) when compared to patients on HS alone. Furthermore, compared to patients solely on HS, patients with HS plus HA exhibited a substantially lower forced expiratory volume (FEV1) (MD: −2.97; 95% CI, −3.79 to −2.15, P=0.52) as well. Conclusion: For CF patients who need ongoing HS therapy and have a history of poor therapy tolerance, adding HA is beneficial.

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)0.012
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.026
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0230.042
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.109
GPT teacher head0.398
Teacher spread0.289 · 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 designMeta-analysis
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

Citations0
Published2024
Admission routes1
Has abstractyes

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