Diuretics use in the management of bronchopulmonary dysplasia in preterm infants: A systematic review
Bibliographic record
Abstract
AIM: Bronchopulmonary dysplasia (BPD), a respiratory complication associated with neonatal prematurity, presents opportunities for pharmacological intervention due to its contributing risk factors. Despite diuretics' controversial usage in BPD treatment and varying institutional practices, this review aims to consolidate evidence from clinical trials regarding diuretic use in BPD. METHODS: We conducted a systematic review following PRISMA guidelines, searching EMBASE, Medline, Web of Science and CINAHL databases (PROSPERO 2022: CRD42022328292). Covidence facilitated screening and data extraction, followed by analysis and formatting in Microsoft Excel. RESULTS: Among 430 screened records, 13 were included for analysis. Three studies assessed spironolactone and chlorothiazide combinations, two studied spironolactone and hydrochlorothiazide, while eight examined furosemide. All studies evaluated drug effects on dynamic pulmonary compliance and pulmonary resistance, serving as comparative measures in our review. CONCLUSION: Diuretics' effectiveness in treating bronchopulmonary dysplasia remains uncertain. The limited number of identified randomised controlled trials (RCTs) hampers high-level evidence-based conclusions when applying the Population, Intervention, Comparison, Outcome (PICO) approach. Conducting large prospective studies of good quality could provide more definitive insights, but the rarity of outcomes and eligible patients poses challenges. Further research, primarily focusing on RCTs assessing diuretics' safety and efficacy in this population, is warranted.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".