Efficacy and safety of ensifentrine, a novel phosphodiesterase 3 and 4 inhibitor, in chronic obstructive pulmonary disease: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: We evaluated the efficacy and safety of Ensifentrine in COPD via a systematic review and meta-analysis of randomized controlled trials (RCTs). METHODS: We performed a detailed literature search on Medline (via PubMed), Scopus, Google Scholar, and Cochrane on the basis of pre-specified eligibility criteria. We used Review Manager to calculate pooled mean differences (MD) and 95% Confidence Interval (CI) using a random effects model. The Cochrane's Risk of Bias 2 (RoB-2) tool was used to assess the risk of bias in the included RCTs. RESULTS: A total of 4 studies, consisting of 2020 patients, were included in the meta-analysis. The mean age ranged from 62.5 years to 65.5 years in the included studies. All the included studies were at low risk of bias. Ensifentrine 3 mg dose significantly improved the mean peak Forced Expiratory Volume-1 (FEV-1), morning trough FEV-1, TDI score, ERS score, and SGRQ-C score as compared to the placebo, yielding a pooled MD of 149.76 (95% CI, 127.9 to 171.6), 43.93 (95% CI, 23.82 to 64.05), 0.92 (95% CI, 0.64 to 1.21, -1.20 (95% CI, -1.99 to -0.40), and -1.92 (95% CI, -3.24 to -0.59), respectively. CONCLUSION: Ensifentrine is associated with improvements in outcomes related to COPD symptoms such as peak FEV-1, morning trough FEV-1 and TDI in the patients suffering from this chronic disease. It is also associated with improved quality of life as seen by E-RS score and SGRQ-C score.
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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 | 0.022 | 0.033 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.049 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".