Effect of P2Y12 Inhibitors, SGLT2 Inhibitors and P-Selectin Inhibitors on One-year Quality-of-Life Outcomes in Critically Ill Patients Hospitalized for COVID-19: A Pre-specified Secondary Analysis of the ACTIV4a Randomized Clinical Trial
Bibliographic record
Abstract
Abstract Introduction Post-Acute Sequelae of COVID-19 (PASC) is a significant complication of SARS-CoV-2 infection, leading to persistent symptoms and diminished functional status. Long-term QoL data, particularly in relation to therapeutic interventions like P2Y12 inhibitors, SGLT2 inhibitors, and crizanlizumab, remain limited. This study aimed to evaluate the effect of these treatments on one-year QoL outcomes in critically ill COVID-19 patients. Methods: This analysis is part of the Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV-4a) randomized controlled platform trial, conducted at 34 hospitals in the United States and Spain from September 2020 to June 2021. Participants were randomized to receive standard care or one of the following interventions: P2Y12 inhibitors, SGLT2 inhibitors, or crizanlizumab. QoL outcomes were assessed one year after hospitalization using the Patient-Reported Outcomes Measurement Information System (PROMIS), which measured domains such as physical and mental health, sleep disturbance, and neurological QoL. Univariate and multivariable analyses were conducted to evaluate treatment effects and identify independent predictors of QoL. Results: In total, 750 participants completed PROMIS questionnaires one year post-trial (n=258 SGLT2 inhibitor, n=191 crizanlizumab, n=19 P2Y12 inhibitor). Subject characteristics including age, sex, race, and baseline comorbidities were not significantly different between treatment and control groups. There were no significant differences in the PROMIS t-scores for physical and mental health, sleep disturbance, and neurological QoL (all p>0.05) based on receipt of P2Y12 inhibitors, SGLT2 inhibitor, or crizanlizumab. Average PROMIS t-scores for mental health were consistently lower than the reference score, and physical health across all groups approached 1 standard deviation below the U.S. general public. Pre-infection respiratory disease was associated with lower physical health (difference = -4.99, p < 0.0001), lower mental health (difference = -4.09, p = 0.0001), and higher sleep disturbance t-scores (difference = 4.38, p < 0.0001). Severe disease status was associated with higher physical health t-scores (difference = 4.06, p = 0.0302). Female sex was associated with lower neurological QoL score (difference = -3.02, p = 0.0175), while Hispanic ethnicity (difference = 6.15, p = 0.0005) and pre-infection immunosuppressive disease were associated with higher neurological QoL scores (difference = 3.88, p = 0.0077). Conclusion: In this secondary analysis of a randomized controlled platform trial, P2Y12 inhibitors, SGLT-2 inhibitors, and crizanlizumab were not associated with significant improvement in one-year QoL outcomes among hospitalized COVID-19 patients. Reduced physical and mental health scores were observed across multiple groups, with predictors of diminished QoL including pre-infection respiratory disease, female sex, and ethnicity.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".