Platelet versus fresh frozen plasma transfusion for coagulopathy in cardiac surgery patients.

BACKGROUND: Platelets (PLTS) and fresh frozen plasma (FFP) are often transfused in cardiac surgery patients for perioperative bleeding. Their relative effectiveness is unknown. METHODS: We conducted an entropy-weighted retrospective cohort study using the Australian and New Zealand Society of Cardiac and Thoracic Surgeons National Cardiac Surgery Database. All adults undergoing cardiac surgery between 2005-2021 across 58 sites were included. The primary outcome was operative mortality. RESULTS: Of 174,796 eligible patients, 15,360 (8.79%) received PLTS in the absence of FFP and 6,189 (3.54%) patients received FFP in the absence of PLTS. The median cumulative dose was 1 unit of pooled platelets (IQR 1 to 3) and 2 units of FFP (IQR 0 to 4) respectively. After entropy weighting to achieve balanced cohorts, FFP was associated with increased perioperative (Risk Ratio [RR], 1.63; 95% Confidence Interval [CI], 1.40 to 1.91; P<0.001) and 1-year (RR, 1.50; 95% CI, 1.32 to 1.71; P<0.001) mortality. FFP was associated with increased rates of 4-hour chest drain tube output (Adjusted mean difference in ml, 28.37; 95% CI, 19.35 to 37.38; P<0.001), AKI (RR, 1.13; 95% CI, 1.01 to 1.27; P = 0.033) and readmission to ICU (RR, 1.24; 95% CI, 1.09 to 1.42; P = 0.001). CONCLUSION: In perioperative bleeding in cardiac surgery patient, platelets are associated with a relative mortality benefit over FFP. This information can be used by clinicians in their choice of procoagulant therapy in this setting.

Platelet Transfusion in Cardiac Surgery: An Entropy-Balanced, Weighted, Multicenter Analysis.

BACKGROUND: Platelet transfusion is common in cardiac surgery, but some studies have suggested an association with harm. Accordingly, we investigated the association of perioperative platelet transfusion with morbidity and mortality. METHODS: We conducted a retrospective analysis of prospectively collected data from the Australian Society of Cardiac and Thoracic Surgeons National Cardiac Surgery Database. We included consecutive adults from 2005 to 2018 across 40 centers. We used inverse probability of treatment weighting via entropy balancing to investigate the association of perioperative platelet transfusion with our 2 primary outcomes, operative mortality (composite of both 30-day and in-hospital mortality) and 90-day mortality, as well as multiple other clinically relevant secondary outcomes. RESULTS: Among 119,132 eligible patients, 25,373 received perioperative platelets and 93,759 were considered controls. After entropy balancing, platelet transfusion was associated with reduced operative mortality (odds ratio [OR], 0.63; 99% confidence interval [CI], 0.47-0.84; P < .0001) and 90-day mortality (OR, 0.66; 99% CI, 0.51-0.85; P < .0001). Moreover, it was associated with reduced odds of deep sternal wound infection (OR, 0.57; 99% CI, 0.36-0.89; P = .0012), acute kidney injury (OR, 0.84; 99% CI, 0.71-0.99; P = .0055), and postoperative renal replacement therapy (OR, 0.71; 99% CI, 0.54-0.93; P = .0013). These positive associations were observed despite an association with increased odds of return to theatre for bleeding (OR, 1.55; 99% CI, 1.16-2.09; P < .0001), pneumonia (OR, 1.26; 99% CI, 1.11-1.44; P < .0001), intubation for longer than 24 hours postoperatively (OR, 1.13; 99% CI, 1.03-1.24; P = .0012), inotrope use for >4 hours postoperatively (OR, 1.14; 99% CI, 1.11-1.17; P < .0001), readmission to hospital within 30 days of surgery (OR, 1.22; 99% CI, 1.11-1.34; P < .0001), as well as increased drain tube output (adjusted mean difference, 89.2 mL; 99% CI, 77.0 mL-101.4 mL; P < .0001). CONCLUSIONS: In cardiac surgery patients, perioperative platelet transfusion was associated with reduced operative and 90-day mortality. Until randomized controlled trials either confirm or refute these findings, platelet transfusion should not be deliberately avoided when considering odds of death.

A Tutorial for Propensity Score Weighting for Moderation Analysis With Categorical Variables: An Application Examining Smoking Disparities Among Sexual Minority Adults.

OBJECTIVE: To provide step-by-step guidance and STATA and R code for using propensity score (PS) weighting to estimate moderation effects with categorical variables. RESEARCH DESIGN: Tutorial illustrating the key steps for estimating and testing moderation using observational data. Steps include: (1) examining covariate overlap across treatment groups within levels of the moderator; (2) estimating the PS weights; (3) evaluating whether PS weights improved covariate balance; (4) estimating moderated treatment effects; and (5) assessing the sensitivity of findings to unobserved confounding. Our illustrative case study uses data from 41,832 adults from the 2019 National Survey on Drug Use and Health to examine if gender moderates the association between sexual minority status (eg, lesbian, gay, or bisexual [LGB] identity) and adult smoking prevalence. RESULTS: For our case study, there were no noted concerns about covariate overlap, and we were able to successfully estimate the PS weights within each level of the moderator. Moreover, balance criteria indicated that PS weights successfully achieved covariate balance for both moderator groups. PS-weighted results indicated there was significant evidence of moderation for the case study, and sensitivity analyses demonstrated that results were highly robust for one level of the moderator but not the other. CONCLUSIONS: When conducting moderation analyses, covariate imbalances across levels of the moderator can cause biased estimates. As demonstrated in this tutorial, PS weighting within each level of the moderator can improve the estimated moderation effects by minimizing bias from imbalance within the moderator subgroups.

Impact of Administering Buprenorphine to Overdose Survivors Using Emergency Medical Services.

STUDY OBJECTIVE: To evaluate the efficacy and safety of utilizing emergency medical services units to administer high dose buprenorphine after an overdose to treat withdrawal symptoms, reduce repeat overdose, and provide a next-day substances use disorder clinic appointment to initiate long-term treatment. METHODS: This was a retrospective matched cohort study of patients who experienced an overdose and either received emergency medical services care from a buprenorphine-equipped ambulance or a nonbuprenorphine-equipped ambulance in Camden, New Jersey, an urban community with high overdose rates. There were 117 cases and 123 control patients in the final sample. RESULTS: Compared with a nonbuprenorphine-equipped ambulance, exposure to a buprenorphine-equipped ambulance was associated with greater odds of engaging in opioid use disorder treatment within 30 days of an emergency medical services encounter (unadjusted odds ratio: 5.62, 95% confidence interval, 2.36 to 13.39). Buprenorphine-equipped ambulance engagement did not decrease repeat overdose compared to the comparison group. Patients who received buprenorphine experienced a decrease in withdrawal symptoms. Their clinical opiate withdrawal scale score decreased from an average of 9.27 to 3.16. buprenorphine-equipped ambulances increased on-scene time by 6.12 minutes. CONCLUSION: Patients who encountered paramedics trained to administer buprenorphine and able to arrange prompt substance use disorder treatment after an acute opioid overdose demonstrated a decrease in opioid withdrawal symptoms, an increase in outpatient addiction follow-up care, and showed no difference in repeat overdose. Patients receiving buprenorphine in the out-of-hospital setting did not experience precipitated withdrawal. Expanded out-of-hospital treatment of opiate use disorder is a promising model for rapid access to buprenorphine after an overdose in a patient population that often has limited contact with the health care system.

Causal mediation analysis: From simple to more robust strategies for estimation of marginal natural (in)direct effects.

This paper aims to provide practitioners of causal mediation analysis with a better understanding of estimation options. We take as inputs two familiar strategies (weighting and model-based prediction) and a simple way of combining them (weighted models), and show how a range of estimators can be generated, with different modeling requirements and robustness properties. The primary goal is to help build intuitive appreciation for robust estimation that is conducive to sound practice. We do this by visualizing the target estimand and the estimation strategies. A second goal is to provide a "menu" of estimators that practitioners can choose from for the estimation of marginal natural (in)direct effects. The estimators generated from this exercise include some that coincide or are similar to existing estimators and others that have not previously appeared in the literature. We note several different ways to estimate the weights for cross-world weighting based on three expressions of the weighting function, including one that is novel; and show how to check the resulting covariate and mediator balance. We use a random continuous weights bootstrap to obtain confidence intervals, and also derive general asymptotic variance formulas for the estimators. The estimators are illustrated using data from an adolescent alcohol use prevention study. R-code is provided.

Estimates of SARS-CoV-2 Omicron BA.2 Subvariant Severity in New England.

Importance: The SARS-CoV-2 Omicron subvariant, BA.2, may be less severe than previous variants; however, confounding factors make interpreting the intrinsic severity challenging. Objective: To compare the adjusted risks of mortality, hospitalization, intensive care unit admission, and invasive ventilation between the BA.2 subvariant and the Omicron and Delta variants, after accounting for multiple confounders. Design, Setting, and Participants: This was a retrospective cohort study that applied an entropy balancing approach. Patients in a multicenter inpatient and outpatient system in New England with COVID-19 between March 3, 2020, and June 20, 2022, were identified. Exposures: Cases were assigned as being exposed to the Delta (B.1.617.2) variant, the Omicron (B.1.1.529) variant, or the Omicron BA.2 lineage subvariants. Main Outcomes and Measures: The primary study outcome planned before analysis was risk of 30-day mortality. Secondary outcomes included the risks of hospitalization, invasive ventilation, and intensive care unit admissions. Results: Of 102 315 confirmed COVID-19 cases (mean [SD] age, 44.2 [21.6] years; 63 482 women [62.0%]), 20 770 were labeled as Delta variants, 52 605 were labeled as the Omicron B.1.1.529 variant, and 28 940 were labeled as Omicron BA.2 subvariants. Patient cases were excluded if they occurred outside the prespecified temporal windows associated with the variants or had minimal longitudinal data in the Mass General Brigham system before COVID-19. Mortality rates were 0.7% for Delta (B.1.617.2), 0.4% for Omicron (B.1.1.529), and 0.3% for Omicron (BA.2). The adjusted odds ratio of mortality from the Delta variant compared with the Omicron BA.2 subvariants was 2.07 (95% CI, 1.04-4.10) and that of the original Omicron variant compared with the Omicron BA.2 subvariant was 2.20 (95% CI, 1.56-3.11). For all outcomes, the Omicron BA.2 subvariants were significantly less severe than that of the Omicron and Delta variants. Conclusions and Relevance: In this cohort study, after having accounted for a variety of confounding factors associated with SARS-CoV-2 outcomes, the Omicron BA.2 subvariant was found to be intrinsically less severe than both the Delta and Omicron variants. With respect to these variants, the severity profile of SARS-CoV-2 appears to be diminishing after taking into account various factors including therapeutics, vaccinations, and prior infections.

Matching Methods for Confounder Adjustment: An Addition to the Epidemiologist's Toolbox.

Propensity score weighting and outcome regression are popular ways to adjust for observed confounders in epidemiologic research. Here, we provide an introduction to matching methods, which serve the same purpose but can offer advantages in robustness and performance. A key difference between matching and weighting methods is that matching methods do not directly rely on the propensity score and so are less sensitive to its misspecification or to the presence of extreme values. Matching methods offer many options for customization, which allow a researcher to incorporate substantive knowledge and carefully manage bias/variance trade-offs in estimating the effects of nonrandomized exposures. We review these options and their implications, provide guidance for their use, and compare matching methods with weighting methods. Because of their potential advantages over other methods, matching methods should have their place in an epidemiologist's methodological toolbox.

A Comparison of Hypofractionated and Twice-Daily Thoracic Irradiation in Limited-Stage Small-Cell Lung Cancer: An Overlap-Weighted Analysis.

Despite evidence for the superiority of twice-daily (BID) radiotherapy schedules, their utilization in practice remains logistically challenging. Hypofractionation (HFRT) is a commonly implemented alternative. We aim to compare the outcomes and toxicities in limited-stage small-cell lung cancer (LS-SCLC) patients treated with hypofractionated versus BID schedules. A bi-institutional retrospective cohort review was conducted of LS-SCLC patients treated with BID (45 Gy/30 fractions) or HFRT (40 Gy/15 fractions) schedules from 2007 to 2019. Overlap weighting using propensity scores was performed to balance observed covariates between the two radiotherapy schedule groups. Effect estimates of radiotherapy schedule on overall survival (OS), locoregional recurrence (LRR) risk, thoracic response, any ≥grade 3 (including lung, and esophageal) toxicity were determined using multivariable regression modelling. A total of 173 patients were included in the overlap-weighted analysis, with 110 patients having received BID treatment, and 63 treated by HFRT. The median follow-up was 20.4 months. Multivariable regression modelling did not reveal any significant differences in OS (hazard ratio [HR] 1.67, p = 0.38), LRR risk (HR 1.48, p = 0.38), thoracic response (odds ratio [OR] 0.23, p = 0.21), any ≥grade 3+ toxicity (OR 1.67, p = 0.33), ≥grade 3 pneumonitis (OR 1.14, p = 0.84), or ≥grade 3 esophagitis (OR 1.41, p = 0.62). HFRT, in comparison to BID radiotherapy schedules, does not appear to result in significantly different survival, locoregional control, or toxicity outcomes.