The impact of abortion restrictions on American mental health.

The overturning of Roe v. Wade has led to numerous states enacting new abortion restrictions. However, limited empirical evidence exists regarding the general mental health impact of these bans. Leveraging the nationwide Household Pulse Survey, we evaluate the impact of emergent gestational limits and outright bans on self-reported mental health status between July 2021 and June 2023 using a difference in difference approach. Responses indicate a significant increase in reports of mental distress after the institution of such restrictions. These effects appear to persist at least 4 months following a ban and are moderated by household income and education but not by sex, race, age, marital status, or sexual orientation. Less educated and less wealthy subjects reported greater mental health distress compared to wealthier, more educated groups. These results suggest that the institution of abortion restrictions has had broad negative implications for the mental health of people living in the US, particularly those of lower education and personal wealth.

Demographic and Clinical Factors Associated With SARS-CoV-2 Spike 1 Antibody Response Among Vaccinated US Adults: the C4R Study.

This study investigates correlates of anti-S1 antibody response following COVID-19 vaccination in a U.S. population-based meta-cohort of adults participating in longstanding NIH-funded cohort studies. Anti-S1 antibodies were measured from dried blood spots collected between February 2021-August 2022 using Luminex-based microsphere immunoassays. Of 6245 participants, mean age was 73 years (range, 21-100), 58% were female, and 76% were non-Hispanic White. Nearly 52% of participants received the BNT162b2 vaccine and 48% received the mRNA-1273 vaccine. Lower anti-S1 antibody levels are associated with age of 65 years or older, male sex, higher body mass index, smoking, diabetes, COPD and receipt of BNT16b2 vaccine (vs mRNA-1273). Participants with a prior infection, particularly those with a history of hospitalized illness, have higher anti-S1 antibody levels. These results suggest that adults with certain socio-demographic and clinical characteristics may have less robust antibody responses to COVID-19 vaccination and could be prioritized for more frequent re-vaccination.

Nonlinear associations between computed tomography-measures of adiposity and long pentraxin-3 in the Multi-Ethnic Study of Atherosclerosis.

Objective: Long pentraxin-3 (PTX-3) is an acute phase protein associated with cardiovascular disease, lung injury, and mortality. We evaluated the association between computed tomography (CT)-measurements of adipose tissue and plasma levels of PTX-3. Methods: We performed a cross-sectional analysis of community-dwelling adults enrolled in the multi-center Multiethnic Study of Atherosclerosis who underwent cardiac or abdominal CT and had available PTX-3 measurements. Results: There was a U-shaped association between pericardial adipose tissue volume (PAT), abdominal visceral adipose tissue area (VAT), hepatic attenuation, and PTX-3 levels, with extremes of adiposity associated with greater PTX-3 levels. Using multivariable-adjusted piecewise regression models, among participants with low PAT, every 1% increase in PAT volume was associated with a 13.8% decrease in PTX-3 (95% confidence interval [CI] -21.6 to -6.0); among participants with high PAT, every 1% increase in PAT volume was associated with a 6.0% increase in PTX-3 (95% CI -0.4 to 12.5). Results were similar for abdominal VAT and hepatic attenuation. Conclusions: In a cohort of community-dwelling adults, we demonstrated a "U-shaped" association between pericardial, abdominal visceral, and hepatic adiposity with PTX3 levels, suggesting that extreme adiposity is associated with greater circulating levels of PTX3. Further work is required to identify the mechanisms linking adiposity and PTX-3.

Provider beliefs and practices regarding the management of obesity in lung transplant recipients.

Obesity at the time of lung transplant is associated with decreased survival. How providers manage obesity after lung transplantation is unknown. We performed an international survey of lung transplant providers to assess beliefs and practices regarding post-transplant obesity management. Eighty-one providers initiated the survey and 73 (90%) completed the full survey. Respondents were primarily North American-based pulmonary physicians. Nearly all providers believe treating obesity improves quality of life (99%) and survival (95%) after lung transplantation, but that only 41% of patients attempting weight loss are successful. While respondents nearly always recommend diet (96%), exercise (92%), and dietician consultation (89%), they less frequently recommend prescription weight loss medications (29%) or bariatric surgery (11%). Lung transplant providers are motivated to treat obesity in transplant recipients. However, there is a gap between general obesity treatment guidelines and lung transplant practice. Additional training, education, and trials in this population could address this gap.

Scoring donor lungs for graft failure risk: The Lung Donor Risk Index (LDRI).

Lung transplantation lags behind other solid organ transplants in donor lung utilization due, in part, to uncertainty regarding donor quality. We sought to develop an easy-to-use donor risk metric that, unlike existing metrics, accounts for a rich set of donor factors. Our study population consisted of n = 26 549 adult lung transplant recipients abstracted from the United Network for Organ Sharing Standard Transplant Analysis and Research file. We used Cox regression to model graft failure (GF; earliest of death or retransplant) risk based on donor and transplant factors, adjusting for recipient factors. We then derived and validated a Lung Donor Risk Index (LDRI) and developed a pertinent online application (https://shiny.pmacs.upenn.edu/LDRI_Calculator/). We found 12 donor/transplant factors that were independently predictive of GF: age, race, insulin-dependent diabetes, the difference between donor and recipient height, smoking, cocaine use, cytomegalovirus seropositivity, creatinine, human leukocyte antigen (HLA) mismatch, ischemia time, and donation after circulatory death. Validation showed the LDRI to have GF risk discrimination that was reasonable (C = 0.61) and higher than any of its predecessors. The LDRI is intended for use by transplant centers, organ procurement organizations, and regulatory agencies and to benefit patients in decision-making. Unlike its predecessors, the proposed LDRI could gain wide acceptance because of its granularity and similarity to the Kidney Donor Risk Index.

Development and validation of primary graft dysfunction predictive algorithm for lung transplant candidates.

BACKGROUND: Primary graft dysfunction (PGD) is the leading cause of early morbidity and mortality after lung transplantation. Accurate prediction of PGD risk could inform donor approaches and perioperative care planning. We sought to develop a clinically useful, generalizable PGD prediction model to aid in transplant decision-making. METHODS: We derived a predictive model in a prospective cohort study of subjects from 2012 to 2018, followed by a single-center external validation. We used regularized (lasso) logistic regression to evaluate the predictive ability of clinically available PGD predictors and developed a user interface for clinical application. Using decision curve analysis, we quantified the net benefit of the model across a range of PGD risk thresholds and assessed model calibration and discrimination. RESULTS: The PGD predictive model included distance from donor hospital to recipient transplant center, recipient age, predicted total lung capacity, lung allocation score (LAS), body mass index, pulmonary artery mean pressure, sex, and indication for transplant; donor age, sex, mechanism of death, and donor smoking status; and interaction terms for LAS and donor distance. The interface allows for real-time assessment of PGD risk for any donor/recipient combination. The model offers decision-making net benefit in the PGD risk range of 10% to 75% in the derivation centers and 2% to 10% in the validation cohort, a range incorporating the incidence in that cohort. CONCLUSION: We developed a clinically useful PGD predictive algorithm across a range of PGD risk thresholds to support transplant decision-making, posttransplant care, and enrich samples for PGD treatment trials.

The Impact of Donor Smoking on Primary Graft Dysfunction and Mortality after Lung Transplantation.

Rationale: Primary graft dysfunction (PGD) is the leading cause of early morbidity and mortality after lung transplantation. Prior studies implicated proxy-defined donor smoking as a risk factor for PGD and mortality. Objectives: We aimed to more accurately assess the impact of donor smoke exposure on PGD and mortality using quantitative smoke exposure biomarkers. Methods: We performed a multicenter prospective cohort study of lung transplant recipients enrolled in the Lung Transplant Outcomes Group cohort between 2012 and 2018. PGD was defined as grade 3 at 48 or 72 hours after lung reperfusion. Donor smoking was defined using accepted thresholds of urinary biomarkers of nicotine exposure (cotinine) and tobacco-specific nitrosamine (4-[methylnitrosamino]-1-[3-pyridyl]-1-butanol [NNAL]) in addition to clinical history. The donor smoking-PGD association was assessed using logistic regression, and survival analysis was performed using inverse probability of exposure weighting according to smoking category. Measurements and Main Results: Active donor smoking prevalence varied by definition, with 34-43% based on urinary cotinine, 28% by urinary NNAL, and 37% by clinical documentation. The standardized risk of PGD associated with active donor smoking was higher across all definitions, with an absolute risk increase of 11.5% (95% confidence interval [CI], 3.8% to 19.2%) by urinary cotinine, 5.7% (95% CI, -3.4% to 14.9%) by urinary NNAL, and 6.5% (95% CI, -2.8% to 15.8%) defined clinically. Donor smoking was not associated with differential post-lung transplant survival using any definition. Conclusions: Donor smoking associates with a modest increase in PGD risk but not with increased recipient mortality. Use of lungs from smokers is likely safe and may increase lung donor availability. Clinical trial registered with www.clinicaltrials.gov (NCT00552357).

Impact of age and telomere length on circulating T cells and rejection risk after lung transplantation for idiopathic pulmonary fibrosis.

BACKGROUND: Most idiopathic pulmonary fibrosis (IPF) lung transplant recipients (IPF-LTRs) have short telomere (ST) length. Inherited mutations in telomere-related genes are associated with the development of T cell immunodeficiency. Despite this, IPF-LTRs with telomere-related rare variants are not protected from acute cellular rejection (ACR). We set out to determine the impact of both age and telomere length on the circulating T cell compartment and ACR burden of IPF-LTRs. METHODS: We identified 106 IPF-LTRs who had telomere length testing using flowFISH (57 with short telomeres and 49 with long telomeres) as well as a subset from both cohorts who had cryopreserved PBMC at least 1 time point, 6 months posttransplantation. Circulating T cells from before transplantation and at 6 and 12 months posttransplantation were analyzed using multiparameter flow cytometry to study phenotype and functional capacity, and bulk T cell receptor sequencing was performed to study repertoire diversity. Linear regression was used to study the relationship of age and telomere length on early (within 1 year) and late (between 1 and 2 years) ACR. RESULTS: IPF-LTRs with ST were found to have premature "aging" of their circulating T cell compartment, with age-agnostic elevations in posttransplant terminal differentiation of CD8+ T cells, increased granzyme B positivity of both CD8+ and CD4+ T cells, upregulation of the exhaustion marker, CD57, and chemotactic protein CCR5, and enhanced T cell receptor clonal expansion. Additionally, we found a significant decline in early ACR burden with increasing age, but only in the ST cohort. CONCLUSIONS: IPF-LTRs with ST have premature "aging" of their circulating T cell compartment posttransplantation and a clear age-related decline in ACR burden.

Mortality in Patients with Obesity and Acute Respiratory Distress Syndrome Receiving Extracorporeal Membrane Oxygenation: The Multicenter ECMObesity Study.

Rationale: Patients with obesity are at increased risk for developing acute respiratory distress syndrome (ARDS). Some centers consider obesity a relative contraindication to receiving extracorporeal membrane oxygenation (ECMO) support, despite growing implementation of ECMO for ARDS in the general population. Objectives: To investigate the association between obesity and mortality in patients with ARDS receiving ECMO. Methods: In this large, international, multicenter, retrospective cohort study, we evaluated the association of obesity, defined as body mass index ⩾ 30 kg/m2, with ICU mortality in patients receiving ECMO for ARDS by performing adjusted multivariable logistic regression and propensity score matching. Measurements and Main Results: Of 790 patients with ARDS receiving ECMO in our study, 320 had obesity. Of those, 24.1% died in the ICU, compared with 35.3% of patients without obesity (P < 0.001). In adjusted models, obesity was associated with lower ICU mortality (odds ratio, 0.63 [95% confidence interval, 0.43-0.93]; P = 0.018). Examined as a continuous variable, higher body mass index was associated with decreased ICU mortality in multivariable regression (odds ratio, 0.97 [95% confidence interval, 0.95-1.00]; P = 0.023). In propensity score matching of 199 patients with obesity to 199 patients without, patients with obesity had a lower probability of ICU death than those without (22.6% vs. 35.2%; P = 0.007). Conclusions: Among patients receiving ECMO for ARDS, those with obesity had lower ICU mortality than patients without obesity in multivariable and propensity score matching analyses. Our findings support the notion that obesity should not be considered a general contraindication to ECMO.

Transplanting candidates with stacked risks negatively affects outcomes.

BACKGROUND: Lung transplant (LT) centers are increasingly evaluating patients with multiple risk factors for adverse outcomes. The effects of these stacked risks remains unclear. Our aim was to determine the relationship between the number of comorbidities and post-transplant outcomes. METHODS: We performed a retrospective cohort study using the National Inpatient Sample (NIS) and UNOS Starfile (USF). We applied a probabilistic matching algorithm using 7 variables (transplant: month, year, and type; recipient: age, sex, race, payer). We matched recipients in the USF to transplant patients in the NIS between 2016 and 2019. The Elixhauser methodology was used to identify comorbidities present on admission. We determined the associations between mortality, length of stay (LOS), total charges, and disposition with comorbidity numbers using penalized cubic splines, Kaplan-Meier, and linear and logistic regression methods. RESULTS: From 28,484,087 NIS admissions, we identified 1,821 LT recipients. Matches were exact in 76.8% of the cohort. While the remaining cohort had a probability match of ≥0.94. Penalized splines of Elixhauser comorbidity number identified 3 knots defining 3 groups of stacked risk: low (<3), medium (3-6), and high risk (>6). Inpatient mortality increased from low to medium to high-risk categories: (1.6%, 3.9%, and 7.0%; p < 0.001), as did LOS (16, 21, 29 days, p < 0.001), total charges ($553,057, $666,791, $821,641.5; p = 0.004) and discharge to a skilled nursing facility (15%, 20%, 31%; p < 0.001). CONCLUSIONS: Stacked risks adversely affect post-LT mortality, LOS, charges, and discharge disposition. Further study to understand the details of specific stacked risks is warranted.

Fibrotic-Like Pulmonary Radiographic Patterns Are Not Associated With Adverse Outcomes in COVID-19 Chronic Critical Illness.

OBJECTIVES: Pulmonary fibrosis is a feared complication of COVID-19. To characterize the risks and outcomes associated with fibrotic-like radiographic abnormalities in patients with COVID-19-related acute respiratory distress syndrome (ARDS) and chronic critical illness. DESIGN: Single-center prospective cohort study. SETTING: We examined chest CT scans performed between ICU discharge and 30 days after hospital discharge using established methods to quantify nonfibrotic and fibrotic-like patterns. PATIENTS: Adults hospitalized with COVID-19-related ARDS and chronic critical illness (> 21 d of mechanical ventilation, tracheostomy, and survival to ICU discharge) between March 2020 and May 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We tested associations of fibrotic-like patterns with clinical characteristics and biomarkers, and with time to mechanical ventilator liberation and 6-month survival, controlling for demographics, comorbidities, and COVID-19 therapies. A total of 141 of 616 adults (23%) with COVID-19-related ARDS developed chronic critical illness, and 64 of 141 (46%) had a chest CT a median (interquartile range) 66 days (42-82 d) after intubation. Fifty-five percent had fibrotic-like patterns characterized by reticulations and/or traction bronchiectasis. In adjusted analyses, interleukin-6 level on the day of intubation was associated with fibrotic-like patterns (odds ratio, 4.40 per quartile change; 95% CI, 1.90-10.1 per quartile change). Other inflammatory biomarkers, Sequential Organ Failure Assessment score, age, tidal volume, driving pressure, and ventilator days were not. Fibrotic-like patterns were not associated with longer time to mechanical ventilator liberation or worse 6-month survival. CONCLUSIONS: Approximately half of adults with COVID-19-associated chronic critical illness have fibrotic-like patterns that are associated with higher interleukin-6 levels at intubation. Fibrotic-like patterns are not associated with longer time to liberation from mechanical ventilation or worse 6-month survival.

Body Mass Index and Cause-Specific Mortality after Lung Transplantation in the United States.

Rationale: Low and high body mass index (BMI) are associated with increased mortality after lung transplantation. Why extremes of BMI might increase risk of death is unknown. Objectives: To estimate the association of extremes of BMI with causes of death after transplantation. Methods: We performed a retrospective study of the United Network for Organ Sharing database, including 26,721 adults who underwent lung transplantation in the United States between May 4, 2005, and December 2, 2020. We mapped 76 reported causes of death into 16 distinct groups. We estimated cause-specific hazards for death from each cause using Cox models. Results: Relative to a subject with a BMI of 24 kg/m2, a subject with a BMI of 16 kg/m2 had 38% (hazard ratio [HR], 1.38; 95% confidence interval [95% CI], 0.99-1.90), 82% (HR, 1.82; 95% CI, 1.34-2.46), and 62% (HR, 1.62; 95% CI, 1.18-2.22) increased hazards of death from acute respiratory failure, chronic lung allograft dysfunction (CLAD), and infection, respectively, and a subject with a BMI of 36 kg/m2 had 44% (HR, 1.44; 95% CI, 0.97-2.12), 42% (HR, 1.42; 95% CI, 0.93-2.15), and 185% (HR, 2.85; 95% CI, 1.28-6.33) increased hazards of death from acute respiratory failure, CLAD, and primary graft dysfunction, respectively. Conclusions: Low BMI is associated with increased risk of death from infection, acute respiratory failure, and CLAD after lung transplantation, whereas high BMI is associated with increased risk of death from primary graft dysfunction, acute respiratory failure, and CLAD.

Development of the Lung Transplant Frailty Scale (LT-FS).

BACKGROUND: Existing measures of frailty developed in community dwelling older adults may misclassify frailty in lung transplant candidates. We aimed to develop a novel frailty scale for lung transplantation with improved performance characteristics. METHODS: We measured the short physical performance battery (SPPB), fried frailty phenotype (FFP), Body Composition, and serum Biomarkers representative of putative frailty mechanisms. We applied a 4-step established approach (identify frailty domain variable bivariate associations with the outcome of waitlist delisting or death; build models sequentially incorporating variables from each frailty domain cluster; retain variables that improved model performance ability by c-statistic or AIC) to develop 3 candidate "Lung Transplant Frailty Scale (LT-FS)" measures: 1 incorporating readily available clinical data; 1 adding muscle mass, and 1 adding muscle mass and research-grade Biomarkers. We compared construct and predictive validity of LT-FS models to the SPPB and FFP by ANOVA, ANCOVA, and Cox proportional-hazard modeling. RESULTS: In 342 lung transplant candidates, LT-FS models exhibited superior construct and predictive validity compared to the SPPB and FFP. The addition of muscle mass and Biomarkers improved model performance. Frailty by all measures was associated with waitlist disability, poorer HRQL, and waitlist delisting/death. LT-FS models exhibited stronger associations with waitlist delisting/death than SPPB or FFP (C-statistic range: 0.73-0.78 vs. 0.57 and 0.55 for SPPB and FFP, respectively). Compared to SPPB and FFP, LT-FS models were generally more strongly associated with delisting/death and improved delisting/death net reclassification, with greater improvements with increasing LT-FS model complexity (range: 0.11-0.34). For example, LT-FS-Body Composition hazard ratio for delisting/death: 6.0 (95%CI: 2.5, 14.2), SPPB HR: 2.5 (95%CI: 1.1, 5.8), FFP HR: 4.3 (95%CI: 1.8, 10.1). Pre-transplant LT-FS frailty, but not SPPB or FFP, was associated with mortality after transplant. CONCLUSIONS: The LT-FS is a disease-specific physical frailty measure with face and construct validity that has superior predictive validity over established measures.

Subphenotypes of frailty in lung transplant candidates.

Heterogeneous frailty pathobiology might explain the inconsistent associations observed between frailty and lung transplant outcomes. A Subphenotype analysis could refine frailty measurement. In a 3-center pilot cohort study, we measured frailty by the Short Physical Performance Battery, body composition, and serum biomarkers reflecting causes of frailty. We applied latent class modeling for these baseline data. Next, we tested class construct validity with disability, waitlist delisting/death, and early postoperative complications. Among 422 lung transplant candidates, 2 class model fit the best (P = .01). Compared with Subphenotype 1 (n = 333), Subphenotype 2 (n = 89) was characterized by systemic and innate inflammation (higher IL-6, CRP, PTX3, TNF-R1, and IL-1RA); mitochondrial stress (higher GDF-15 and FGF-21); sarcopenia; malnutrition; and lower hemoglobin and walk distance. Subphenotype 2 had a worse disability and higher risk of waitlist delisting or death (hazards ratio: 4.0; 95% confidence interval: 1.8-9.1). Of the total cohort, 257 underwent transplant (Subphenotype 1: 196; Subphenotype 2: 61). Subphenotype 2 had a higher need for take back to the operating room (48% vs 28%; P = .005) and longer posttransplant hospital length of stay (21 days [interquartile range: 14-33] vs 18 days [14-28]; P = .04). Subphenotype 2 trended toward fewer ventilator-free days, needing more postoperative extracorporeal membrane oxygenation and dialysis, and higher need for discharge to rehabilitation facilities (P ≤ .20). In this early phase study, we identified biological frailty Subphenotypes in lung transplant candidates. A hyperinflammatory, sarcopenic Subphenotype seems to be associated with worse clinical outcomes.

Obstructive Sleep Apnea and Longitudinal Changes in Interstitial Lung Imaging and Lung Function: The MESA Study.

Rationale: Obstructive sleep apnea (OSA) has been hypothesized to be a risk factor in interstitial lung disease (ILD) and is associated with radiological markers that may represent the earlier stages of ILD. Prior studies have been limited by their cross-sectional design and potential confounding by body habitus. Objectives: To test the hypothesis that OSA severity is associated with more high-attenuation areas (HAAs) on computed tomography and worse lung function over time among older community-dwelling adults. Methods: We used data from participants in the MESA (Multi-Ethnic Study of Atherosclerosis) who had apnea-hypopnea index (AHI) measured from polysomnography (2010-2013), high attenuation areas (HAAs, -600 to -250 Hounsfield units, n = 784), assessments from exams 5 (2010-2012) and 6 (2016-2018) full-lung computed tomography scans, and spirometry assessments (n = 677). Linear mixed-effects models with random intercept were used to examine associations of OSA severity (i.e., AHI and hypoxic burden) with changes in HAAs, total lung volumes, and forced vital capacity (FVC) between exams 5 and 6. Potential confounders were adjusted for in the model, including age, sex, smoking history, height, and weight. Results: Among those with a higher AHI there were more men and a higher body mass index. Participants with AHI ⩾ 15 events/h and in the highest hypoxic burden quartile each had increases in HAAs of 11.30% (95% confidence interval [CI], 3.74-19.35%) and 9.85% (95% CI, 1.40-19.01%) per 10 years, respectively. There was a more rapid decline in total lung volumes imaged and FVC among those with AHI ⩾ 15 events/h of 220.2 ml (95% CI, 47.8-392.5 ml) and 3.63% (95% CI, 0.43-6.83%) per 10 years, respectively. Conclusions: A greater burden of hypoxia related to obstructive events during sleep was associated with increased lung densities over time and a more rapid decline in lung volumes regardless of body habitus. Our findings suggest OSA may be a contributing factor in the early stages of ILD.

MUC5B, telomere length and longitudinal quantitative interstitial lung changes: the MESA Lung Study.

BACKGROUND: The MUC5B promoter variant (rs35705950) and telomere length are linked to pulmonary fibrosis and CT-based qualitative assessments of interstitial abnormalities, but their associations with longitudinal quantitative changes of the lung interstitium among community-dwelling adults are unknown. METHODS: We used data from participants in the Multi-Ethnic Study of Atherosclerosis with high-attenuation areas (HAAs, Examinations 1-6 (2000-2018)) and MUC5B genotype (n=4552) and telomere length (n=4488) assessments. HAA was defined as the per cent of imaged lung with attenuation of -600 to -250 Hounsfield units. We used linear mixed-effects models to examine associations of MUC5B risk allele (T) and telomere length with longitudinal changes in HAAs. Joint models were used to examine associations of longitudinal changes in HAAs with death and interstitial lung disease (ILD). RESULTS: The MUC5B risk allele (T) was associated with an absolute change in HAAs of 2.60% (95% CI 0.36% to 4.86%) per 10 years overall. This association was stronger among those with a telomere length below an age-adjusted percentile of 5% (p value for interaction=0.008). A 1% increase in HAAs per year was associated with 7% increase in mortality risk (rate ratio (RR)=1.07, 95% CI 1.02 to 1.12) for overall death and 34% increase in ILD (RR=1.34, 95% CI 1.20 to 1.50). Longer baseline telomere length was cross-sectionally associated with less HAAs from baseline scans, but not with longitudinal changes in HAAs. CONCLUSIONS: Longitudinal increases in HAAs were associated with the MUC5B risk allele and a higher risk of death and ILD.

Rationing scarce healthcare capacity: A study of the ventilator allocation guidelines during the COVID-19 pandemic.

In the United States, even though national guidelines for allocating scarce healthcare resources are lacking, 26 states have specific ventilator allocation guidelines to be invoked in case of a shortage. While several states developed their guidelines in response to the recent COVID-19 pandemic, New York State developed these guidelines in 2015 as "pandemic influenza is a foreseeable threat, one that we cannot ignore." The primary objective of this study is to assess the existing procedures and priority rules in place for allocating/rationing scarce ventilator capacity and propose alternative (and improved) priority schemes. We first build machine learning models using inpatient records of COVID-19 patients admitted to New York-Presbyterian/Columbia University Irving Medical Center and an affiliated community health center to predict survival probabilities as well as ventilator length-of-use. Then, we use the resulting point estimators and their uncertainties as inputs for a multiclass priority queueing model with abandonments to assess three priority schemes: (i) SOFA-P (Sequential Organ Failure Assessment based prioritization), which most closely mimics the existing practice by prioritizing patients with sufficiently low SOFA scores; (ii) ISP (incremental survival probability), which assigns priority based on patient-level survival predictions; and (iii) ISP-LU (incremental survival probability per length-of-use), which takes into account survival predictions and resource use duration. Our findings highlight that our proposed priority scheme, ISP-LU, achieves a demonstrable improvement over the other two alternatives. Specifically, the expected number of survivals increases and death risk while waiting for ventilator use decreases. We also show that ISP-LU is a robust priority scheme whose implementation yields a Pareto-improvement over both SOFA-P and ISP in terms of maximizing saved lives after mechanical ventilation while limiting racial disparity in access to the priority queue.