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Background: Clinically significant tricuspid regurgitation (TR) is an important contributor to morbidity and mortality. The Tricuspid Regurgitation Impact on Outcomes (TRIO) score based on 8 parameters (age, gender, chronic heart failure, chronic lung disease, heart rate, creatinine, aspartate transaminase level, and TR severity) is used for risk stratification. The performance of the TRIO score in patients with TR secondary to severe pulmonary hypertension (PH) is unknown. Research Questions: To evaluate whether the TRIO score can be applied in patients with TR and pulmonary hypertension (PH), and to identify other predictors of mortality. Methods: Retrospective study including patients with TR ≥ moderate. Severe PH was defined as right ventricular systolic pressure (RVSP) ≥50 mmHg. The impact of clinical, echocardiographic and laboratory variables on mortality was evaluated with the Cox proportional hazard method. Results: A total of 13,482 patients from the TRIO population were included; severe PH was present in 6,530 (48.4%); mean age 73.4 + 13.3, 55.7% females. TRIO score performance was modest (AUC 0.62) in risk stratification (Figure A). PH patients had significantly higher mortality than those without PH at all levels of TRIO score (Figure B); differences were progressively lower with increasing TRIO scores. At multivariate analysis, only TRIO score [HR = 1.54 (1.35-1.77) per unit change], presence of an elevated NT-proBNP [HR = 1.02 (1.02-1.03) per 1000 pg/ml change], RVSP (HR = 1.08 (1.02-1.16) per 10 mmHg change], presence of RV dysfunction [HR = 1.15, (1.05-1.26)] and pulmonary artery pulsatility index (PAPi) ≤ 4 [HR = 1.34 (1.07-1.67)] were significant predictors of mortality (model AUC 0.65). Conclusions: TRIO score allows risk stratification in PH patients, but performance is modest; incorporating additional factors marginally increased model performance. PH patients have higher mortality at all levels of TRIO score, more so at low scores.

Introduction: Isolated functional tricuspid regurgitation (FTR) in the absence of structural heart disease may develop secondary to elevation in left heart pressures caused by left ventricular diastolic dysfunction (DD), as in heart failure with preserved ejection fraction (HFpEF). FTR may also herald the presence of occult DD or indicate greater risk for new-onset DD. However, prevalence and incidence of diastolic dysfunction (DD) in isolated FTR have not been studied. Aims: Investigate the prevalence and incidence of DD across the different severities of FTR of unclear cause. Methods: Adults with normal EF and without structural heart disease undergoing echocardiography at a tertiary medical center with a repeat study ≥6 months from baseline were identified. Severe DD was defined by ≥3/4 abnormal DD parameters (medial e’, medial E/e’, tricuspid regurgitation velocity, left atrial volume index) and moderate DD by ≥2. Results: Among 30,428 patients (median age 60; 50% women), FTR was absent in 73%, mild in 22%, moderate in 4%, and severe in 0.4%. Severe DD was present in 2%, 5%, 11%, and 13% patients, respectively, (p<.001) and moderate DD in 9%, 19%, 31%, and 48%, respectively (p<.001). The association of DD with increasing FTR was independent of all clinical characteristics. Over median 3.0 (IQR 1.5-5.4) years, incident severe and moderate DD developed more frequently with increasing FTR severity ( Figure) . Findings were confirmed in a propensity-matched subset where patients were matched for age, sex, BMI, atrial fibrillation, and comorbidities and in patients without lung disease or ≥moderate right ventricular enlargement. Conclusions: Patients with FTR of undefined etiology commonly have DD suggesting the presence of underlying left heart disease. Patients without apparent DD or HF at baseline who have FTR remain at significantly increased risk of developing DD over follow-up and may be a target population for therapies to prevent progression to clinical HFpEF.

Abstract Background The disease severity index (DSI) for inflammatory bowel disease (IBD) combines measures of disease phenotype, inflammatory activity, and patient-reported outcomes. We aimed to validate the DSI and assess its utility in predicting a complicated IBD course. Methods A multicenter cohort of adults with IBD was recruited. Intraclass correlation coefficients (ICCs) and weighted Kappa assessed inter-rater reliability. Cronbach’s alpha measured internal consistency of DSI items. Spearman’s rank correlations compared the DSI with endoscopic indices, symptom indices, quality of life, and disability. A subgroup was followed for 24 months to assess for a complicated IBD course. Area under the receiver operating characteristics curve (AUROC) and multivariable logistic regression assessed the utility of the DSI in predicting disease progression. Results Three hundred and sixty-nine participants were included (Crohn’s disease [CD], n = 230; female, n = 194; mean age, 46 years [SD, 15]; median disease duration, 11 years [interquartile range, 5-21]), of which 171 (CD, n = 99; ulcerative colitis [UC], n = 72) were followed prospectively. The DSI showed inter-rater reliability for CD (ICC 0.93, n = 65) and UC (ICC 0.97, n = 33). The DSI items demonstrated inter-rater agreement (Kappa &gt; 0.4) and internal consistency (CD, α &gt; 0.59; UC, α &gt; 0.75). The DSI was significantly associated with endoscopic activity (CDn=141, r = 0.65, P &lt; .001; UCn=105, r = 0.80, P &lt; .001), symptoms (CDn=159, r = 0.69, P &lt; .001; UCn=132, r = 0.58, P &lt; .001), quality of life (CDn=198, r = −0.59, P &lt; .001; UCn=128, r = −0.68, P &lt; .001), and disability (CDn=83, r = −0.67, P &lt; .001; UCn=52, r = −0.74, P &lt; .001). A DSI of 23 best predicted a complicated IBD course (AUROC = 0.82, P &lt; .001) and was associated with this end point on multivariable analyses (aOR, 9.20; 95% confidence interval, 3.32-25.49). Conclusions The DSI reliably encapsulates factors contributing to disease severity and accurately prognosticates the longitudinal IBD course.

High dose chemotherapy followed by autologous hematopoietic cell transplantation (auto HCT) is a standard therapy for patients with plasma cell disorders (PCD). A barrier to improving candidate selection for auto HCT is appraisal of risk for transplant related complications. Electrocardiography (ECG) is a standard pre-HCT test to evaluate the potential for arrhythmia and structural heart disease. We hypothesized that an artificial intelligence (AI) based interpretation of ECG waveform data (AI-ECG) could enhance risk prediction for cardiac-specific and other outcomes following auto HCT for patients with PCD. To test this hypothesis, we used several AI-ECG tools developed using a deep-learning based approach that were trained to predict comorbidity (Attia et al, Lancet 2019 & Grogan et al, Mayo Clin Proc 2021). Model outputs include a scaled prediction value indicating increasing risk for atrial fibrillation/flutter (AF), reduced ejection fraction (EF), or cardiac amyloidosis. We evaluated this tool in 9,225 ECGs obtained from 849 patients (median 6 ECGs/patient, inter-quartile range: 3-12) who underwent first or subsequent auto HCT at Memorial Sloan Kettering Cancer Center between 2016-2022 and who had a diagnosis of multiple myeloma (N = 810), amyloidosis (N = 37), or other PCD (N = 2). The endpoints were to determine whether baseline AI-ECG prediction of AF risk correlated with peri-transplant AF events, and to explore whether model outputs correlated with survival and other cardiac clinical outcomes. The mean age of patients was 61.0 years (range 23.7 - 81.2) and median follow up was 2.7 years post auto HCT. Contributing cardiovascular risk factors included a prior history of AF (N = 101, 11.9%), coronary or cerebrovascular disease (N = 95, 11.2%), and diabetes mellitus (N = 98, 11.5%). Reduced dose melphalan (&lt; 200 mg/m 2) was administered in 26%. The HCT-comorbidity index (HCT-CI) was high risk (≥3) in 52.7%. The one-year overall survival and progression-free survival in the whole cohort was 94% (95% confidence interval (95% CI): 92 - 95%) and 86% (84 - 89%), respectively. Among patients not in AF at pre HCT evaluation, the 90-day cumulative incidence of AF was 5.6% (4.2 - 7.3%). In univariable competing risk regression, baseline pre HCT AI-ECG appraisal of AF risk was strongly correlated with incidence AF in patients who were in sinus rhythm before HCT (hazard ratio (HR): 25.1, 95% CI: 11.7 - 53.7, p &lt; 0.001). In a multivariable model adjusting for patient age and HCT-CI, AI-ECG AF predicted risk remained associated with incidence of post HCT AF (HR: 13.4, 95% CI: 5.9 - 30.4, p &lt; 0.001). Considering a decision threshold identified during original model training, AI-ECG predicted AF events with an accuracy of 75% (Mcnemar's p &lt; 2 x 10 -16). The precision, recall, and F1-score were 0.94, 0.77, and 0.85, respectively. AI-ECG predicted age correlated highly with actual patient age (Spearman rho = 0.59, p &lt; 2 x 10 -16). Amyloid risk scores were highly correlated with a known clinical history of amyloidosis (median 0.45 versus 0.05, Wilcoxon rank-sum p &lt; 0.001). Patients with EF &lt; 50% had greater prediction scores for cardiomyopathy compared to patients with normal EF (median 0.23 versus 0.01, Wilcoxon rank-sum p &lt;0.001). In univariable analysis, increasing AI-ECG predicted age (HR 1.02, CI: 1.003 - 1.04, p = 0.02) and predicted AF risk score (HR: 3.2, CI: 1.4 - 7.2, p = 0.006) were associated with risk for death, whereas predicted amyloid score and predicted low EF were not associated with decreased survival. In multivariable analysis of all patients that considered patient age, hematopoietic comorbidity index, and remission status at HCT, increasing predicted AF score trended towards association with increased risk for death (HR: 2.3, 95%CI: 1.0 - 5.5, p = 0.059). Predicted AF score correlated highly with the HCT-CI and patient age. Finally, we examined whether risk prediction for low EF correlated with peri-HCT fluid overload (FO) defined by absolute weight gain. The incidence of ≥ 10% weight gain (grade 2 FO) and ≥ 20% weight gain (grade 3 FO) at 180 days post HCT was 7.4% (95% CI: 5.8%, 9.3%) and 1.0% (95% CI: 0.5%, 1.8%), respectively. Predicted low EF was not associated with development of either grade 2 or grade 3 FO in this population. In summary, AI-ECG predicts episodes of AF in patients undergoing auto HCT for PCD and may augment transplant risk appraisal when considered in conjunction with other measures of comorbidity.

Introduction HMAs are the only approved therapy for CMML. In order to improve response rates and survival, the addition of VEN has been utilized in both CMML and after blast transformation (CMML-BT) with conflicting results in small single center studies. To clarify the role of upfront HMA+VEN in CMML and CMML-BT, we performed a large multicenter analysis. Methods We included patients with HMA-naïve CMML and CMML-BT treated with combination HMA and VEN from 4 academic centers. The primary outcome was overall survival (OS) with secondary outcomes including overall response rate (ORR) by 2015 MDS/MPN IWG criteria for CMML and 2022 ELN criteria for CMML-BT. To better appreciate the benefit of adding VEN to HMA treatment, we also performed 1:1 propensity score matched (PSM) analysis of patients treated with HMA alone as upfront therapy for CMML or CMML-BT. Matching was based on age, sex, ECOG performance status, CPSS-Mol, blood counts, peripheral and bone marrow blasts. Results Eighty-nine patients were treated with frontline HMA+VEN, 51 CMML and 38 CMML-BT (5 had received HMA alone for prior CMML). The median age was 71 years, 70% were male, and 83% had ECOG 0-1. Among CMML patients, 55% had MP-CMML subtype, 65% had CMML-2 and 12%, 30%, 58% were CPSS-mol intermediate-1, intermediate-2 and high risk, respectively. In the entire cohort, ASXL1 (63%), TET2 (47%), SRSF2 (39%) and RUNX1 (27%) were the most commonly mutated genes and 55% of patients harbored a RAS mutation ( KRAS [20%], NRAS [18%], CBL [13%], NF1 [11%], PTPN11 [9%]). For HMA combination partner, 46 (52%) were treated with azacitidine, 35 (39%) with decitabine, and 8 (9%) with both during their VEN course. During a median follow-up time of 15.8 months (mos) 52 patients (58%) died: 23 (45%) with CMML and 29 (76%) with CMML-BT. Among CMML patients, the ORR was 90%, including complete remission (CR) in 22%, complete cytogenic remission (CCR) in 4%, optimal marrow response (CMR) in 50%, and partial marrow response (PMR) in 6%. The OS of CMML patients was 25.1 mo (95% CI 15.7 - NR). A PSM population of HMA patients matched to HMA+VEN treated patients showing similar baseline characteristics. ORR was significantly higher with HMA+VEN (95%) as compared those treated with HMA alone (46%), p &lt; 0.001. However, there was no significant OS difference between HMA+VEN vs HMA alone (19.1 mos vs 19.1 mos, p = 0.85, Figure 1). For CMML-BT patients, the ORR of HMA+VEN was 81% including CR in 17%, CR with partial hematologic recover (CRh) in 3%, CR with incomplete hematologic recovery (CRi) in 28%, morphologic leukemia-free state (MLFS) in 22% and partial response (PR) in 11%. The OS of CMML-BT patients was 8 mos (95% CI 4.6 - 26.2). A PSM population of CMML-BT patients treated with HMA alone showed a significantly increased ORR with HMA+VEN (82% vs 40%, p = 0.039). However, there was no difference in OS (7.49 mos vs 9.26 mos, p = 0.83, Figure 2). Among HMA-VEN treated patients, achievement of a CR was associated with an improved OS in the CMML (HR 0.31, 95% CI 0.13 - 0.75) and CMML-BT (HR 0.37, 95% CI 0.19 - 0.74). No predictors of response were identified, including the presence of a RAS mutation. In terms of safety, 7 patients (7.9%) had a grade 3/4 (G3/4) neutropenic infection and 2 patients (2.2%) had a G3/4 hemorrhagic event while being treated with HMA+VEN. A total of 29 patients went on to receive allogeneic transplant (alloSCT): 22 (43%) with CMML and 7 (18%) with CMML-BT. CMML patients who underwent alloSCT after HMA+VEN were younger as compared to non-transplanted patients (64 vs 74 years, p &lt; 0.0001), but had otherwise similar baseline characteristics including stage, CPSS-mol category and prevalence of RAS mutations. Similarly, CMML-BT patients bridged to alloSCT were younger (66 vs 74 years, p &lt; 0.002) and had a better ECOG performance status (p = 0.047). Of patients who received alloSCT, 10 patients (34%) died, 5 with CMML and 5 with CMML-BT. The median OS after alloSCT was 26.7 mo. Conclusions Although the use of VEN with HMA in the upfront treatment of CMML and AML secondary to CMML results in higher response rates compared to HMA alone, this combination does not improve survival based on this multi-center PSM analysis. The current sample size of CMML-BT may limit detection of OS differences between treatment groups. The role of VEN to reduce blasts and serve as a bridge to alloSCT, particularly after HMA failure, requires further investigation in larger studies in both the CMML and CMML-BT populations.

Abstract The long-term physiological consequences of SARS-CoV-2, termed Post-Acute Sequelae of COVID-19 (PASC), are rapidly evolving into a major public health concern. The underlying cellular and molecular etiology remain poorly defined but growing evidence links PASC to abnormal immune responses and/or poor organ recovery post-infection. Yet, the precise mechanisms driving non-resolving inflammation and impaired tissue repair in the context of PASC remain unclear. With insights from three independent clinical cohorts of PASC patients with abnormal lung function and/or viral infection-mediated pulmonary fibrosis, we established a clinically relevant mouse model of post-viral lung sequelae to investigate the pathophysiology of respiratory PASC. By employing a combination of spatial transcriptomics and imaging, we identified dysregulated proximal interactions between immune cells and epithelial progenitors unique to the fibroproliferation in respiratory PASC but not acute COVID-19 or idiopathic pulmonary fibrosis (IPF). Specifically, we found a central role for lung-resident CD8+ T cell macrophage interactions in maintaining Krt8hi transitional and ectopic Krt5+ basal cell progenitors, thus impairing alveolar regeneration and driving fibrotic sequelae after acute viral pneumonia. Mechanistically, CD8+ T cell derived IFN-γ and TNF stimulated lung macrophages to chronically release IL-1β, resulting in the abnormal accumulation of dysplastic epithelial progenitors and fibrosis. Notably, therapeutic neutralization of IFN-γ and TNF, or IL-1β after the resolution of acute infection resulted in markedly improved alveolar regeneration and restoration of pulmonary function. Together, our findings implicate a dysregulated immune-epithelial progenitor niche in driving respiratory PASC. Moreover, in contrast to other approaches requiring early intervention, we highlight therapeutic strategies to rescue fibrotic disease in the aftermath of respiratory viral infections, addressing the current unmet need in the clinical management of PASC and post-viral disease.