Citations

Importance Reduced heart rate during exercise is common and associated with impaired aerobic capacity in heart failure with preserved ejection fraction (HFpEF), but it remains unknown if restoring exertional heart rate through atrial pacing would be beneficial. Objective To determine if implanting and programming a pacemaker for rate-adaptive atrial pacing would improve exercise performance in patients with HFpEF and chronotropic incompetence. Design, Setting, and Participants Single-center, double-blind, randomized, crossover trial testing the effects of rate-adaptive atrial pacing in patients with symptomatic HFpEF and chronotropic incompetence at a tertiary referral center (Mayo Clinic) in Rochester, Minnesota. Patients were recruited between 2014 and 2022 with 16-week follow-up (last date of follow-up, May 9, 2022). Cardiac output during exercise was measured by the acetylene rebreathe technique. Interventions A total of 32 patients were recruited; of these, 29 underwent pacemaker implantation and were randomized to atrial rate responsive pacing or no pacing first for 4 weeks, followed by a 4-week washout period and then crossover for an additional 4 weeks. Main Outcomes and Measures The primary end point was oxygen consumption (V̇ o 2 ) at anaerobic threshold (V̇ o 2,AT ); secondary end points were peak V̇ o 2 , ventilatory efficiency (V̇ e /V̇ co 2 slope), patient-reported health status by the Kansas City Cardiomyopathy Questionnaire Overall Summary Score (KCCQ-OSS), and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels. Results Of the 29 patients randomized, the mean age was 66 years (SD, 9.7) and 13 (45%) were women. In the absence of pacing, peak V̇ o 2 and V̇ o 2 at anaerobic threshold (V̇ o 2,AT ) were both correlated with peak exercise heart rate ( r = 0.46-0.51, P < .02 for both). Pacing increased heart rate during low-level and peak exercise (16/min [95% CI, 10 to 23], P < .001; 14/min [95% CI, 7 to 21], P < .001), but there was no significant change in V̇ o 2,AT (pacing off, 10.4 [SD, 2.9] mL/kg/min; pacing on, 10.7 [SD, 2.6] mL/kg/min; absolute difference, 0.3 [95% CI, −0.5 to 1.0] mL/kg/min; P = .46), peak V̇ o 2 , minute ventilation (V̇ e) /carbon dioxide production (V̇ co 2 ) slope, KCCQ-OSS, or NT-proBNP level. Despite the increase in heart rate, atrial pacing had no significant effect on cardiac output with exercise, owing to a decrease in stroke volume (−24 mL [95% CI, −43 to −5 mL]; P = .02). Adverse events judged to be related to the pacemaker device were observed in 6 of 29 participants (21%). Conclusions and Relevance In patients with HFpEF and chronotropic incompetence, implantation of a pacemaker to enhance exercise heart rate did not result in an improvement in exercise capacity and was associated with increased adverse events. Trial Registration ClinicalTrials.gov Identifier: NCT02145351

Abstract Background: The prognostic value of stromal tumor-infiltrating lymphocytes (TILs) as a biomarker for triple-negative breast cancer (TNBC) has been extensively demonstrated in patients (pts) receiving (neo)adjuvant systemic therapy. In addition, several small studies suggest that a subset of pts with early-stage TNBC and high TILs have excellent long-term outcomes, even in the absence of systemic therapy [1-3]. However, data on the absolute risk of TNBC recurrence according to TIL levels in the absence of systemic therapy are limited and critical to inform the design of future systemic therapy de-escalation clinical trials. Methods: We conducted an individual patient data pooled analysis of 12 international cohorts of pts with TNBC treated with locoregional therapy but no systemic therapy. TNBC was defined as tumors with estrogen and progesterone receptor of < 1% and HER2 negative (IHC 0, 1+ or IHC 2+ and FISH negative) per local evaluation. TILs were locally assessed in hematoxylin & eosin-stained slides according to the International Immuno-Oncology Biomarker Working Group guidelines (www.tilsinbreastcancer.org). We used the Kaplan-Meier method to assess survival outcomes according to prespecified TIL thresholds: 30% and 50%. Confidence intervals (CI) for survival probabilities were calculated using a percentile bootstrap method. The primary endpoint was invasive disease-free survival (iDFS, STEEP 2.0 definition). Key secondary outcomes included recurrence-free survival (RFS), distant disease-free survival (DDFS) and overall survival (OS). Results: 1,835 pts diagnosed with TNBC between 1982 and 2017 who did not receive systemic therapy were included. The median age at diagnosis was 56 (IQR 38-71). Menopausal status was known in 1,184 women, of whom 78% were post-menopausal. The median tumor size was 2.0 cm (IQR 1.2-2.6). Most pts (87%) had no axillary lymph node involvement (N0). Most tumors were invasive ductal carcinoma (74%) and grade 3 (70%). The median level of TILs was 15% (IQR 5-40). The median duration of follow-up was 30.4 years (95% CI 29.9, 31.1). A total of 950 (52%) iDFS, 828 (45%) RFS, 767 (42%) DDFS events, and 604 (33%) deaths were observed. In multivariable analyses, higher TILs were independently associated with improved iDFS, RFS, DDFS, and OS beyond clinicopathological factors (likelihood ratio p< 10e-6). Each 10% increment in stromal TILs was associated with an 8% (95% CI: 6-11), 10% (95% CI: 7-13), and 13% (95% CI: 10-15) reduction in the risk of experiencing an iDFS, RFS or DDFS event, and with a 12% (95% CI: 9-15) reduction in the risk of death. iDFS, RFS, DDFS and OS rates according to different TIL thresholds and nodal status are shown in the Table. Of note, the RFS estimates (which exclude second non-breast primaries and contralateral breast cancers) were consistently higher than the iDFS counterparts (which include both), consistent with a high rate of contralateral breast cancers and second primary tumors in this cohort. Notably, patients with node-negative—and especially stage I—TNBC with high TILs had excellent survival rates at 10-year follow-up. Conclusion: TILs are highly prognostic in pts with systemically untreated early-stage TNBC. Pts with pN0 (and especially stage I) TNBC with high TILs exhibited very favorable long-term outcomes even in the absence of systemic therapy. These data define the natural history of TIL-rich TNBC pts and are crucial to identifying the optimal patient population for future chemotherapy and immunotherapy de-escalation clinical trials. References: [1] Leon-Ferre et al, 2017, PMID: 28913760 [2] Park et al, 2019, PMID: 31566659 [3] de Jong et al, 2022, PMID: 35353548 Table 5 and 10-year survival endpoints according TIL level, nodal status, and stage Citation Format: Roberto A. Leon-Ferre, Sarah Flora Jonas, Roberto Salgado, Sherene Loi, Vincent De Jong, Jodi M. Carter, Torsten Nielson, Samuel Leung, Nazia Riaz, Giuseppe Curigliano, Carmen Criscitiello, Vincent Cockenpot, Matteo Lambertini, Vera Suman, Barbro Linderholm, John WM Martens, Carolien HM van Deurzen, Mieke Timmermans, Tatsunori Shimoi, Shu Yazaki, Masayuki Yoshida, Sung-Bae Kim, Hee Jin Lee, Maria Vittoria Dieci, Guillaume Bataillon, Anne Salomon, Fabrice Andre, Marleen Kok, Sabine Linn, Matthew P. Goetz, Stefan Michiels. Stromal tumor-infiltrating lymphocytes identify early-stage triple-negative breast cancer patients with favorable outcomes at 10-year follow-up in the absence of systemic therapy: a pooled analysis of 1835 patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD9-05.

Abstract Background: Triple-negative breast cancers (TNBC) exhibit high rates of recurrence and mortality. However, recent studies suggest that a subset of patients (pts) with early-stage TNBC enriched in tumor-infiltrating lymphocytes (TILs) have excellent clinical outcomes even in the absence of systemic therapy. Additional histological biomarkers that could identify pts for future systemic therapy escalation/de-escalation strategies are of great interest. TNBC are frequently highly proliferative with abundant mitoses. However, classic markers of proliferation (manual mitosis counting and Ki-67) appear to offer no prognostic value. Here, we evaluated the prognostic effects of automated mitotic spindle hotspot (AMSH) counting on RFS in independent cohorts of systemically untreated early-stage TNBC. Methods: AMSH counting was conducted with a state-of-the-art deep learning algorithm trained on the detection of mitoses within 2 mm2 areas with the highest mitotic density (i.e. hotspots) in digital H&E images. Details of the development, training and validation of the algorithm were published previously [1] in a cohort of unselected TNBC. We obtained AMSH counts in a centrally confirmed TNBC cohort from Mayo Clinic [2] and focused our analysis on pts who received locoregional therapy but no systemic therapy. Using a fractional polynomial analysis with a multivariable proportional hazards regression model, we confirmed the assumption of linearity in the log hazard for the continuous variable AMSH and evaluated whether AMSH counts were prognostic of RFS. We corroborated our findings in an independent cohort of systemically untreated TNBC pts from the Radboud University Medical Center in the Netherlands (Radboud Cohort). Results are reported at a median follow-up of 8.1 and 6.7 years for the Mayo and Netherlands cohorts, respectively. Results: Among 182 pts with who did not receive systemic therapy in the Mayo Cohort, 140 (77%) with available AMSH counts were included. The mean age was 61 (range: 31-94), 71% were postmenopausal, 67% had tumors ≤ 2cm, and 83% were node-negative. As expected, most tumors were Nottingham grade 3 (84%) and had a high Ki-67 proliferation index (54% with Ki-67 >30%). Most tumors (73%) had stromal TILs ≤ 30%. The median AMSH count was 18 (IQR: 8, 42). AMSH counts were linearly associated with grade and tumor size, with the proportion of pts with grade 3 tumors and size > 2 cm increasing as the AMSH counts increased (p=0.007 and p=0.059, respectively). In a multivariate model controlling for nodal status, tumor size, and stromal TILs, AMSH counts were independently associated with RFS (p< 0.0001). For every 10-point increase in the AMSH count, we observed a 17% increase in the risk of experiencing an RFS event (HR 1.17, 95% CI 1.08-1.26). We corroborated our findings in the Radboud Cohort (n=126). The mean age was 68 (range: 40-96), and 81% were node-negative. While the median AMSH count was 36 (IQR: 16-63), higher than in the Mayo Cohort (p=0.004), the prognostic impact was similar, with a significant association between AMSH count and RFS (p=0.028) in a multivariate model corrected for nodal status, tumor size, and stromal TILs. For every 10-point increase in the AMSH count in the Netherlands cohort, we observed a 9% increase in the risk of experiencing an RFS event (HR 1.09, 95% CI 1.01-1.17). RFS rates according to AMSH counts for both cohorts are shown in the Table. Conclusions: AMSH counting is a new proliferation biomarker that provides prognostic value independent of nodal status, tumor size, and stromal TILs in systemically untreated early-stage TNBC. Plans are underway to evaluate AMSH counts in additional cohorts of systemically untreated TNBC, and in other disease settings such as prior to neoadjuvant systemic therapy. If validated, this biomarker should be prospectively evaluated as a potential selection biomarker in clinical trials of systemic therapy de-escalation. References: 1. PMID: 29994086 2. PMID: 28913760 Table RFS according to AMSH counts in the Mayo and Radboud Cohorts Citation Format: Roberto A. Leon-Ferre, Jodi M. Carter, David Zahrieh, Jason P. Sinnwell, Roberto Salgado, Vera Suman, David Hillman, Judy C. Boughey, Krishna R. Kalari, Fergus J. Couch, James N. Ingle, Maschenka Balkenkohl, Francesco Ciompi, Jeroen van der Laak, Matthew P. Goetz. Mitotic spindle hotspot counting using deep learning networks is highly associated with clinical outcomes in patients with early-stage triple-negative breast cancer who did not receive systemic therapy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-11-34.

The relationship between diabetes and coronavirus disease 2019 (COVID-19) is bidirectional: Although individuals with diabetes and high blood glucose (hyperglycemia) are predisposed to severe COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can also cause hyperglycemia and exacerbate underlying metabolic syndrome. Therefore, interventions capable of breaking the network of SARS-CoV-2 infection, hyperglycemia, and hyperinflammation, all factors that drive COVID-19 pathophysiology, are urgently needed. Here, we show that genetic ablation or pharmacological inhibition of mitochondrial pyruvate carrier (MPC) attenuates severe disease after influenza or SARS-CoV-2 pneumonia. MPC inhibition using a second-generation insulin sensitizer, MSDC-0602K (MSDC), dampened pulmonary inflammation and promoted lung recovery while concurrently reducing blood glucose levels and hyperlipidemia after viral pneumonia in obese mice. Mechanistically, MPC inhibition enhanced mitochondrial fitness and destabilized hypoxia-inducible factor–1α, leading to dampened virus-induced inflammatory responses in both murine and human lung macrophages. We further showed that MSDC enhanced responses to nirmatrelvir (the antiviral component of Paxlovid) to provide high levels of protection against severe host disease development after SARS-CoV-2 infection and suppressed cellular inflammation in human COVID-19 lung autopsies, demonstrating its translational potential for treating severe COVID-19. Collectively, we uncover a metabolic pathway that simultaneously modulates pulmonary inflammation, tissue recovery, and host metabolic health, presenting a synergistic therapeutic strategy to treat severe COVID-19, particularly in patients with underlying metabolic disease.

Anxiety is associated with development of cardiovascular disease. Although the sympathetic nervous system is a likely mediator of this relationship, populations with chronic anxiety have shown little, if any, alteration in resting levels of directly recorded muscle sympathetic nerve activity (MSNA). The present study is the first to reveal an independent relationship between trait anxiety, resting blood pressure, and MSNA in a large cohort of healthy males and females devoid of cardiometabolic comorbidities.

Abstract Aims The current guidelines recommend aortic valve intervention in patients with severe aortic regurgitation (AR) with the onset of symptoms, left ventricular enlargement, or systolic dysfunction. Recent studies have suggested that we might be missing the window of early intervention in a significant number of patients by following the guidelines. Methods and results The overarching goal was to determine if machine learning (ML)-based algorithms could be trained to identify patients at risk for death from AR independent of aortic valve replacement (AVR). Models were trained with five-fold cross-validation on a dataset of 1035 patients, and performance was reported on an independent dataset of 207 patients. Optimal predictive performance was observed with a conditional random survival forest model. A subset of 19/41 variables was selected for inclusion in the final model. Variable selection was performed with 10-fold cross-validation using random survival forest model. The top variables included were age, body surface area, body mass index, diastolic blood pressure, New York Heart Association class, AVR, comorbidities, ejection fraction, end-diastolic volume, and end-systolic dimension, and the relative variable importance averaged across five splits of cross-validation in each repeat were evaluated. The concordance index for predicting survival of the best-performing model was 0.84 at 1 year, 0.86 at 2 years, and 0.87 overall, respectively. Conclusion Using common echocardiographic parameters and patient characteristics, we successfully trained multiple ML models to predict survival in patients with severe AR. This technique could be applied to identify high-risk patients who would benefit from early intervention, thereby improving patient outcomes.

BACKGROUND Neuromuscular choristoma (NMC) is a rare congenital lesion in which muscle tissue is admixed with nerve fascicles within a peripheral nerve. Patients commonly present in early childhood with neuropathy, plexopathy, or chronic undergrowth in the distribution of the affected nerve. OBSERVATIONS The authors present the case of a 35-year-old man with unrecognized neuromuscular NMC of the sciatic nerve, which resulted in recurrent, multicentric NMC-associated desmoid-type fibromatosis (NMC-DTF) within the nerve territory in association with a Marjolin ulcer, a cutaneous malignancy. LESSONS Based on anatomical and pathophysiological findings described in this case report, the authors support the association between NMC-DTF and Marjolin ulcer.

AbstractIntroduction/AimsIn the Diabetes Control and Complications Trial (DCCT), the minimal nerve conduction (NC) criterion for diabetic sensorimotor polyneuropathy (DSPN) was abnormality of NC in more than one peripheral nerve without specifying the attributes of NCs to be evaluated. In the present study, we assess individual and composite scores of NCs meeting the DCCT criterion and signs for improved diagnosis and assessment of DSPN severity.MethodsEvaluated were 13 attributes and 6 composite NC scores and signs and symptoms in 395 healthy subjects (HS) and 388 persons with diabetes (DM).ResultsPercent abnormality between subjects with DM and HS was remarkably different among individual attributes and the six composite NC scores. For diagnosis of DSPN using the DCCT criterion, assessment of conduction velocities (CVs) and distal latencies (DLs) provided sensitive diagnoses of DSPN. NC amplitudes provided stronger measures of severity. In studied cohorts, DSPN was staged: N0, no NC abnormality using NC score 2 (CVs and DLs), 60.0%; N1, NC abnormality only, 18.4%; N2, NC abnormality and signs of feet or legs, 16.3%; and N3, NC abnormality and signs of thighs, 5.3%.DiscussionFor sensitive and standard diagnosis of DSPN using the DCCT NC criterion, specifically defined composite scores of CVs and DLs, e.g., score 2, is recommended. A composite score of amplitudes, e.g., score 4, provides a stronger measure of neuropathy severity. Also, provided are HS reference values of evaluated attributes of NCs and estimates of staged severity of DSPN of mid North American DM cohorts.

Abstract Aims Current non-invasive screening methods for cardiac allograft rejection have shown limited discrimination and are yet to be broadly integrated into heart transplant care. Given electrocardiogram (ECG) changes have been reported with severe cardiac allograft rejection, this study aimed to develop a deep-learning model, a form of artificial intelligence, to detect allograft rejection using the 12-lead ECG (AI-ECG). Methods and results Heart transplant recipients were identified across three Mayo Clinic sites between 1998 and 2021. Twelve-lead digital ECG data and endomyocardial biopsy results were extracted from medical records. Allograft rejection was defined as moderate or severe acute cellular rejection (ACR) based on International Society for Heart and Lung Transplantation guidelines. The extracted data (7590 unique ECG-biopsy pairs, belonging to 1427 patients) was partitioned into training (80%), validation (10%), and test sets (10%) such that each patient was included in only one partition. Model performance metrics were based on the test set (n = 140 patients; 758 ECG-biopsy pairs). The AI-ECG detected ACR with an area under the receiver operating curve (AUC) of 0.84 [95% confidence interval (CI): 0.78–0.90] and 95% (19/20; 95% CI: 75–100%) sensitivity. A prospective proof-of-concept screening study (n = 56; 97 ECG-biopsy pairs) showed the AI-ECG detected ACR with AUC = 0.78 (95% CI: 0.61–0.96) and 100% (2/2; 95% CI: 16–100%) sensitivity. Conclusion An AI-ECG model is effective for detection of moderate-to-severe ACR in heart transplant recipients. Our findings could improve transplant care by providing a rapid, non-invasive, and potentially remote screening option for cardiac allograft function.