Citations

Abstract Funding Acknowledgements Type of funding sources: None. Aims. Combined cardiopulmonary exercise test (CPET) and exercise stress echocardiography (ESE) provides a non-invasive tool to study cardiopulmonary pathophysiology. We analyzed how cardiac functional reserve during exercise relates to peak oxygen consumption (VO2). Methods and Results. We performed a symptom-limited graded ramp bicycle CPET-ESE in 30 healthy controls and 357 patients: 113 at risk of developing heart failure (American College of Cardiology/American Heart Association HF Stages A-B) and 244 in HF Stage C with preserved (HFpEF, n = 101) or reduced ejection fraction (HFrEF, n = 143). Peak VO2 significantly decreased from controls to Stage A-B and Stage C (Table 1). A multivariable regression model to predict peak VO2 revealed peak left ventricular systolic annulus tissue velocity (S"), peak TAPSE/PAPs (tricuspid annular plane systolic excursion/systolic pulmonary artery pressure) and low-load left atrial reservoir strain/E/e’ were independent predictors, in addition to peak heart rate, stroke volume and workload (adjusted R²=0.76, p < 0.0001). The model was successfully tested in subjects with atrial fibrillation (n = 49), and with (n = 224) and without (n = 163) beta-blockers (all p < 0.01). Peak S’ showed the highest accuracy in predicting peak VO2 < 10 mL/kg/min (cut-point ≤ 7.5 cm/s; AUC = 0.92, p < 0.0001) and peak VO2 > 20 mL/kg/min (cut-point > 12.5 cm/s; AUC = 0.84, p < 0.0001) in comparison to the other cardiac variables of the model (p < 0.05). Conclusions. A model incorporating different measures of cardiac mechanics is strongly related to peak aerobic capacity and may help in identifying different causes of effort intolerance from HF Stage A to C. Table 1 Variable Overall population (n = 387) Controls (n = 30) Stage A-B (n = 113) Stage C-HFpEF (n = 101) Stage c-HFrEF (n = 143) p-value Age, years 68.9 ± 11.1 67.1 ± 10.6 67.7 ± 10.4 70.5 ± 10.1 68.5 ± 11 0.1 Male, n (%) 247 (64) 18 (60) 70 (62) 57 (56) 102 (71) 0.1 VO2 @peak, mL/min/kg 15.7 (12.1-19.6) 23 (21.7- 29.7) 18 (15.4- 20.7)* 13.6 (11.8- 16.8)*† 14.2 (10.7- 17.5)*† <0.0001 Workload @peak, W 90 (65-120) 130 (115-195) 110 (84-130)* 70 (55-100)*† 80 (60-110)*† <0.0001 Heart rate @peak, bpm 123 ± 22 142 ± 12 130 ± 20* 115 ± 17*† 119 ± 23*† <0.0001 Stroke volume @peak, mL 83 (71-99) 98 (85-114) 86 (76-107) 83 (74-97)* 75 (63-95)*† <0.0001 Average S" @peak, cm/s 11.2 ± 3.8 17.1 ± 3.9 13.3 ± 2.9* 10.6 ± 2.5*† 8.7 ± 2.7*†‡ <0.0001 TAPSE/PAPs @peak, mm/mmHg 0.75 (0.46-0.97) 1.05 (0.93- 1.16) 0.81 (0.52- 0.91)* 0.52 (0.38- 0.83)*† 0.58 (0.41- 0.89)*† <0.0001 Left atrial reservoir strain/E/e" @low-load, % 2.25 (1.17-5.04) 6.23 (4.45-6.77) 4.34 (3.89- 5.58)* 2.23 (1.31- 2.86)*† 1.91 (1.07-2.44)*†‡ <0.0001 * p < 0.01 vs Controls; † p < 0.01 vs Stage A-B; ‡ p < 0.01 vs Stage C-HFpEF. PAPs systolic pulmonary artery pressure; TAPSE: tricuspid annular plane systolic excursion; VO2: oxygen consumption. Abstract Figure 1

Abstract Funding Acknowledgements Type of funding sources: None. Aims. We tested the prognostic role of a risk score including bio-humoral evaluation, cardiopulmonary-echocardiographic stress (CPET-ESE) and lung ultrasound, in patients with heart failure (HF) with reduced and preserved ejection fraction (HFrEF and HFpEF), and subjects at risk of developing HF (American College of Cardiology/American Heart Association Stages A and B). Methods and results. We evaluated 318 subjects: 94 in Stages A-B, 194 in Stage C (85 HFpEF and 109 HFrEF), and 30 age and sex-matched controls (Stage 0). During a median follow-up of 18.5 months, we reported 40 urgent HF visits, 31 HF hospitalisations and 10 cardiovascular deaths. Cox proportional-hazards regression for predicting adverse events identified five independent predictors and each was assigned a number of points proportional to its regression coefficient: Δstress-rest B-lines >10 (3 points), peak oxygen consumption <16 mL/kg/min (2 points), minute ventilation/carbon dioxide production slope ≥36 (2 points), peak systolic pulmonary artery pressure ≥50 mmHg (1 point) and resting N-terminal pro-brain natriuretic peptide (NT-proBNP) >900 pg/mL (1 point). We defined three risk categories: low-risk (<3 points), intermediate-risk (3-6 points), and high-risk (>6 points). The event-free survival probability for these three groups were 93%, 52% and 20%, respectively. Hazard Ratio was 4.55 for each risk category upgrade (95% confidence interval [CI], 3.44-5.93). The area-under-curve for the scoring system to predict events was 0.92 (95% CI 0.88-0.96). Conclusion. A multiparametric risk score including indices of exercise-induced pulmonary congestion, markers of cardiopulmonary dysfunction and NT-proBNP identifies patients at increased risk for HF events across the HF spectrum. Table 1 Variable EPYC score EPYC score <3 (low risk) n = 217 EPYC score 3-6 (intermediate risk) n = 70 EPYC score >6 (high risk) n = 31 p-value (between risk categories) Event-free (n = 244) 0 (0 - 2) 210 (97) 32 (46) 2 (6) <0.0001 With events (n = 74) 6 (4 - 9) 7 (3) 38 (54) 29 (94) <0.0001 p-value (event-free vs with events) <0.0001 <0.0001 <0.0001 <0.0001 Stage 0-Controls (n = 30) 0 (0 - 1) 30 0 0 <0.0001 Stages A-B (n = 94) 1 (0 - 2) 85 (45) 6 (9) 3 (10) <0.0001 Stage C-HFpEF (n = 85) 3 (1 - 6)*† 46 (25) 29 (41) 10 (32) <0.0001 Stage C-HFrEF (n = 109) 4 (2 - 7)*† 56 (30) 35 (50) 18 (58) <0.0001 p-value (between HF Stages) <0.0001 <0.0001 <0.0001 <0.0001 Values are mean ± standard deviation, n (%), or median [25th quartile, 75th quartile]. * p < 0.01 vs Stage 0-Controls; † p < 0.01 vs Stages A-B. Abstract Figure 1

Background: The association between obesity and prognosis in HER2-positive early breast cancer remains unclear, with limited data available. This study aimed to determine the impact of body mass index (BMI) at baseline and weight change after 2 years on outcomes of patients with HER2-positive early breast cancer. Methods: ALTTO was a randomized phase III trial in patients with HER2-positive early breast cancer. BMI was collected at randomization and 2 years after. WHO BMI categories were used: underweight, <18.5 kg/m2; normal weight, 18.5 to <25 kg/m2; overweight, ≥25 to <30 kg/m2; and obese ≥30 kg/m2. A weight change from baseline of ≥5.0% and ≤5.0% was categorized as weight gain and weight loss. The impact of BMI at randomization and of weight change on disease-free survival (DFS), distant disease-free survival (DDFS), and overall survival (OS) were investigated with multivariate analyses, adjusting for baseline patients and tumor characteristics. Results: A total of 8,381 patients were included: 187 (2.2%), 3,797 (45.3%), 2,690 (32.1%), and 1,707 (20.4%) were underweight, normal weight, overweight, and obese at baseline, respectively. Compared with normal weight, being obese at randomization was associated with a significantly worse DDFS (adjusted hazard ratio [aHR], 1.25; 95% CI, 1.04–1.50) and OS (aHR, 1.27; 95% CI, 1.01–1.60), but no significant difference in DFS (aHR, 1.14; 95% CI, 0.97–1.32). Weight loss ≥5.0% at 2 years after randomization was associated with significantly poorer DFS (aHR, 1.34; 95% CI, 1.05–1.71), DDFS (aHR, 1.46; 95% CI, 1.07–1.98), and OS (aHR, 1.83; 95% CI, 1.18–2.84). Hormone receptor and menopausal status but not anti-HER2 treatment type influenced outcomes. Toxicities were more frequent in obese patients. Conclusions: In patients with HER2-positive early breast cancer, obesity at baseline is a poor prognostic factor. Weight loss during treatment and follow-up negatively impacts clinical outcomes. Dietary counseling should be part of survivorship care programs.

Introduction: Light chain deposition disease (LCDD) is a rare complication of monoclonal gammopathies, defined by non-amyloid linear monoclonal light chain (most commonly kappa) deposits in the kidney and other organs. The rarity of LCDD has hampered clinical studies and staging systems and response criteria are lacking. The International Kidney Myeloma Working Group (IKMG) started a clinical data collection from all participating centers in order to define the natural history of LCDD, and to establish prognostic factors and response criteria in a large, international, unselected patient population. Methods: Eight referral centers have yet participated in the data collection at the data lock of July 31, 2020. Patient inclusion is ongoing and expected accrual is 500 patients. The diagnosis of LCDD had to be biopsy-proven. The patients were diagnosed between 1992 to 2020. Response was assessed 6 months after treatment initiation according to the criteria used in light chain (AL) amyloidosis. Renal survival (RS) was defined as time from diagnosis to dialysis or last follow-up. Patients who died without requiring dialysis were censored at the time of death. The analysis of factors predicting RS was performed in patients whose baseline estimated glomerular filtration rate (eGFR) was &gt;15 mL/min. The cutoffs of baseline variables, as well as the cutoffs measured at the time of response, best predicting RS or OS at 12 months were identified by means of Receiver Operator Characteristics (ROC) analyses. All patients gave written informed consent for their clinical data to be used for research purposes. Results: Overall, 359 patients have been included in this first analysis. Sixteen (4%) subjects had concomitant cast nephropathy. The main clinical characteristics are reported in the Table. Median overall survival (OS) was 13 years and RS was 12 years (Figure1 A and 1B) and median survival of living patients is 4.5 years. At univariate analysis the only baseline variables predicting RS were proteinuria [best cutoff 2.5 g/24h, HR 2.25 (95%CI 1.13-4.60), P=0.02], and eGFR [best cutoff &gt;30 mL/min, HR 0.50 (95%CI 0.26-0.96) P=0.037], but at multivariate analysis only proteinuria predicted RS [HR 2.17 (95% CI 1.08, 4.33), P=0.027]. At univariate analysis, a higher bone marrow plasma cell infiltrate (best cutoff ≥20%) at diagnosis was associated with a significantly lower OS [HR 1.96 (95% CI 1.23-3.13) P=0.004], as was having end stage renal disease (ESRD) defined as an eGFR &lt;15 mL/min [HR 1.81 (95%CI 1.11-2.92) P=0.015]. We then tested the ability of the hematologic response criteria for AL amyloidosis to discriminate groups with different survival after treatment in a 6 months landmark analysis. Our choice of adopting the amyloidosis response criteria was corroborated by the results of the ROC analysis showing that the difference between involved and uninvolved free light chains (dFLC) cutoff (40 mg/L) used in AL amyloidosis to define very good partial response (VGPR) had 87% sensitivity and 65% specificity in identifying patients who needed dialysis within 12 months. Partial response (PR, 19% requiring dialysis at 3 years) was not associated with a RS benefit over no-response (29% requiring dialysis at 3 years, P=0.511). However, VGPR conferred a significant RS advantage (10% requiring dialysis at 3 years) over PR (P=0.002). No significant difference in RS was seen between complete response (CR, 0% requiring dialysis at 3 years) and VGPR (P=0.178). Thus, achieving VGPR or CR by amyloidosis response criteria [post-treatment dFLC&lt;40 mg/L (VGPR by AL criteria), with or without negative serum and urine immunofixation and normal FLC-ratio (CR by AL criteria)] was adopted as a provisional criterion for hematologic response in LCDD (Figure 1D). LCDD response was also associated with prolonged OS (Figure 1C). Conclusions: Almost one-third of patients with LCDD are diagnosed when they already have ESRD resulting in shorter OS. The degree of proteinuria and of bone marrow plasma cell infiltration predict RS and OS, respectively. Achievement of post treatment dFLC &lt;40 mg/L or negative serum and urine immunofixation at 6 months is proposed as a provisional criterion for hematologic response, being able to predict both improved RS and OS. Planned expanded recruitment might allow a validation analysis of the results, the analysis of organ response data and the evaluation of different time-points for response assessment. Disclosures Milani: Celgene: Other: Travel support; Janssen: Other: Speaker honoraria; Pfizer: Other: Speaker honoraria. Kastritis:Pfizer: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Genesis Pharma: Consultancy, Honoraria. Schönland:Janssen, Prothena, Takeda: Honoraria, Other: travel support to meetings, Research Funding. Bridoux:Baxter: Consultancy; Janssen: Honoraria; Celgene: Honoraria. Tuchman:Celgene: Honoraria, Research Funding, Speakers Bureau; Oncopeptides: Consultancy; Amgen: Research Funding; Caelum: Honoraria; Sanofi: Honoraria, Research Funding; Janssen: Research Funding; Roche: Research Funding; Karyopharm: Honoraria, Research Funding. Jimenez-Zepeda:Janssen, Celgene, Amgen, Takeda: Honoraria. Palladini:Jannsen Cilag: Honoraria, Other; Celgene: Other: Travel support. Wechalekar:Celgene: Honoraria; Caelum: Other: Advisory; Janssen: Honoraria, Other: Advisory; Takeda: Honoraria, Other: Travel.

Introduction: MF is a clonal stem cell disorder characterized by progressive bone marrow failure, extramedullary hematopoiesis, and debilitating constitutional symptoms. Approximately 60% of pts develop anemia within a year of diagnosis; pts who are transfusion dependent have worse survival and quality-of-life outcomes (Tefferi A, et al. Mayo Clin Proc 2012;87:25-33). Treatment for MF-associated anemia remains critically unaddressed, with no approved therapies available. Luspatercept is a first-in-class erythroid maturation agent that has been shown to increase hemoglobin and reduce transfusion burden in pts with myelodysplastic syndromes (Fenaux P, et al. N Engl J Med 2020;382:140-51) and β-thalassemia (Cappellini MD, et al. N Engl J Med 2020;382:1219-31). Pts have also achieved multiple response episodes with luspatercept (Fenaux P, et al. Blood 2019;134:841). We previously reported findings from the ongoing open-label, phase 2 ACE-536-MF-001 trial evaluating luspatercept in pts with MF-associated anemia (Gerds AT, et al. Blood 2019;134:557). Here we report updated study results, focusing on response in pts requiring RBC transfusions. Methods: 79 pts with MF and anemia were enrolled (Figure). Of these, 43 were requiring RBC transfusions, defined as 6-12 U/84 d prior to treatment, or 4-12 U/84 d for the 3 expansion cohort pts. Pts in Cohort 3B received a stable ruxolitinib (RUX) dose for ≥ 16 wks (40 wks for expansion cohort pts), whereas Cohort 2 pts did not (Figure). Pts in Cohort 3B received a median RUX dose of 20 mg/d (range 5-40) for a median of 73 wks (range 29-359) prior to treatment. Pts received luspatercept every 21 d at a starting dose of 1.0 mg/kg (1.33 mg/kg for 3 expansion cohort pts in Cohort 3B), with doses escalating up to 1.75 mg/kg; 81% and 50% of pts in Cohorts 2 and 3B escalated to 1.75 mg/kg. Primary endpoint for pts receiving transfusions was RBC transfusion-independence (RBC-TI) for ≥ 12 consecutive wks within the first 24 wks on study. However, as responses were observed that did not fall within the 24-wk response window, additional assessments were conducted for the entire treatment duration for RBC-TI and ≥ 50% decrease in RBC transfusions (minimum 4 RBC U decrease) from baseline. Intent-to-treat data were analyzed as of March 29, 2020. Results: Pts in Cohorts 2 and 3B received a median of 8 cycles of luspatercept (range 1-39), for a median (mean) duration of 24 (31) and 23 (39) wks, respectively. Pts in Cohorts 2 and 3B received a median of 2.7 RBC U/28 d (range 1-5) and 2.7 RBC U/28 d (range 2-4), respectively. For the primary endpoint, 2/21 (10%) and 6/22 (27%) pts receiving transfusions in Cohorts 2 and 3B achieved RBC-TI over any consecutive 12 wks during the first 24 wks. Median time to start of first RBC-TI response period in Cohorts 2 and 3B was 1.5 days and 37 days; median duration of response was 49 wks (range 16-82) and 42 wks (range 12-111), respectively. When assessing the entire treatment period, 4/21 (19%) and 8/22 (36%) pts in Cohorts 2 and 3B achieved RBC-TI ≥ 12 wks, respectively. 25% of the RBC-TI responders in both cohorts experienced 2 separate episodes of RBC-TI ≥ 12 wks. Median cumulative duration of all individual ≥ 12-wk response episodes of RBC-TI was 59 wks (range 24-82) in Cohort 2 and 55 wks (range 12-116) in Cohort 3B. 8/21 (38%) and 10/22 (46%) pts in Cohorts 2 and 3B achieved a ≥ 50% reduction in RBC transfusion burden (minimum ≥ 4 U reduction) over 12 wks; of these, 38% and 20% of responders in Cohorts 2 and 3B experienced 2 separate ≥ 12-wk response episodes, and 1 pt (13%) in Cohort 2 experienced 3 separate responses. 4/15 (27%) and 8/14 (57%) pts in Cohorts 2 and 3B who reached 24 wks of treatment achieved clinical benefit and therefore continued luspatercept on an ongoing basis. Safety is reported for all 79 pts on study. 5 (6%) pts had grade 3-4 treatment-related adverse events (AEs); these AEs were diarrhea (n = 2), dehydration (n = 1), and hypertension (n = 3). There were no treatment-related deaths. Treatment-related AEs (any grade) occurring in ≥ 5% of pts were hypertension (13%), bone pain (9%), and diarrhea (5%). 8 (10%) pts had ≥ 1 AE leading to discontinuation. 16 (20%) pts remain on treatment. Conclusions: These longer-term findings suggest durable activity of luspatercept in pts with MF-associated anemia. In addition, a quarter of pts receiving transfusions achieved more than one ≥ 12-wk episode of RBC-TI response with luspatercept. The incidence of grade 3-4 AEs with luspatercept was low. Disclosures Gerds: Roche/Genentech: Research Funding; Celgene: Consultancy, Research Funding; Sierra Oncology: Research Funding; AstraZeneca/MedImmune: Consultancy; Incyte Corporation: Consultancy, Research Funding; Pfizer: Research Funding; Apexx Oncology: Consultancy; CTI Biopharma: Consultancy, Research Funding; Gilead Sciences: Research Funding; Imago Biosciences: Research Funding. Vannucchi:Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Blueprint: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Incyte: Membership on an entity's Board of Directors or advisory committees. Passamonti:Novartis: Speakers Bureau; BMS: Speakers Bureau; Roche: Other: Support of parent study and funding of editorial support. Kremyanskaya:Constellation Pharmaceuticals: Research Funding; Incyte Corporation: Research Funding; Bristol Myers Squibb: Research Funding; Protagonist Therapeutics: Consultancy, Research Funding; Astex Pharmaceuticals: Research Funding. Gotlib:CTI Biopharma: Research Funding; Kartos: Consultancy, Honoraria, Research Funding; Incyte: Consultancy, Honoraria, Research Funding; Roche: Honoraria, Research Funding; BMS: Research Funding. McCaul:BMS: Speakers Bureau; Seattle Genetics: Speakers Bureau; Karyopharm: Speakers Bureau; Incyte: Speakers Bureau. Ribrag:argenX: Research Funding; pharmamar: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; servier: Consultancy; nanostring: Honoraria, Membership on an entity's Board of Directors or advisory committees; gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; AZD: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other; Infinity: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; MSD: Honoraria, Membership on an entity's Board of Directors or advisory committees; gustave roussy comprehensive cancer center: Current Employment; EPZ: Honoraria, Membership on an entity's Board of Directors or advisory committees; epizyme (EPZ): Research Funding. Mead:Novartis: Consultancy, Honoraria, Other: travel, accommodations, expenses, Research Funding, Speakers Bureau; Celgene/BMS: Consultancy, Honoraria, Other: travel, accommodations, expenses, Research Funding; Abbvie: Consultancy; CTI: Consultancy; Gilead: Consultancy. Harrison:Roche: Honoraria; Gilead Sciences: Honoraria, Speakers Bureau; Incyte Corporation: Speakers Bureau; Janssen: Speakers Bureau; CTI Biopharma Corp: Honoraria, Speakers Bureau; Sierra Oncology: Honoraria; Celgene: Honoraria, Research Funding, Speakers Bureau; Shire: Honoraria, Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau; AOP Orphan Pharmaceuticals: Honoraria; Promedior: Honoraria. Mesa:Sierra Oncology: Consultancy; LaJolla Pharmaceutical Company: Consultancy; Novartis: Consultancy; Incyte: Research Funding; CTI BioPharma: Research Funding; Genentech: Research Funding; AbbVie: Research Funding; Promedior: Research Funding; Bristol Myers Squibb: Research Funding; Samus Therapeutics: Research Funding. Kiladjian:AbbVie: Membership on an entity's Board of Directors or advisory committees; AOP Orphan: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Barosi:Bristol Myers Squibb: Consultancy. Gerike:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Shetty:BMS: Current Employment, Current equity holder in publicly-traded company. Pariseau:Bristol Myers Squibb: Current Employment. Miranda:Bristol Myers Squibb: Current Employment. Schwickart:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Giuseppi:BMS: Current Employment, Current equity holder in publicly-traded company. Zhang:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Backstrom:Acceleron Pharma: Current Employment, Current equity holder in publicly-traded company; BMS: Current equity holder in publicly-traded company. Verstovsek:AstraZeneca: Research Funding; Roche: Research Funding; CTI Biopharma Corp: Research Funding; Genentech: Research Funding; Incyte Corporation: Consultancy, Research Funding; NS Pharma: Research Funding; Novartis: Consultancy, Research Funding; PharmaEssentia: Research Funding; ItalPharma: Research Funding; Sierra Oncology: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Blueprint Medicines Corp: Research Funding; Promedior: Research Funding; Gilead: Research Funding; Protagonist Therapeutics: Research Funding.

Background Prior reports indicate that living in a rural area may be associated with worse health outcomes. However, data on rurality and heart failure (HF) outcomes are scarce. Methods and Results Residents from 6 southeastern Minnesota counties with a first‐ever code for HF ( International Classification of Diseases, Ninth Revision [ ICD‐9 ], code 428, and International Classification of Diseases, Tenth Revision [ ICD‐10 ] code I50) between January 1, 2013 and December 31, 2016, were identified. Resident address was classified according to the rural‐urban commuting area codes. Rurality was defined as living in a nonmetropolitan area. Cox regression was used to analyze the association between living in a rural versus urban area and death; Andersen‐Gill models were used for hospitalization and emergency department visits. Among 6003 patients with HF (mean age 74 years, 48% women), 43% lived in a rural area. Rural patients were older and had a lower educational attainment and less comorbidity compared with patients living in urban areas ( P <0.001). After a mean (SD) follow‐up of 2.8 (1.7) years, 2440 deaths, 20 506 emergency department visits, and 11 311 hospitalizations occurred. After adjustment, rurality was independently associated with an increased risk of death (hazard ratio [HR], 1.18; 95% CI, 1.09–1.29) and a reduced risk of emergency department visits (HR, 0.89; 95% CI, 0.82–0.97) and hospitalizations (HR, 0.78; 95% CI, 0.73–0.84). Conclusions Among patients with HF, living in a rural area is associated with an increased risk of death and fewer emergency department visits and hospitalizations. Further study to identify and address the mechanisms through which rural residence influences mortality and healthcare utilization in HF is needed in order to reduce disparities in rural health.

Abstract Cardiac amyloidosis is a serious and progressive infiltrative disease that is caused by the deposition of amyloid fibrils at the cardiac level. It can be due to rare genetic variants in the hereditary forms or as a consequence of acquired conditions. Thanks to advances in imaging techniques and the possibility of achieving a non-invasive diagnosis, we now know that cardiac amyloidosis is a more frequent disease than traditionally considered. In this position paper the Working Group on Myocardial and Pericardial Disease proposes an invasive and non-invasive definition of cardiac amyloidosis, addresses clinical scenarios and situations to suspect the condition and proposes a diagnostic algorithm to aid diagnosis. Furthermore, we also review how to monitor and treat cardiac amyloidosis, in an attempt to bridge the gap between the latest advances in the field and clinical practice.

Abstract Aims Risk stratification of heart failure (HF) patients with preserved ejection fraction (HFpEF) can promote a more personalized treatment. We tested the prognostic value of a multi-parametric evaluation, including biomarkers, cardiopulmonary exercise testing-exercise stress echocardiography (CPET-ESE), and lung ultrasound, in HFpEF patients and subjects at risk of developing HF (HF Stages A and B). Background Risk stratification of heart failure (HF) patients with preserved ejection fraction (HFpEF) can promote a more personalized treatment. Design We tested the prognostic value of a multi-parametric evaluation, including biomarkers, cardiopulmonary exercise testing-exercise stress echocardiography (CPET-ESE), and lung ultrasound, in HFpEF patients and subjects at risk of developing HF (HF Stages A and B). Methods and results We performed a resting clinical/bio-humoural evaluation and a symptom-limited CPET-ESE in 274 patients (45 Stage A, 68 Stage B, and 161 Stage C-HFpEF) and 30 age- and sex-matched healthy controls. During a median follow-up of 18.5 months, we reported 71 HF hospitalizations and 10 cardiovascular deaths. Cox proportional-hazards regression identified five independent predictors and each was assigned a number of points proportional to its regression coefficient: stress-rest ΔB-lines &gt;10 (3 points), peak oxygen consumption &lt;16 mL/kg/min (2 points), minute ventilation/carbon dioxide production slope ≥36 (2 points), peak systolic pulmonary artery pressure ≥50 mmHg (1 point) and resting N-terminal pro-brain natriuretic peptide (NT-proBNP) &gt;900 pg/mL (1 point). The event-free survival probability for low risk (&lt;3 points), intermediate risk (3–6 points), and high risk (&gt;6 points) were 93%, 52%, and 20%, respectively. The area under the curve (AUC) for the scoring system to predict events was 0.92 (95% CI 0.88–0.96), with an accuracy significantly higher than the individual components of the score (all P &lt; 0.01 vs. individual AUCs). Conclusion A weighted risk score including NT-proBNP, markers of cardiopulmonary dysfunction and indices of exercise-induced pulmonary congestion identifies HFpEF patients at increased risk for adverse events and Stage A and B subjects more likely to progress towards more advanced HF stages.

Abstract Background Cutibacterium species are common pathogens in periprosthetic joint infections (PJI). These infections are often treated with β-lactams or clindamycin as monotherapy, or in combination with rifampin. Clinical evidence supporting the value of adding rifampin for treatment of Cutibacterium PJI is lacking. Methods In this multicenter retrospective study, we evaluated patients with Cutibacterium PJI and a minimal follow-up of 12 months. The primary endpoint was clinical success, defined by the absence of infection relapse or new infection. We used Fisher’s exact tests and Cox proportional hazards models to analyze the effect of rifampin and other factors on clinical success after PJI. Results We included 187 patients (72.2% male, median age 67 years) with a median follow-up of 36 months. The surgical intervention was a 2-stage exchange in 95 (50.8%), 1-stage exchange in 51 (27.3%), debridement and implant retention (DAIR) in 34 (18.2%), and explantation without reimplantation in 7 (3.7%) patients. Rifampin was included in the antibiotic regimen in 81 (43.3%) cases. Infection relapse occurred in 28 (15.0%), and new infection in 13 (7.0%) cases. In the time-to-event analysis, DAIR (adjusted hazard ratio [HR] = 2.15, P = .03) and antibiotic treatment over 6 weeks (adjusted HR = 0.29, P = .0002) significantly influenced treatment failure. We observed a tentative evidence for a beneficial effect of adding rifampin to the antibiotic treatment—though not statistically significant for treatment failure (adjusted HR = 0.5, P = .07) and not for relapses (adjusted HR = 0.5, P = .10). Conclusions We conclude that a rifampin combination is not markedly superior in Cutibacterium PJI, but a dedicated prospective multicenter study is needed.