Prediction of heart failure events based on physiologic sensor data in HINODE defibrillator patients.

AIMS: Hospitalizations are common in patients with heart failure and are associated with high mortality, readmission and economic burden. Detecting early signs of worsening heart failure may enable earlier intervention and reduce hospitalizations. The HeartLogic algorithm is designed to predict worsening heart failure using diagnostic data from multiple device sensors. The main objective of this analysis was to evaluate the sensitivity of the HeartLogic alert calculation in predicting worsening heart failure events (HFEs). We also evaluated the false positive alert rate (FPR) and compared the incidence of HFEs occurring in a HeartLogic alert state to those occurring out of an alert state. METHODS: The HINODE study enrolled 144 patients (81 ICD and 63 CRT-D) with device sensor data transmitted via a remote monitoring system. HeartLogic alerts were then retrospectively simulated using relevant sensor data. Clinicians and patients were blinded to calculated alerts. Reported adverse events with HF symptoms were adjudicated and classified by an independent HFE committee. Sensitivity was defined as the ratio of the number of detected usable HFEs (true positives) to the total number of usable HFEs. A false positive alert was defined as an alert with no usable HFE between the alert onset date and the alert recovery date plus 30 days. The patient follow-up period was categorized as in alert state or out of alert state. The event rate ratio was the HFE rate calculated in alert to out of alert. RESULTS: The patient cohort was 79% male and had an average age of 68 ± 12 years. This analysis yielded 244 years of follow-up data with 73 HFEs from 37 patients. A total of 311 HeartLogic alerts at the nominal threshold (16) occurred across 106 patients providing an alert rate of 1.27 alerts per patient-year. The HFE rate was 8.4 times greater while in alert compared with out of alert (1.09 vs. 0.13 events per patient-year; P < 0.001). At the nominal alert threshold, 80.8% of HFEs were detected by a HeartLogic alert [95% confidence interval (CI): 69.9%-89.1%]. The median time from first true positive alert to an adjudicated clinical HFE was 53 days. The FPR was 1.16 (95% CI: 0.98-1.38) alerts per patient-year. CONCLUSIONS: Results suggest that signs of worsening HF can be detected successfully with remote patient follow-up. The use of HeartLogic may predict periods of increased risk for HF or clinically significant events, allowing for early intervention and reduction of hospitalization in a vulnerable patient population.

Validated administrative data based ICD-10 algorithms for chronic conditions: A systematic review.

OBJECTIVE: This systematic review aimed to identify ICD-10 based validated algorithms for chronic conditions using health administrative data. METHODS: A comprehensive systematic literature search using Ovid MEDLINE, Embase, PsycINFO, Web of Science and CINAHL was performed to identify studies, published between 1983 and May 2023, on validated algorithms for chronic conditions using administrative health data. Two reviewers independently screened titles and abstracts and reviewed full text of selected studies to complete data extraction. A third reviewer resolved conflicts arising at the screening or study selection stages. The primary outcome was validated studies of ICD-10 based algorithms with both sensitivity and PPV of ≥70 %. Studies with either sensitivity or PPV <70 % were included as secondary outcomes. RESULTS: Overall, the search identified 1686 studies of which 54 met the inclusion criteria. Combining a previously published literature search, a total of 61 studies were included for data extraction. The study identified 40 chronic conditions with high validity and 22 conditions with moderate validity. The validated algorithms were based on administrative data from different countries including Canada, USA, Australia, Japan, France, South Korea, and Taiwan. The algorithms identified included several types of cancers, cardiovascular conditions, kidney diseases, gastrointestinal disorders, and peripheral vascular diseases, amongst others. CONCLUSION: With ICD-10 prominently used across the world, this up-to-date systematic review can prove to be a helpful resource for research and surveillance initiatives using administrative health data for identifying chronic conditions.

Managing SVC Syndrome in Patients with Cardiac Implantable Electronic Device Leads: Strategies and Considerations.

BACKGROUND: Data on Transvenous (TV) lead-associated superior vena cava (SVC) syndrome are limited. The management of this problem might require a multidisciplinary approach, often involving TV lead extraction (TLE) followed by angioplasty and stenting. OBJECTIVE: To describe the management and outcome of TV lead-associated SVC syndrome METHODS: We retrospectively identified patients with a diagnosis of SVC syndrome and TV leads at Emory Healthcare between 2015 and 2023. RESULTS: 15 patients with lead-related SVC syndrome were identified. The cohort average age was 50 years. Symptoms included swelling in the face, neck, and upper extremity (67%), shortness of breath (53%) and lightheadedness (40%). Patients had on average 2 ± 0.7 leads crossing the SVC with a lead dwell time of 9.8 ± 7.5 years. Thirteen patients were managed with transvenous lead extraction (TLE), followed by SVC stenting and angioplasty (10), angioplasty alone (2), while one patient had no intervention after TLE. One patient was managed with anticoagulation, and another had angioplasty and stenting with lead jailing. One patient experienced SVC perforation and cardiac tamponade during SVC stenting managed successfully with a covered stent and pericardiocentesis. Among the 12 patients with TLE and angioplasty ± stenting, 7 patients underwent reimplantation of a transvenous lead. Two of those patients had symptoms recurrence and none of the 5 patients without lead reimplantation had recurrence of symptoms. CONCLUSION: Lead-related SVC syndrome management requires a multidisciplinary approach often including TLE followed by angioplasty and stenting. Avoiding TV lead reimplantation might help reduce symptoms recurrence.

Positive predictive value and sensitivity of cancer-associated venous thromboembolism diagnoses in the Danish National Patient Register.

INTRODUCTION: Hospital discharge diagnoses from administrative registries are frequently used in studies of cancer-associated venous thromboembolism, but the validity of International Classification of Diseases (ICD) codes for identifying such events is unknown. MATERIALS AND METHODS: Using patient samples from the Danish National Patient Register, we calculated positive predictive values (PPV), i.e., the proportion of registered ICD codes, which could be confirmed after manual search of the electronic health record. Sensitivity was estimated in a sample of patients with imaging-verified venous thromboembolism but without prior knowledge about their ICD coding status. Sensitivity was calculated as the proportion of these patients, who were discharged with an ICD code for venous thromboembolism. RESULTS: The overall PPV of an ICD-10 diagnosis of cancer-associated venous thromboembolism was 75.9 % (95 % confidence interval 71.3-80.0). In subgroups, the PPV was particularly low for recurrent venous thromboembolism (44.2 %), diagnoses in a secondary position (55.7 %), outpatient diagnoses (65.3 %), and diagnoses given at surgical (66.7 %), emergency wards (48.4 %), or via hospices/palliative teams (0 %). The overall sensitivity was 68 %, meaning 32 % of patients with cancer diagnosed in hospital with venous thromboembolism were discharged without any registered ICD code for venous thromboembolism. CONCLUSIONS: The positive predictive value of an ICD diagnosis of cancer-associated venous thromboembolism in the Danish Patient Register was overall adequate for research purposes, but with notable variation across subgroups. Sensitivity was limited, as 1/3 of patients with venous thromboembolism were discharged without any relevant ICD code. Cautious interpretation of incidence of cancer-associated venous thromboembolism based on administrative register-based data is warranted.

Somatic and psychiatric comorbidity in people with diagnosed gambling disorder: A Finnish nation-wide register study.

BACKGROUND AND AIMS: This is the first nation-wide register study based on a total population sample measuring the gender-specific incidences of chronic diseases and conditions among adults diagnosed with gambling disorder (GD). DESIGN, SETTING AND PARTICIPANTS: The study used aggregated data for 2011-22 retrieved from the Register of Primary Health Care visits, Care Register for Health Care and Care Register for Social Welfare, including specialized outpatient and inpatient health care, inpatient social care and institutional care and housing services with 24-hour or part-time assistance, set in mainland Finland. Participants comprised people aged 18-90+ years with GD diagnosis [corresponding to pathological gambling, International Classification of Diseases 10th revision (ICD-10) code F63.0, n = 3605; men n = 2574, women n = 1031] and the general population (n = 4 374 192). MEASUREMENTS: Incidences of somatic diseases and psychiatric disorders were calculated for the people with diagnosed GD and for the general population, separately for women and men. FINDINGS: After standardizing for age, the incidence of each diagnostic group was systematically higher for people with GD compared with the general population, except for cancer. The highest standardized incidence ratio (SIR) values were for psychiatric disorders [SIR = 234.2; 95% confidence interval (CI) = 226.1-242.4], memory disorders (SIR = 172.1; 95% CI = 119.1-234.8), nervous system diseases (SIR = 162.8; 95% CI = 152.8-173.1), chronic respiratory diseases (SIR = 150.6; 95% CI = 137.6-164.2), diabetes (SIR = 141.4; 95% CI = 127.9-155.5) and digestive diseases (SIR = 134.5; 95% CI = 127.1-142.2). CONCLUSIONS: In Finland, the incidence of chronic diseases and conditions among people with gambling disorder is higher compared with the general population, apart from cancer.

Predictors of appropriate therapies delivered by the implantable cardioverter-defibrillator in patients with coronary artery disease during long-term period.

This prospective study aimed to investigate the ability of cardiac autonomic nervous system (CANS) activity assessment to predict appropriate implantable cardioverter-defibrillator (ICD) therapy in patients with coronary artery disease (CAD) during long-term follow-up period. We enrolled patients with CAD and ICD implantation indications that included both secondary and primary prevention of sudden cardiac death. Before ICD implantation CANS was assessed by using heart rate variability (HRV), myocardium scintigraphy with 123I-meta-iodobenzylguanidine (123I-MIBG) and erythrocyte membranes ß-adrenoreactivity (EMA). The study's primary endpoint was the documentation of appropriate ICD therapy. Of 45 (100.0%) patients, 15 (33.3%) had appropriate ICD therapy during 36 months follow-up period. Patients with appropriate ICD therapy were likely to have a higher summed 123I-MIBG score delayed (p < 0.001) and lower 123I-MIBG washout rate (p = 0.008) indicators. These parameters were independently associated with endpoint in univariable and multivariable logistic regression. We created a logistic equation and calculated a cut-off value. The resulting ROC curve revealed a discriminative ability with AUC of 0.933 (95% confidence interval 0.817-0.986; sensitivity 100.00%; specificity 93.33%). Combined CANS activity assessment is useful in prediction of appropriate ICD therapy in patients with CAD during long-term follow-up period after device implantation.

The effects of empagliflozin on ventricular arrhythmias in heart failure patients with an implantable cardioverter-defibrillator: a double-blind randomized controlled trial.

Sodium-glucose transporter 2 (SGLT2) inhibitors such as empagliflozin are one of the main treatments for type 2 diabetes mellitus (DM2) and heart failure (HF). They have also demonstrated anti-arrhythmic effects in some preclinical and clinical studies. The purpose of this study was to assess the effects of empagliflozin on ventricular arrhythmias in HF patients with an implantable cardioverter-defibrillator (ICD). In a prospective double-blinded, randomized controlled trial of Iran County, Mashhad (72 patients 1:1), we compared the frequency and proportion of ventricular arrhythmias and ICD therapies during the 24 weeks to the prior 24 weeks. Results revealed that empagliflozin significantly reduced the frequency and proportion of ventricular tachycardia (VT)/fibrillation (VF) episodes (P = 0.019 and 0.039, respectively). Moreover, it tended to reduce the frequency and proportion of ICD therapies, including anti-tachycardia pacing (ATP) and shock. Subgroup analysis of patients with or without any antiarrhythmic drugs (digoxin, mexiletine, amiodarone, or sotalol) revealed that only patients who were previously on the antiarrhythmic drugs benefit from empagliflozin antiarrhythmic effects. In conclusion, empagliflozin exhibits anti-arrhythmic effects in HF patients with an ICD. Larger and long-term clinical studies are still needed to investigate and confirm all positive effects of SGLT2 inhibitors in this regard. Trial registration number: IRCT20120520009801N7 (Approval date: June 11, 2022).

Electrical storm after acute myocardial infarction treated with radiofrequency ablation under the escort of ICD.

The occurrence of ventricular tachycardia (VT) in patients with acute myocardial infarction (AMI) is associated with poor prognosis. Drug therapy and implantable cardioverter-defibrillators (ICDs) are effective methods to prevent sudden death. Radiofrequency (RF) catheter ablation can map the matrix and mechanism of VT, thereby effectively reducing the occurrence of ICD discharge. This paper reports on the case of a middle-aged man who underwent emergency percutaneous coronary intervention for AMI and developed VT and ventricular fibrillation on day 7 after reperfusion. An ICD was implanted. On day 19, he received catheter ablation because of refractory monomorphic ventricular tachycardia and frequent discharge of the ICD. After three months, the patient had not experienced any further ventricular tachycardia attacks. The conclusion is that RF catheter ablation can resolve the ES after myocardial infarction and significantly reduce the occurrence of ICD discharges.

Copper-Based Composites Nanoparticles Improve Triple-Negative Breast Cancer Treatment with Induction of Apoptosis-Cuproptosis and Immune Activation.

The synergistic effect of apoptosis and cuproptosis, along with the activation of the immune system, presents a promising approach to enhance the efficacy against triple-negative breast cancer (TNBC). Here, two prodrugs are synthesized: a reactive oxygen species (ROS)-responsive prodrug PEG-TK-DOX and a glutathione (GSH)-responsive prodrug PEG-DTPA-SS-CPT. These prodrugs are self-assembled and chelated Cu2+ to prepare nanoparticle PCD@Cu that simultaneously loaded doxorubicin (DOX), camptothecin (CPT), and Cu2+. The elevated levels of ROS and GSH in TNBC cells disrupted the PCD@Cu structure, leading to the release of Cu+, DOX, and CPT and the depletion of GSH. DOX and CPT triggered apoptosis with immunogenic cell death (ICD) in TNBC cells. Simultaneously, PCD@Cu downregulated the expression of copper transporting ATPase 2 (ATP7B), causing a significant accumulation of copper ions in TNBC cells. This further induced the aggregation of lipoylated dihydrolipoamide S-acetyltransferase (DLAT) and downregulation of iron-sulfur (Fe-S) cluster proteins, ultimately leading to cuproptosis and ICD in TNBC. In vitro and in vivo experiments confirmed that PCD@Cu induced apoptosis and cuproptosis in TNBC and activated the immune system, demonstrating strong anti-tumor capabilities. Moreover, PCD@Cu exhibited an excellent biosafety profile. Overall, this study provides a promising strategy for effective TNBC therapy.

A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data.

BACKGROUND: Multimorbidity is a significant public health concern, characterized by the coexistence and interaction of multiple preexisting medical conditions. This complex condition has been associated with an increased risk of COVID-19. Individuals with multimorbidity who contract COVID-19 often face a significant reduction in life expectancy. The postpandemic period has also highlighted an increase in frailty, emphasizing the importance of integrating existing multimorbidity details into epidemiological risk assessments. Managing clinical data that include medical histories presents significant challenges, particularly due to the sparsity of data arising from the rarity of multimorbidity conditions. Also, the complex enumeration of combinatorial multimorbidity features introduces challenges associated with combinatorial explosions. OBJECTIVE: This study aims to assess the severity of COVID-19 in individuals with multiple medical conditions, considering their demographic characteristics such as age and sex. We propose an evolutionary machine learning model designed to handle sparsity, analyzing preexisting multimorbidity profiles of patients hospitalized with COVID-19 based on their medical history. Our objective is to identify the optimal set of multimorbidity feature combinations strongly associated with COVID-19 severity. We also apply the Apriori algorithm to these evolutionarily derived predictive feature combinations to identify those with high support. METHODS: We used data from 3 administrative sources in Piedmont, Italy, involving 12,793 individuals aged 45-74 years who tested positive for COVID-19 between February and May 2020. From their 5-year pre-COVID-19 medical histories, we extracted multimorbidity features, including drug prescriptions, disease diagnoses, sex, and age. Focusing on COVID-19 hospitalization, we segmented the data into 4 cohorts based on age and sex. Addressing data imbalance through random resampling, we compared various machine learning algorithms to identify the optimal classification model for our evolutionary approach. Using 5-fold cross-validation, we evaluated each model's performance. Our evolutionary algorithm, utilizing a deep learning classifier, generated prediction-based fitness scores to pinpoint multimorbidity combinations associated with COVID-19 hospitalization risk. Eventually, the Apriori algorithm was applied to identify frequent combinations with high support. RESULTS: We identified multimorbidity predictors associated with COVID-19 hospitalization, indicating more severe COVID-19 outcomes. Frequently occurring morbidity features in the final evolved combinations were age>53, R03BA (glucocorticoid inhalants), and N03AX (other antiepileptics) in cohort 1; A10BA (biguanide or metformin) and N02BE (anilides) in cohort 2; N02AX (other opioids) and M04AA (preparations inhibiting uric acid production) in cohort 3; and G04CA (Alpha-adrenoreceptor antagonists) in cohort 4. CONCLUSIONS: When combined with other multimorbidity features, even less prevalent medical conditions show associations with the outcome. This study provides insights beyond COVID-19, demonstrating how repurposed administrative data can be adapted and contribute to enhanced risk assessment for vulnerable populations.

Feasibility, Safety and Short-Term Follow-Up Of Defibrillator Lead at Left Bundle Branch Area Pacing Location: A Pilot Study.

BACKGROUND: Left bundle branch area pacing(LBBAP) has been increasingly adopted as an alternative modality for cardiac-resynchronization-therapy(CRT). The feasibility and safety of utilizing LBBAP lead to provide sensing of ventricular arrhythmia in patients receiving implantable cardioverter defibrillator(ICD) with CRT has been demonstrated recently OBJECTIVES: Aim of our study was to analyse the feasibility, safety and short-term follow-up of a traditional defibrillator lead at LBBAP location. METHODS: Patients who underwent successful LBBAP-defibrillator using DF-1/DF-4 lead and delivery catheter were included in the study. Defibrillation threshold(DFT) testing was performed after implantation to assess the ability of LBBAP defibrillator lead to sense and provide appropriate therapy for ventricular arrhythmia. RESULTS: Though the ICD-lead could be successfully deployed in LBB area in 7 out of 8 patients, it was repositioned to right-ventricle(RV) apex due to atrial-oversensing in one and cheesy-septum in another patient. Acute procedural success was 62.5%(5/8 patients). Mean age 62.6±21.6 years. Mean procedural duration 115.6±38.1 minutes with LBBAP defibrillator lead fluoroscopy duration of 10.6±3.5 minutes. Mean capture threshold 0.58±0.23V/0.4ms, sensed R-wave amplitude 9.6±2.2mV, pacing-impedance 560±145Ohms and shock impedance of 65.4±5.5Ohms. Defibrillation testing was successful in inducing ventricular-fibrillation and could be sensed and reverted promptly by the shock delivered through the lead. During mean follow-up of 3.8±2.2 months the pacing parameters remained stable. There were no episodes of inappropriate arrhythmia detection or therapy delivery during follow-up. CONCLUSION: LBBAP defibrillator is feasible, safe and effective during short-term follow-up. DFT-testing at the time of implantation will help in ensuring appropriate sensing and treatment of ventricular arrhythmias.

EFFICACY AND SAFETY OF THE SUBCUTANEOUS IMPLANTABLE CARDIOVERTER-DEFIBRILLATOR IN PATIENTS WITH AND WITHOUT OBESITY: A META-ANALYSIS.

BACKGROUND: The subcutaneous implantable cardioverter-defibrillator (S-ICD) has emerged as an alternative to transvenous systems for preventing sudden cardiac death. However, concerns have been raised regarding its efficacy and safety in obese individuals. OBJECTIVE: This meta-analysis aims to evaluate the efficacy and safety of the S-ICD in patients with obesity by assessing the relationship between body mass index (BMI) and clinical outcomes. METHODS: A comprehensive search of multiple databases was conducted for English-language peer-reviewed studies reporting clinical outcomes in S-ICD recipients with (BMI ≥30 kg/m2) and without obesity (BMI <30 kg/m2). Data on pre-implantation screening failure, defibrillation testing, complications, appropriate and inappropriate shocks, and survival were analysed using standard random-effect meta-analytical techniques. RESULTS: Twenty-nine studies involving 20,486 patients were included. There was no statistically significant difference in the mean BMI values of patients with failed or successful preimplantation screening (mean difference -0.60 kg/m2, 95% CI -2.06 to 0.86). Obesity was associated with higher rates of failed defibrillation testing at ≤65J (OR 2.16, 95% CI 1.39-3.35), and mal-/suboptimal positioning occurred more frequently in obese compared to non-obese patients (OR 3.37, 95% CI 1.76-6.44). Increased BMI as a continuous variable (per increase in 1 kg/m2 BMI) was associated with elevated defibrillation thresholds (OR 1.05, 95% CI 1.03-1.08), a higher risk of complications (HR 1.04, 95% CI 1.02-1.05), a trend towards increased number of appropriate shocks (HR 1.02, 95% CI 1.00-1.04), and no significant increase in the risk for inappropriate shocks (HR 1.01, 95% CI 0.99-1.03). CONCLUSION: This meta-analysis underscores the importance of considering obesity in S-ICD implantation decisions. While S-ICD remains effective in obese patients, attention to potential technical challenges and higher complication rates is warranted.

Management of Long QT Syndrome: A Systematic Review.

Long QT syndrome (LQTS) is a cardiac disorder characterized by prolonged repolarization of the heart's electrical cycle, which can be observed as an extended QT interval on an electrocardiogram (ECG). The safe and effective management of LQTS often necessitates a multifaceted approach encompassing pharmacological treatment, lifestyle modifications, and, in high-risk cases, the implantation of implantable cardioverter-defibrillators (ICDs). Beta-blockers, particularly nadolol and propranolol, are foundational in treating LQTS, especially for high-risk patients, though ICDs are recommended for those with a history of cardiac arrest or recurrent arrhythmic episodes. Intermediate and low-risk patients are usually managed with medical therapy and regular monitoring. Lifestyle modifications, such as avoiding strenuous physical activities and certain medications, play a critical role. Additionally, psychological support is essential due to the anxiety and depression associated with LQTS. Left cardiac sympathetic denervation (LCSD) offers an alternative for those intolerant to beta-blockers or ICDs. For diagnosis and management, advancements in artificial intelligence (AI) are proving beneficial, enhancing early detection and risk stratification. Despite these developments, significant gaps in understanding the pathophysiology and optimal management strategies for LQTS remain. Future research should focus on refining risk stratification, developing new therapeutic approaches, and generating robust data to guide treatment decisions, ultimately aiming for a personalized medicine approach.

The new chronic pain MG30 category and diagnostic specificity in quality registries-problems and suggested solutions with special reference to Swedish Quality Registry for Pain rehabilitation (SQRP).

The Swedish Quality Registry for Pain rehabilitation (SQRP) is a well-established clinical registry for adult patients with complex chronic pain conditions. SQRP registers patient-reported outcome measures from a majority of specialist chronic pain units/departments in Sweden. Up to four International Classification of Diseases version 10 (ICD-10) diagnoses can be registered in SQRP. The aim of the paper is to describe how we envision the new chronic pain category MG30 in ICD-11 can be used in SQRP. We envision that the first diagnosis in SQRP shall always be a MG30 diagnosis, which will ensure broad implementation of ICD-11 in Swedish pain care. However, at first glance, there seems to be specificity problems with ICD-11 codes that might impair their useability in SQRP or other registries. But ICD-11 offers more than meets the eye. First, the entries at the level of the so-called foundational layer have unique resource identifiers (URI) that can be used to enhance specificity. Second, ICD-11 contains numerous extension codes that can be combined with the MG30 codes - for instance, concerning the anatomical location of pain. Third, to enrich the description of the clinical concept at hand, it is possible to create clusters of stem codes. These three options are briefly discussed. We conclude that the full potential of the MG30 category can be better exploited in registries such as SQRP if foundational codes, extension codes, and/or clustering of stem codes are used to enhance diagnostic specificity.

Advancements in nanomedicine delivery systems: unraveling immune regulation strategies for tumor immunotherapy.

This review highlights the significant role of nanodrug delivery systems (NDDS) in enhancing the efficacy of tumor immunotherapy. Focusing on the integration of NDDS with immune regulation strategies, it explores their transformative impacts on the tumor microenvironment and immune response dynamics. Key advancements include the optimization of drug delivery through NDDS, targeting mechanisms like immune checkpoint blockade and modulating the immunosuppressive tumor environment. Despite the progress, challenges such as limited clinical efficacy and complex manufacturing processes persist. The review emphasizes the need for further research to optimize these systems, potentially revolutionizing cancer treatment by improving delivery efficiency, reducing toxicity and overcoming immune resistance.

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A novel tool for arrhythmic risk stratification in desmoplakin gene variant carriers.

BACKGROUND AND AIMS: Pathogenic desmoplakin (DSP) gene variants are associated with the development of a distinct form of arrhythmogenic cardiomyopathy known as DSP cardiomyopathy. Patients harbouring these variants are at high risk for sustained ventricular arrhythmia (VA), but existing tools for individualized arrhythmic risk assessment have proven unreliable in this population. METHODS: Patients from the multi-national DSP-ERADOS (Desmoplakin SPecific Effort for a RAre Disease Outcome Study) Network patient registry who had pathogenic or likely pathogenic DSP variants and no sustained VA prior to enrolment were followed longitudinally for the development of first sustained VA event. Clinically guided, step-wise Cox regression analysis was used to develop a novel clinical tool predicting the development of incident VA. Model performance was assessed by c-statistic in both the model development cohort (n = 385) and in an external validation cohort (n = 86). RESULTS: In total, 471 DSP patients [mean age 37.8 years, 65.6% women, 38.6% probands, 26% with left ventricular ejection fraction (LVEF) < 50%] were followed for a median of 4.0 (interquartile range: 1.6-7.3) years; 71 experienced first sustained VA events {2.6% [95% confidence interval (CI): 2.0, 3.5] events/year}. Within the development cohort, five readily available clinical parameters were identified as independent predictors of VA and included in a novel DSP risk score: female sex [hazard ratio (HR) 1.9 (95% CI: 1.1-3.4)], history of non-sustained ventricular tachycardia [HR 1.7 (95% CI: 1.1-2.8)], natural logarithm of 24-h premature ventricular contraction burden [HR 1.3 (95% CI: 1.1-1.4)], LVEF < 50% [HR 1.5 (95% CI: .95-2.5)], and presence of moderate to severe right ventricular systolic dysfunction [HR 6.0 (95% CI: 2.9-12.5)]. The model demonstrated good risk discrimination within both the development [c-statistic .782 (95% CI: .77-.80)] and external validation [c-statistic .791 (95% CI: .75-.83)] cohorts. The negative predictive value for DSP patients in the external validation cohort deemed to be at low risk for VA (<5% at 5 years; n = 26) was 100%. CONCLUSIONS: The DSP risk score is a novel model that leverages readily available clinical parameters to provide individualized VA risk assessment for DSP patients. This tool may help guide decision-making for primary prevention implantable cardioverter-defibrillator placement in this high-risk population and supports a gene-first risk stratification approach.

Synergistic action of gemcitabine and celecoxib in promoting the antitumor efficacy of anti-programmed death-1 monoclonal antibody by triggering immunogenic cell death.

Background: Emerging evidence suggests that immunogenic chemotherapy not only kills tumor cells but also improves the immune-suppressive tumor microenvironment by inducing immunogenic cell death (ICD), leading to sustained anti-tumor effects. The lack of ICD inducers explored in lung cancer necessitates investigation into new inducers for this context, therefore, this study aims to explore whether the gemcitabine (GEM) and celecoxib can activate the immunogenic chemotherapy progress in lung cancer tissue. Methods: We assessed five chemotherapeutic agents for their ability to trigger ICD using ex vivo and in vivo experiments, including western blotting (WB), flow cytometry, and tumor preventive vaccine assays. Additionally, we evaluated the synergistic effects of GEM, celecoxib, and anti-programmed death 1 monoclonal antibody (aPD-1) in tumor-bearing mice to understand how GEM activates antitumor immunity and enhances immunochemotherapy. Results: GEM was identified as an effective ICD inducer, showing high expression of calreticulin (CRT) and heat shock protein 90 (HSP90). Co-culture with GEM-treated cells [Lewis lung carcinoma (LLC) and CMT-64] enhanced dendritic cell (DC) activity, evidenced by maturation markers and increased phagocytic capacity. Moreover, celecoxib was found to enhance ICD by reducing indoleamine 2,3-dioxygenase 1 (IDO1) expression and increasing reactive oxygen species (ROS)-based endoplasmic reticulum (ER) stress. The combination therapy [GEM, celecoxib, and aPD-1 (GCP)] exhibited potent and sustained antitumor activity in immunocompetent mice, with enhanced recruitment of tumor-infiltrating lymphocytes. Conclusions: These findings support the potential use of GCP therapy as a treatment option for lung cancer patients.

Signature identification based on immunogenic cell death-related lncRNAs to predict the prognosis and immune activity of patients with endometrial carcinoma.

Background: Endometrial carcinoma (EC) is one of the most prevalent gynecologic malignancies and requires further classification for treatment and prognosis. Long non-coding RNAs (lncRNAs) and immunogenic cell death (ICD) play a critical role in tumor progression. Nevertheless, the role of lncRNAs in ICD in EC remains unclear. This study aimed to explore the role of ICD related-lncRNAs in EC via bioinformatics and establish a prognostic risk model based on the ICD-related lncRNAs. We also explored immune infiltration and immune cell function across prognostic groups and made treatment recommendations. Methods: A total of 552 EC samples and clinical data of 548 EC patients were extracted from The Cancer Genome Atlas (TCGA) database and University of California Santa Cruz (UCSC) Xena, respectively. A prognostic-related feature and risk model was developed using the least absolute shrinkage and selection operator (LASSO). Subtypes were classified with consensus cluster analysis and validated with t-Distributed Stochastic Neighbor Embedding (tSNE). Kaplan-Meier analysis was conducted to assess differences in survival. Infiltration by immune cells was estimated by single sample gene set enrichment analysis (ssGSEA), Tumor IMmune Estimation Resource (TIMER) algorithm. Quantitative polymerase chain reaction (qPCR) was used to detect lncRNAs expression in clinical samples and cell lines. A series of studies was conducted in vitro and in vivo to examine the effects of knockdown or overexpression of lncRNAs on ICD. Results: In total, 16 ICD-related lncRNAs with prognostic values were identified. Using SCARNA9, FAM198B-AS1, FKBP14-AS1, FBXO30-DT, LINC01943, and AL161431.1 as risk model, their predictive accuracy and discrimination were assessed. We divided EC patients into high-risk and low-risk groups. The analysis showed that the risk model was an independent prognostic factor. The prognosis of the high- and low-risk groups was different, and the overall survival (OS) of the high-risk group was lower. The low-risk group had higher immune cell infiltration and immune scores. Consensus clustering analysis divided the samples into four subtypes, of which cluster 4 had higher immune cell infiltration and immune scores. Conclusions: A prognostic signature composed of six ICD related-lncRNAs in EC was established, and a risk model based on this signature can be used to predict the prognosis of patients with EC.