Microwave produced 8-methyl-1,2,4,8-tetraazaspiro[4.5]dec-2-en-3-amine derivatives: their in vitro and in silico analysis.

Compound 1 is formed by a microwave-assisted multicomponent reaction of 1-methylpiperidin-4-one, 2-amino-4-methoxy-6-methyl-1,3,5-triazine, and thiosemicarbazide, followed by the synthesis of Schiff base 2a-l with a variety of aldehydes. A comparison was made between the conventional and microwave methods, and the microwave approach was shown to be considerably superior to the classical method since it takes less time and produces higher yields. Several spectral investigations, including 1H NMR, 13C NMR, Mass, and IR spectroscopy, are used to characterize the complete series. In vitro antibacterial testing suggests that compounds 2c, 2f, and 2g are promising antibacterial agents, although compounds 2d, 2e, and 2l are effective antimycobacterial agents when compared to the conventional medicine Rifampicin. The docking score from docking studies is considerable, which validates the results of the biological examination. Molecular docking was performed on Escherichia coli DNA gyrase. According to the in silico ADME analysis, each drug molecule is ideal for use in terms of drug solubility, hydrogen bonding, and cell permeability.

Quantitative CT and machine learning classification of fibrotic interstitial lung diseases.

OBJECTIVES: To evaluate quantitative computed tomography (QCT) features and QCT feature-based machine learning (ML) models in classifying interstitial lung diseases (ILDs). To compare QCT-ML and deep learning (DL) models' performance. METHODS: We retrospectively identified 1085 patients with pathologically proven usual interstitial pneumonitis (UIP), nonspecific interstitial pneumonitis (NSIP), and chronic hypersensitivity pneumonitis (CHP) who underwent peri-biopsy chest CT. Kruskal-Wallis test evaluated QCT feature associations with each ILD. QCT features, patient demographics, and pulmonary function test (PFT) results trained eXtreme Gradient Boosting (training/validation set n = 911) yielding 3 models: M1 = QCT features only; M2 = M1 plus age and sex; M3 = M2 plus PFT results. A DL model was also developed. ML and DL model areas under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CIs) were compared for multiclass (UIP vs. NSIP vs. CHP) and binary (UIP vs. non-UIP) classification performances. RESULTS: The majority (69/78 [88%]) of QCT features successfully differentiated the 3 ILDs (adjusted p ≤ 0.05). All QCT-ML models achieved higher AUC than the DL model (multiclass AUC micro-averages 0.910, 0.910, 0.925, and 0.798 and macro-averages 0.895, 0.893, 0.925, and 0.779 for M1, M2, M3, and DL respectively; binary AUC 0.880, 0.899, 0.898, and 0.869 for M1, M2, M3, and DL respectively). M3 demonstrated statistically significant better performance compared to M2 (∆AUC: 0.015, CI: [0.002, 0.029]) for multiclass prediction. CONCLUSIONS: QCT features successfully differentiated pathologically proven UIP, NSIP, and CHP. While QCT-based ML models outperformed a DL model for classifying ILDs, further investigations are warranted to determine if QCT-ML, DL, or a combination will be superior in ILD classification. KEY POINTS: • Quantitative CT features successfully differentiated pathologically proven UIP, NSIP, and CHP. • Our quantitative CT-based machine learning models demonstrated high performance in classifying UIP, NSIP, and CHP histopathology, outperforming a deep learning model. • While our quantitative CT-based machine learning models performed better than a DL model, additional investigations are needed to determine whether either or a combination of both approaches delivers superior diagnostic performance.

Optimal Medical Therapy for Chronic Coronary Disease in 2024: Focus on Antithrombotic Therapy.

Antiplatelet therapy is the cornerstone of the secondary prevention of cardiovascular disease. Aspirin is indicated for all patients with chronic coronary disease to prevent recurrent ischemic events. A more potent antithrombotic therapy-including P2Y12 inhibitor monotherapy, dual antiplatelet therapy, or vascular dose anticoagulation-reduces the risk of ischemic events but also increases bleeding risk. Clinicians must weigh both ischemic risks and bleeding risks when determining an optimal antithrombotic therapy for patients with chronic coronary disease, and soliciting patient involvement in shared decision-making is critical.

Predicting Usual Interstitial Pneumonia Histopathology From Chest CT Imaging With Deep Learning.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, often fatal form of interstitial lung disease (ILD) characterized by the absence of a known cause and usual interstitial pneumonitis (UIP) pattern on chest CT imaging and/or histopathology. Distinguishing UIP/IPF from other ILD subtypes is essential given different treatments and prognosis. Lung biopsy is necessary when noninvasive data are insufficient to render a confident diagnosis. RESEARCH QUESTION: Can we improve noninvasive diagnosis of UIP be improved by predicting ILD histopathology from CT scans by using deep learning? STUDY DESIGN AND METHODS: This study retrospectively identified a cohort of 1,239 patients in a multicenter database with pathologically proven ILD who had chest CT imaging. Each case was assigned a label based on histopathologic diagnosis (UIP or non-UIP). A custom deep learning model was trained to predict class labels from CT images (training set, n = 894) and was evaluated on a 198-patient test set. Separately, two subspecialty-trained radiologists manually labeled each CT scan in the test set according to the 2018 American Thoracic Society IPF guidelines. The performance of the model in predicting histopathologic class was compared against radiologists' performance by using area under the receiver-operating characteristic curve as the primary metric. Deep learning model reproducibility was compared against intra-rater and inter-rater radiologist reproducibility. RESULTS: For the entire cohort, mean patient age was 62 ± 12 years, and 605 patients were female (49%). Deep learning performance was superior to visual analysis in predicting histopathologic diagnosis (area under the receiver-operating characteristic curve, 0.87 vs 0.80, respectively; P < .05). Deep learning model reproducibility was significantly greater than radiologist inter-rater and intra-rater reproducibility (95% CI for difference in Krippendorff's alpha did not include zero). INTERPRETATION: Deep learning may be superior to visual assessment in predicting UIP/IPF histopathology from CT imaging and may serve as an alternative to invasive lung biopsy.

Sex Differences in the Impact of Aortic Valve Calcium Score on Mortality After Transcatheter Aortic Valve Replacement.

BACKGROUND: Transcatheter aortic valve replacement (TAVR) is now an approved alternative to surgical aortic valve replacement for the treatment of severe aortic stenosis. As the clinical adoption of TAVR expands, it remains important to identify predictors of mortality after TAVR. We aimed to evaluate the impact of sex differences in aortic valve calcium score (AVCS) on long-term mortality following TAVR in a large patient sample. METHODS: We included consecutive patients who successfully underwent TAVR for treatment of severe native aortic valve stenosis from June 2010 to May 2021 across all US Mayo Clinic sites with follow-up through July 2021. AVCS values were obtained from preoperative computed tomography of the chest. Additional clinical data were abstracted from medical records. Kaplan-Meier curves and Cox-proportional hazard regression models were employed to evaluate the effect of AVCS on long-term mortality. RESULTS: A total of 2543 patients were evaluated in the final analysis. Forty-one percent were women, median age was 82 years (Q1: 76, Q3: 86), 18.4% received a permanent pacemaker following TAVR, and 88.5% received a balloon expandable valve. We demonstrate an increase in mortality risk with higher AVCS after multivariable adjustment (P<0.001). When stratified by sex, every 500-unit increase in AVCS was associated with a 7% increase in mortality risk among women (adjusted hazard ratio, 1.07 [95% CI, 1.02-1.12]) but not in men. CONCLUSIONS: We demonstrate a notable sex difference in the association between AVCS and long-term mortality in a large TAVR patient sample. This study highlights the potential value of AVCS in preprocedural risk stratification, specifically among women undergoing TAVR. Additional studies are needed to validate this finding.

Predictors of Mortality Amongst Tocilizumab Administered COVID-19 Asian Indians: A Predictive Study From a Tertiary Care Centre.

Introduction Hyper-cytokinemia is a dreaded complication of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection and an important predictor of mortality in coronavirus disease 2019 (COVID-19). The current evidence at best is still ambiguous for use of tocilizumab in cytokine storm in COVID-19. Moreover, the factors that are associated with beneficial response from tocilizumab are unknown in COVID-19. We aimed to study the clinical outcomes especially mortality vis-à-vis clinical and laboratory characteristics of patients administered tocilizumab and identify predictors of mortality benefits amongst deceased vs recovered COVID-19 patients. Methods The present study is a retrospective observation of the demographic, clinical, and biological data of all the consecutive patients treated with tocilizumab for COVID-19 pneumonia at the COVID tertiary care centre from July 2020 to October 2020 at Ahmedabad, India. We compared the deceased group with those who recovered/discharged and evaluated patient-level demographics, clinical attributes, and laboratory investigations available to identify subgroups in whom tocilizumab reduced mortality. Results Of the 112 patients included, the mean (SD) age was 56.84 ± 13.56 years and 80 (71.4%) were male. There were 97 (86.6%) patients in the survivors and 15 (13.39%) in the deceased group. Deceased were older than the recovered group (mean: 66.14, SD: 14.41 vs mean: 55.36, SD: 12.98; p=0.04). Hypertension (33.03%) was the commonest comorbidity observed. Mortality was significantly higher in patients with cancer and type-2 diabetes (p=0.05 and p=0.01, respectively). Level of D-dimer and lactate dehydrogenase (LDH) showed trends towards significance as a predictor of mortality (p=0.07 and p=0.08, respectively) not reaching significance. D-dimer level > 5,000 nanograms per millilitre (ng/mL) was the significant predictor of subsequent deaths (p<0.0001). Fourteen patients reported adverse events of tocilizumab. Patients who developed in-hospital complications (such as septic or vasodilatory shock and/or sepsis, acute kidney injury, multiorgan dysfunction) had significantly higher mortality (p<0.0001, p=0.009, and p=0.03, respectively). Conclusion Tocilizumab might be more beneficial in younger patients without sepsis/ septic shock, acute kidney injury, multiorgan dysfunction, and who were non-ventilated. The predictors of mortality amongst Asian Indians treated with tocilizumab were older patients, the presence of type-2 diabetes, cancer, in-hospital complication (such as acute kidney injury, sepsis/septic shock, multiorgan dysfunction), higher D-dimer > 5,000 ng/mL. A larger study with pre-defined inclusion cut-offs of these variables may aid in defining patient's characteristics of Asian Indians who may benefit from tocilizumab in COVID-19.

Outcomes in Patients With Hypertrophic Cardiomyopathy and Left Ventricular Systolic Dysfunction.

BACKGROUND: End-stage (ES) hypertrophic cardiomyopathy (HCM) has been considered a particularly grim and unfavorable disease complication, associated with substantial morbidity and mortality, frequently requiring heart transplant. Previous reports have included small numbers of patients with relatively short follow-up, predominantly in prior treatment eras. OBJECTIVES: The purpose of this study was to re-evaluate clinical profile and prognosis for end-stage heart failure in a large HCM cohort with contemporary management strategies. METHODS: Patients at Tufts HCM Institute, from 2004 to 2017, were identified with ES and systolic dysfunction (ejection fraction [EF] <50%), followed for 5.8 ± 4.7 years (up to 18 years). RESULTS: Of the 2,447 patients, 118 (4.8%) had ES-HCM (EF 39 ± 9%; range 12% to 49%) at age 48 ± 15 years. Notably, over follow-up, 57 patients (48%) achieved clinical stability in New York Heart Association functional classes I/II with medical treatment (or cardiac resynchronization therapy), including 6 patients ≥10 years from ES diagnosis (up to 14 years). In total, 61 other patients (52%) developed refractory heart failure to disabling New York Heart Association functional classes III/IV (5.2%/year); 67% have survived, including 31 with heart transplant. Of the 118 ES patients, 21 had appropriate implantable cardioverter-defibrillator (ICD) therapy terminating potentially lethal tachyarrhythmias, with no difference in frequency of events in patients with EF 35% to 49% versus EF <35% (17% vs. 19%; p = 0.80). With all available treatment modalities, ES-related mortality was 1.9%/year, with 10-year survival of 85% (95% confidence interval: 77% to 94%). Mortality was 4-fold lower than previously reported for ES (8.0%/year), but exceeded 10-fold HCM with preserved EF (0.2%/year; p < 0.001). CONCLUSIONS: Although ES remains an important complication of HCM, contemporary treatment strategies, including ICDs and heart transplant, are associated with significantly lower mortality than previously considered. Primary prevention ICDs should be considered when EF is <50% in HCM. Rapid heart failure progression is not an inevitable consequence of ES, and some patients experience extended periods of clinical stability.

Impact of Sex on Clinical Course and Survival in the Contemporary Treatment Era for Hypertrophic Cardiomyopathy.

Background The relation of sex to clinical presentation and course in hypertrophic cardiomyopathy (HCM) remains incompletely resolved. We assessed differences in clinical outcomes between men and women within our large HCM cohort. Methods and Results Of 2123 consecutive patients, a minority (38%) were women who were diagnosed with HCM at older ages or referred for subspecialty evaluation later than men (50±19 versus 44±16 and 55±18 versus 49±16; P<0.001). Women more commonly developed advanced New York Heart Association class III/IV symptoms (53% versus 35% in men; P<0.001), predominantly secondary to outflow obstruction. While end-stage heart failure with systolic dysfunction (ejection fraction <50%) was similar in men (5% versus 4% in women; P=0.33), women were 3-fold more likely to develop heart failure with preserved systolic function (7.5% versus 2.6%; P=0.002). Sudden death events terminated by defibrillator therapy were similar in women (0.9%/year) versus men (1.0%/year; hazard ratio, 0.92; 95% CI, 0.6-1.5; P=0.73). HCM mortality was uncommon, with identical rates in both sexes (0.3%/year; hazard ratio, 1.5; 95% CI, 0.7-3.4;, P=0.25). Age-adjusted all-cause mortality also did not differ between women and men (1.7% versus 1.3%/year; hazard ratio, 1.32; 95% CI, 0.92-1.91; P=0.13). Conclusions Survival was not less favorable in women with HCM. Contemporary treatments including surgical myectomy to reverse heart failure and defibrillators to prevent sudden death, were effective in both sexes contributing to low mortality. However, despite more frequent outflow obstruction, women with HCM are underrecognized and referred to centers later than men, often with more advanced heart failure. Greater awareness of HCM in women should lead to earlier diagnosis and treatment, with implications for improved quality of life.