Rural-urban Differences in Long-term Mortality and Readmission Following COVID-19 Hospitalization, 2020 to 2023.

Background: We compared long-term mortality and readmission rates after COVID-19 hospitalization based on rural-urban status and assessed the impact of COVID-19 vaccination introduction on clinical outcomes by rurality. Methods: The study comprised adults hospitalized for COVID-19 at 17 hospitals in 4 US states between March 2020 and July 2022, followed until May 2023. The main analysis included all patients, whereas a sensitivity analysis focused on residents from 4 states containing 17 hospitals. Additional analyses compared the pre- and postvaccination periods. Results: The main analysis involved 9325 COVID-19 hospitalized patients: 31% were from 187 rural counties in 31 states; 69% from 234 urban counties in 44 states; the mean age was 65 years (rural, 66 years; urban, 64 years); 3894 women (rural, 41%; urban, 42%); 8007 Whites (rural, 87%; urban, 83%); 1738 deaths (rural, 21%; urban, 17%); and 2729 readmissions (rural, 30%; urban, 29%). During a median follow-up of 602 days, rural residence was associated with a 22% higher all-cause mortality (log-rank, P < .001; hazard ratio, 1.22; 95% confidence interval, 1.10-1.34, P < .001), and a trend toward a higher readmission rate (log-rank, P = .038; hazard ratio, 1.06; 95% confidence interval, .98-1.15; P = .130). The results remained consistent in the sensitivity analysis and in both pre- and postvaccination time periods. Conclusions and Relevance: Patients from rural counties experienced higher mortality and tended to be readmitted more frequently following COVID-19 hospitalization over the long term compared with those from urban counties, a difference that remained even after the introduction of COVID-19 vaccines.

An analysis of suicidal and self-injurious behavior reports with antiseizure medications in the FDA adverse event database.

BACKGROUND: Pharmacovigilance systems such as the FDA Adverse Event Reporting System (FAERS), are established models for adverse event surveillance that may have been missed during clinical trials. We aimed to analyze twenty-five anti-seizure medications (ASMs) in FAERS to assess for increased reporting of suicidal and self-injurious behavior. METHODS: Twenty-five ASMs were analyzed: brivaracetam, cannabidiol, carbamazepine, clobazam, clonazepam, diazepam, eslicarbazepine, felbamate, gabapentin, lacosamide, lamotrigine, levetiracetam, oxcarbazepine, perampanel, phenobarbital, phenytoin, pregabalin, primidone, rufinamide, stiripentol, tiagabine, topiramate, valproate, vigabatrin, zonisamide. Reports of "suicidal and self-injurious behavior" were collected from January 1, 2004, to December 31, 2020, using OpenVigil 2.1 tool with indication as "Epilepsy". Relative reporting ratio, proportional reporting ratio, and reporting odds ratio were calculated utilizing all other drug reports for epilepsy patients as a control. RESULTS: Significant relative operating ratio, ROR (greater than 1, p<0.05) were observed for diazepam (2.909), pregabalin (2.739), brivaracetam (2.462), gabapentin (2.185), clonazepam (1.649), zonisamide (1.462), lacosamide (1.333), and levetiracetam (1.286). CONCLUSIONS: Of the 25 ASMs that were analyzed in this study, 4 (16%) were identified to have been linked with a likely true adverse event. These drugs included diazepam, brivaracetam, gabapenetin, and pregabalin. Although several limitations are present with the FAERS database, it is imperative to closely monitor patient comorbidities for increased risk of suicidality with the use of several ASMs.

Lightweight preprocessing and template matching facilitate streamlined ischemic myocardial scar classification.

Purpose: Ischemic myocardial scarring (IMS) is a common outcome of coronary artery disease that potentially leads to lethal arrythmias and heart failure. Late-gadolinium-enhanced cardiac magnetic resonance (CMR) imaging scans have served as the diagnostic bedrock for IMS, with recent advancements in machine learning enabling enhanced scar classification. However, the trade-off for these improvements is intensive computational and time demands. As a solution, we propose a combination of lightweight preprocessing (LWP) and template matching (TM) to streamline IMS classification. Approach: CMR images from 279 patients (151 IMS, 128 control) were classified for IMS presence using two convolutional neural networks (CNNs) and TM, both with and without LWP. Evaluation metrics included accuracy, sensitivity, specificity, F1-score, area under the receiver operating characteristic curve (AUROC), and processing time. External testing dataset analysis encompassed patient-level classifications (PLCs) and a CNN versus TM classification comparison (CVTCC). Results: LWP enhanced the speed of both CNNs (4.9x) and TM (21.9x). Furthermore, in the absence of LWP, TM outpaced CNNs by over 10x, while with LWP, TM was more than 100x faster. Additionally, TM performed similarly to the CNNs in accuracy, sensitivity, specificity, F1-score, and AUROC, with PLCs demonstrating improvements across all five metrics. Moreover, the CVTCC revealed a substantial 90.9% agreement. Conclusions: Our results highlight the effectiveness of LWP and TM in streamlining IMS classification. Anticipated enhancements to LWP's region of interest (ROI) isolation and TM's ROI targeting are expected to boost accuracy, positioning them as a potential alternative to CNNs for IMS classification, supporting the need for further research.

Development and internal validation of machine learning-based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke.

Aims: We developed new machine learning (ML) models and externally validated existing statistical models [ischaemic stroke predictive risk score (iScore) and totalled health risks in vascular events (THRIVE) scores] for predicting the composite of recurrent stroke or all-cause mortality at 90 days and at 3 years after hospitalization for first acute ischaemic stroke (AIS). Methods and results: In adults hospitalized with AIS from January 2005 to November 2016, with follow-up until November 2019, we developed three ML models [random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBOOST)] and externally validated the iScore and THRIVE scores for predicting the composite outcomes after AIS hospitalization, using data from 721 patients and 90 potential predictor variables. At 90 days and 3 years, 11 and 34% of patients, respectively, reached the composite outcome. For the 90-day prediction, the area under the receiver operating characteristic curve (AUC) was 0.779 for RF, 0.771 for SVM, 0.772 for XGBOOST, 0.720 for iScore, and 0.664 for THRIVE. For 3-year prediction, the AUC was 0.743 for RF, 0.777 for SVM, 0.773 for XGBOOST, 0.710 for iScore, and 0.675 for THRIVE. Conclusion: The study provided three ML-based predictive models that achieved good discrimination and clinical usefulness in outcome prediction after AIS and broadened the application of the iScore and THRIVE scoring system for long-term outcome prediction. Our findings warrant comparative analyses of ML and existing statistical method-based risk prediction tools for outcome prediction after AIS in new data sets.

Captivating actions of pomological crops waste as biosorbents for environmental remediation: a comprehensive review.

Water pollutants are an emerging environmental hurdle for crop production and human health risks. In recent decades, the removal of contaminants from water using a cutting-edge approach like biosorbents is a strategy that is both cost-efficient and sustainable. For instance, since biowaste from fruit crops implies the frequent occurrence of average annual waste, it is imperative to formulate strategic initiatives to mitigate this emerging problem while simultaneously recognizing the potential for reutilization and reintroduction of such waste into the industrial sector. Fruit crops such as peels, seeds, skins, branches and stalks can be altered into biosorbents for water treatment. Partially mitigating the adverse impacts of biowaste that estimate to incur costs of billions of dollars around the world would be achieved with this engineering application. This review provides a perspective on the existing literature and brings up-to-date information and findings in the field of pomological crop waste as biosorbents for environmental remediation. In this way, we review the detrimental impact of environmental contaminants on biological organisms and different types of fruit crop waste and their utilization for wastewater treatment, with special emphasis on the formulation of biowaste sorbents (removal efficiency is > 80%) and their application for capturing pollutants such as heavy metals, organic and inorganic dyes and oils. Besides, the newly invented techniques for the characterization of fruit-based biosorbents, the parametric evaluation of biosorbents and their comparison with other available biosorbents are discussed. This review will be helpful for remediating contaminants in wastewater and a panacea for practical engineering solutions.

Clinicoradiological parameters predicting operative difficulty in laparoscopic partial nephrectomy for renal tumors.

Introduction: The number of renal tumors amenable to laparoscopic surgery is rising, both, due early detection by improved imaging techniques and due to progressive improvements in minimal access surgery. Conversion to open surgery, which is a significant event, can be minimized by proper case selection. We assessed the pre-operative factors that can predict the operative difficulty and can help in case selection, thus avoiding complications and reducing the chances of conversion to open. Methods: One hundred and sixteen patients (73 males and 43 females) with the mean age of 50.78 ± 14.2 years, meeting the inclusion criteria underwent transperitoneal laparoscopic partial nephrectomy (LPN). Various clinical, anthropometric, radiological, and pathological parameters were recorded. Intraoperative difficulty was assessed and graded on a scale of 1 (easiest) to 4 (most difficult or open conversion) by an independent observer to calculate the difficulty score, which along with the other parameters of operative difficulty, was used to calculate the difficulty scale. Significant parameters on the univariate analysis, were subjected to a multivariate analysis, to find parameters that can predict the operative difficulty. Results: The mean age was 52 ± 14.29 years, mean size was 4 ± 1.04 cm, male:female ratio was 1.6:1, most of the tumors were exophytic (60%) and anteriorly located (62%) and had a mean perinephric fat surface density (PnFSD) of 6446.026 ± 2244 surface density pixel units (SDPU). On the univariate analysis, age >60 years, Eastern Cooperative Oncology Group performance score >1, presence of perinephric fat stranding, increased PnFSD (>10,000 SDPU), large tumor size (>4 cm), hilar/posterior location, endophytic tumors and higher clinical stage were significantly associated with intraoperative difficulty. However, on the multivariate analysis, no single factor could independently predict intraoperative difficulty in LPN for Renal tumors. Conclusion: It is difficult to predict the intra-operative difficulty during LPN. Feasibility of LPN should be based on multiple factors rather than a single factor.

Adverse effects of tyrosine kinase inhibitors in cancer therapy: pathophysiology, mechanisms and clinical management.

Since their invention in the early 2000s, tyrosine kinase inhibitors (TKIs) have gained prominence as the most effective pathway-directed anti-cancer agents. TKIs have shown significant utility in the treatment of multiple hematological malignancies and solid tumors, including chronic myelogenous leukemia, non-small cell lung cancers, gastrointestinal stromal tumors, and HER2-positive breast cancers. Given their widespread applications, an increasing frequency of TKI-induced adverse effects has been reported. Although TKIs are known to affect multiple organs in the body including the lungs, liver, gastrointestinal tract, kidneys, thyroid, blood, and skin, cardiac involvement accounts for some of the most serious complications. The most frequently reported cardiovascular side effects range from hypertension, atrial fibrillation, reduced cardiac function, and heart failure to sudden death. The potential mechanisms of these side effects are unclear, leading to critical knowledge gaps in the development of effective therapy and treatment guidelines. There are limited data to infer the best clinical approaches for the early detection and therapeutic modulation of TKI-induced side effects, and universal consensus regarding various management guidelines is yet to be reached. In this state-of-the-art review, we examine multiple pre-clinical and clinical studies and curate evidence on the pathophysiology, mechanisms, and clinical management of these adverse reactions. We expect that this review will provide researchers and allied healthcare providers with the most up-to-date information on the pathophysiology, natural history, risk stratification, and management of emerging TKI-induced side effects in cancer patients.

Giant right hydronephrosis with underlying double malignancy: a case report.

Giant hydronephrosis is mostly caused by ureteropelvic junction obstruction (UPJO). Giant hydronephrosis with concurrent malignancy is less common clinically and is easily misdiagnosed. We report a 77-year-old male who presented with sudden onset progressive abdominal distension in the last month. Abdominal computed tomography showed a right severe hydronephrotic kidney with loss of parenchymal thinning. Cystoscopy showed a 1x1cm papillary lesion protruding from the right ureteric orifice. He underwent a right radical nephroureterectomy with bladder cuff excision with lymph node dissection. Histopathology showed low-grade urothelial carcinoma of the ureter and incidental pleomorphic rhabdomyosarcoma in the right kidney. The patient refused chemotherapy and died 6 months later due to lung metastasis. Incidental pathologic finding of renal rhabdomyosarcoma in adults with giant hydronephrosis and urothelial carcinoma is a rare occurrence with diverse clinical presentations, prognoses, and outcomes.

Phospholipid Encapsulation of an Anti-Fibrotic Endopeptide to Enhance Cellular Uptake and Myocardial Retention.

BACKGROUND: Cardioprotective effects of N-acetyl-ser-asp-lys-pro (Ac-SDKP) have been reported in preclinical models of myocardial remodeling. However, the rapid degradation of this endogenous peptide in vivo limits its clinical use. METHOD: To prolong its bioavailability, Ac-SDKP was encapsulated by phosphocholine lipid bilayers (liposomes) similar to mammalian cell membranes. The physical properties of the liposome structures were assessed by dynamic light scattering and scanning electron microscopy. The uptake of Ac-SDKP by RAW 264.7 macrophages and human and murine primary cardiac fibroblasts was confirmed by fluorescence microscopy and flow cytometry. Spectrum computerized tomography and competitive enzyme-linked immunoassays were performed to measure the ex vivo cardiac biodistribution of Ac-SDKP. The biological effects of this novel synthetic compound were examined in cultured macrophages and cardiac fibroblasts and in a murine model of acute myocardial infarction induced by permanent coronary artery ligation. RESULTS: A liposome formulation resulted in the greater uptake of Ac-SDKP than the naked peptide by cultured RAW 264.7 macrophages and cardiac fibroblasts. Liposome-delivered Ac-SDKP decreased fibroinflammatory genes in cultured cardiac fibroblasts co-treated with TGF-ß1 and macrophages stimulated with LPS. Serial tissue and serum immunoassays showed the high bioavailability of Ac-SDKP in mouse myocardium and in circulation. Liposome-delivered Ac-SDKP improved cardiac function and reduced myocardial fibroinflammatory responses in mice with acute myocardial infarction. CONCLUSION: Encapsulation of Ac-SDKP in a cell membrane-like phospholipid bilayer enhances its plasma and tissue bioavailability and offers cardioprotection against ischemic myocardial injury. Future clinical trials can use this novel approach to test small protective endogenous peptides in myocardial remodeling.

Primary malignant melanoma of prostate: a case report.

While primary genitourinary melanomas account for less than 1% of all melanoma cases, prostatic melanoma is extremely uncommon. These patients are challenging to identify, with a dismal prognosis. We reported a 52-year-old male patient who presented with lower urinary tract symptoms in the last one and a half months. The patient underwent Holmium laser enucleation of the prostate, and the histopathology result of the resected specimen showed prostatic melanoma. Investigations for systemic melanoma evaluation were negative, and the patient underwent radical cystoprostatectomy, urethrectomy, and bilateral lymph node dissection. The patient refused chemotherapy, developed lung metastasis shortly after surgery at three months, and succumbed to the metastatic disease with overall survival of 6 months. In conclusion, primary malignant melanoma of the prostate is a very rare disease. The most logical therapeutic strategy is aggressive surgical resection, followed immediately by adjuvant therapy.

Galectin-3 Is Associated with Cardiac Fibrosis and an Increased Risk of Sudden Death.

BACKGROUND: Myocardial fibrosis is a common postmortem finding among individuals with Sudden Cardiac Death (SCD). Numerous in vivo and in vitro studies have shown that increased galectin-3 (gal3) expression into the myocardium is associated with higher incidence of fibrosis. Although elevated gal3 expression is linked with myocardial fibrosis, its role in predicting the risk of SCD is unknown. METHODS: We reviewed the clinical datasets and post-mortem examination of 221 subjects who had died suddenly. We examined myocardial pathology including the extent of cardiac hypertrophy, fibrosis, and the degree of coronary atherosclerosis in these subjects. In a select group of SCD subjects, we studied myocardial gal3 and periostin expression using immunohistochemistry. To further examine if a higher level of circulating gal3 can be detected preceding sudden death, we measured serum gal3 in a porcine model of subtotal coronary artery ligation which shows an increased tendency to develop lethal cardiac arrhythmias, including ventricular tachycardia or fibrillation. RESULTS: Of the total 1314 human subjects screened, 12.7% had SCD. Comparison of age-matched SCD with non-SCD subjects showed that SCD groups had excessive myocardial fibrosis involving both the left ventricular free wall and interventricular septum. In pigs with subtotal coronary artery ligation and SCD, we detected significantly elevated circulating gal3 levels approximately 10 days preceding the SCD event. Immunohistochemistry showed increased myocardial gal3 and periostin expression in pigs that died suddenly, compared to the controls. CONCLUSION: Our study shows that increased gal3 is associated with a higher risk of myocardial fibrosis and the risk of SCD. This supports the importance of larger translational studies to target gal3 to prevent cardiac fibrosis and attenuate the risk of SCD.

Predicting 30-day all-cause hospital readmission using multimodal spatiotemporal graph neural networks.

Reduction in 30-day readmission rate is an important quality factor for hospitals as it can reduce the overall cost of care and improve patient post-discharge outcomes. While deep-learning-based studies have shown promising empirical results, several limitations exist in prior models for hospital readmission prediction, such as: (a) only patients with certain conditions are considered, (b) do not leverage data temporality, (c) individual admissions are assumed independent of each other, which ignores patient similarity, (d) limited to single modality or single center data. In this study, we propose a multimodal, spatiotemporal graph neural network (MM-STGNN) for prediction of 30-day all-cause hospital readmission, which fuses in-patient multimodal, longitudinal data and models patient similarity using a graph. Using longitudinal chest radiographs and electronic health records from two independent centers, we show that MM-STGNN achieved an area under the receiver operating characteristic curve (AUROC) of 0.79 on both datasets. Furthermore, MM-STGNN significantly outperformed the current clinical reference standard, LACE+ (AUROC=0.61), on the internal dataset. For subset populations of patients with heart disease, our model significantly outperformed baselines, such as gradient-boosting and Long Short-Term Memory models (e.g., AUROC improved by 3.7 points in patients with heart disease). Qualitative interpretability analysis indicated that while patients' primary diagnoses were not explicitly used to train the model, features crucial for model prediction may reflect patients' diagnoses. Our model could be utilized as an additional clinical decision aid during discharge disposition and triaging high-risk patients for closer post-discharge follow-up for potential preventive measures.

An artificial intelligence approach for predicting death or organ failure after hospitalization for COVID-19: development of a novel risk prediction tool and comparisons with ISARIC-4C, CURB-65, qSOFA, and MEWS scoring systems.

BACKGROUND: We applied machine learning (ML) algorithms to generate a risk prediction tool [Collaboration for Risk Evaluation in COVID-19 (CORE-COVID-19)] for predicting the composite of 30-day endotracheal intubation, intravenous administration of vasopressors, or death after COVID-19 hospitalization and compared it with the existing risk scores. METHODS: This is a retrospective study of adults hospitalized with COVID-19 from March 2020 to February 2021. Patients, each with 92 variables, and one composite outcome underwent feature selection process to identify the most predictive variables. Selected variables were modeled to build four ML algorithms (artificial neural network, support vector machine, gradient boosting machine, and Logistic regression) and an ensemble model to generate a CORE-COVID-19 model to predict the composite outcome and compared with existing risk prediction scores. The net benefit for clinical use of each model was assessed by decision curve analysis. RESULTS: Of 1796 patients, 278 (15%) patients reached primary outcome. Six most predictive features were identified. Four ML algorithms achieved comparable discrimination (P > 0.827) with c-statistics ranged 0.849-0.856, calibration slopes 0.911-1.173, and Hosmer-Lemeshow P > 0.141 in validation dataset. These 6-variable fitted CORE-COVID-19 model revealed a c-statistic of 0.880, which was significantly (P < 0.04) higher than ISARIC-4C (0.751), CURB-65 (0.735), qSOFA (0.676), and MEWS (0.674) for outcome prediction. The net benefit of the CORE-COVID-19 model was greater than that of the existing risk scores. CONCLUSION: The CORE-COVID-19 model accurately assigned 88% of patients who potentially progressed to 30-day composite events and revealed improved performance over existing risk scores, indicating its potential utility in clinical practice.

'Stakeholders are almost always resistant': Australian behaviour support practitioners' perceptions of the barriers and enablers to reducing restrictive practices.

A restrictive practice (RP) is defined as a practice or intervention that has the effect of restricting the rights or freedom of movement of a person, and includes physical, mechanical, and chemical restraint, and seclusion. If misused or overused, RPs may present serious human rights infringements. In Australia, behaviour support practitioners who deliver behaviour support funded by the National Disability Insurance Scheme are responsible for developing positive behaviour support plans that aim to reduce and eliminate the use of RPs. At present, little is known about the barriers that behaviour support practitioners experience when attempting to reduce and eliminate the use of RPs and, conversely, what helps (or enables) them to reduce and eliminate RPs. To learn more, we conducted an online survey consisting of two open-ended questions with 109 Australian behaviour support practitioners to identify barriers and enablers. We found that fear and reluctance on the part of stakeholders were often barriers to reducing the use of RPs. However, we found that having time, funding, and resources for training, supervision, other implementation activities, care team collaboration, and data-based decision-making helped overcome barriers. We provide specific recommendations for addressing identified barriers for individual behaviour support practitioners, service provider organisations, and government and regulatory agencies.

Risk factors associated with higher mortality in patients with cardiac implantable electronic device infection.

INTRODUCTION: Cardiac Implantable Electronic Devices (CIEDs) are widely used for the management of advanced heart failure and ventricular arrhythmias. CIED-Infection (CIED-I) has very high mortality, especially in the subsets of patients with limited health-care access and delayed presentation. The purpose of this study is to identify the risk-predictors mortality in subjects with CIED-I. METHODS: We performed a retrospective cohort study of a regional database in patients presenting with CIED infections to tertiary care medical centers across Western New York, USA from 2012 to 2020. The clinical outcomes included recurrent device infection (any admission for CIED-I after the first hospitalization for device infection), septic complications (pulmonary embolism, respiratory failure, septic shock, decompensated HF, acute kidney injury) and mortality outcomes (death during hospitalization, within 30 days from CIED-I, and within 1 year from CIED-I). We studied associations between categorical variables and hard outcomes using χ2 tests and used one-way analysis of variance to measure between-groups differences. RESULTS: We identified 296 patients with CIED-I, among which 218 (74%) were male, 237 (80%) were white and the mean age at the time of infection was 69.2 ± 13.7 years. One-third of the patients were referred from the regional facilities. Staphylococcus aureus was responsible for most infections, followed by Enterococcus fecalis. On multivariate analysis, the covariates associated with significantly increased mortality risk included referral from regional facility (OR: 2.0;1.0-4.0), hypertension (Odds ratio, OR: 3.2;1.3-8.8), right ventricular dysfunction (OR: 2.6;1.2-5.1), end-stage renal disease (OR: 2.6;1.1-6.2), immunosuppression (OR: 11.4;2.5-53.3), and septic shock as a complication of CIED-I (OR: 3.9;1.3-10.8). CONCLUSION: Hypertension, right ventricular dysfunction, immunosuppression, and end-stage renal disease are associated with higher mortality after CIED-I. Disproportionately higher mortality was also noted in subjects referred from the regional facilities. This underscores the importance of early clinical risk-assessment, and the need for a robust referral infrastructure to improve patient outcomes.

Left atrial appendage volume as a prognostic Indicator of long-term mortality in Cancer survivors treated with thoracic radiation.

BACKGROUND: Cancer survivors with prior chest radiation therapy (CXRT) frequently present with atrial fibrillation, heart failure, and have higher overall long-term mortality. There are no data examining the utility of left atrial (LA) and LA appendage (LAA) volume-indices to predict clinical outcomes in these patients. OBJECTIVES: We examined the prognostic value of cardiac phase-dependent 3-D volume-rendered cardiac computerized tomography (CT)-derived LA and LAA volume-indices to predict mortality and major adverse cardiac events (MACE) in cancer survivors treated with thoracic irradiation. METHOD: We screened 625 consecutive patients with severe aortic stenosis who had undergone transcatheter aortic valve replacement from 2012 to 2017. Based on the gated cardiac CT image quality, we included 184 patients (CXRT:43, non-CXRT:141) for further analysis. We utilized multiplane-3D-reconstructed cardiac CT images to calculate LA and LAA volume-indices, and examined the prognostic role of CCT-derived LA and LAA volume-indices in predicting the all-cause mortality, cardiovascular (CV) mortality, and MACE. We used multivariate cox-proportional hazard analysis to identify the clinical predictors of survival. RESULTS: Overall, the CXRT group had significantly elevated LAA volume-index compared to non-CXRT group (CXRT:11.2 ± 8.9 ml/m2; non-CXRT:8.6 ± 4.5 ml/m2, p = 0.03). On multivariate cox-proportional hazard analysis, the elevated LAA volume and LAA volume-index were the strongest predictors of reduced survival in CXRT group compared to non-CXRT group (LAA volume: RR = 1.03,95% CI 1.0-1.01, p = 0.01; and LAA volume index: RR = 1.05, 95% CI 1.0-1.01, p = 0.03). LAA volume > 21.9 ml was associated with increased mortality. In contrast, LA volume was not a significant predictor of mortality. CONCLUSION: We describe a novel technique to assess LA and LAA volume using 3-D volume-rendered cardiac CT. This study shows enlarged LAA volume rather than LA volume carries a poor prognosis in cancer-survivors treated with prior CXRT. Compared to conventionally reported markers, LAA volume of > 21.9 ml was incremental to that of other risk factors.

Characteristics, Treatment Patterns, and Clinical Outcomes After Heart Failure Hospitalizations During the COVID-19 Pandemic, March to October 2020.

OBJECTIVE: To compare clinical characteristics, treatment patterns, and 30-day all-cause readmission and mortality between patients hospitalized for heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic. PATIENTS AND METHODS: The study was conducted at 16 hospitals across 3 geographically dispersed US states. The study included 6769 adults (mean age, 74 years; 56% [5033 of 8989] men) with cumulative 8989 HF hospitalizations: 2341 hospitalizations during the COVID-19 pandemic (March 1 through October 30, 2020) and 6648 in the pre-COVID-19 (October 1, 2018, through February 28, 2020) comparator group. We used Poisson regression, Kaplan-Meier estimates, multivariable logistic, and Cox regression analysis to determine whether prespecified study outcomes varied by time frames. RESULTS: The adjusted 30-day readmission rate decreased from 13.1% (872 of 6648) in the pre-COVID-19 period to 10.0% (234 of 2341) in the COVID-19 pandemic period (relative risk reduction, 23%; hazard ratio, 0.77; 95% CI, 0.66 to 0.89). Conversely, all-cause mortality increased from 9.7% (645 of 6648) in the pre-COVID-19 period to 11.3% (264 of 2341) in the COVID-19 pandemic period (relative risk increase, 16%; number of admissions needed for one additional death, 62.5; hazard ratio, 1.19; 95% CI, 1.02 to 1.39). Despite significant differences in rates of index hospitalization, readmission, and mortality across the study time frames, the disease severity, HF subtypes, and treatment patterns remained unchanged (P>0.05). CONCLUSION: The findings of this large tristate multicenter cohort study of HF hospitalizations suggest lower rates of index hospitalizations and 30-day readmissions but higher incidence of 30-day mortality with broadly similar use of HF medication, surgical interventions, and devices during the COVID-19 pandemic compared with the pre-COVID-19 time frame.

Effect of Organic Manures on Growth, Yield, Leaf Nutrient Uptake and Soil Properties of Kiwifruit (Actinidia deliciosa Chev.) cv. Allison.

In recent decades, organic kiwifruit farming has come up as a feasible method for high-quality kiwi production without using chemical fertilizers. The primary objective of this research was to investigate how the sole application of organic and the combined application of organic manures affected the growth, yields, and quality of Allison kiwifruit, as well as the soil's physicochemical characteristics. The field trial was conducted on cv. Allison to determine the efficacy of organic manures (OM) on growth, nutrient absorption, production and soil health. The experiment involved eight treatments, viz.: T1: 100% Dairy manure (DM); T2: 100% Vermicompost (VC); T3: 100% chicken manure (CM); T4: 50% DM + 50% CM; T5: 50% DM + 50% VC; T6: 50% CM + 50% VC; T7: DM + CM + VC in equal proportions; and T8: Recommended nutrients inorganic NPK + 40 kg DM. A randomized complete block design comprising three replicas was used in this investigation. The use of inorganic fertilizers (NPK) in combination with DM enhanced Spad Values Chlorophyll, fruit production, leaf number, leaf area, and stem diameter while also improving the soil's chemical characteristics. The flower initiation was recorded with DM and Vermicompost (50:50). Furthermore, when compared to inorganic fertilizer treatment, OM treatment significantly improved fruit quality by improving fruit chemical composition in terms of soluble solids contents and leaf nutrient status, as well as improving soil's physical properties with DM and Vermicompost (50:50). The study's outcome revealed that OM had a significant impact on flowering time, fruit SSC, leaf nutritional status, and soil physical characteristics. In comparison to organic treatments, recommended fertilizer dosages (NPK + DM) improved plant growth, fruit yield, and soil chemical characteristics.