Association of Metabolic Syndrome with Stroke, Myocardial Infarction, and Other Postoperative Complications Following Carotid Endarterectomy: A Multicenter, Retrospective Cohort Study.

BACKGROUND: Metabolic syndrome (MetS) is a constellation of hypertension, insulin resistance, obesity, and dyslipidemia and is known to increase the risk of postoperative morbidity. This study aimed to assess the impact of MetS on stroke, myocardial infarction, mortality, and other complications following carotid endarterectomy (CEA). METHODS: We analyzed data from the National Surgical Quality Improvement Program. Patients undergoing elective CEA between 2011 and 2020 were included. Patients with American Society of Anesthesiologists status 5, preoperative length of stay (LOS) > 1 day, ventilator dependence, admission from nonhome location, and ipsilateral internal carotid artery stenosis of < 50% or 100% were excluded. A composite cardiovascular outcome for postoperative stroke, myocardial infarction, and mortality was generated. Multivariable binary logistic regression analyses were used to assess the association of MetS with the composite outcome and other perioperative complications. RESULTS: We included 25,226 patients (3,613, 14.3% with MetS). MetS was associated with postoperative stroke, unplanned readmission, and prolonged LOS on bivariate analysis. On multivariable analysis, MetS was significantly associated with the composite cardiovascular outcome (1.320 [1.061-1.642]), stroke (1.387 [1.039-1.852]), unplanned readmission (1.399 [1.210-1.619]), and prolonged LOS (1.378 [1.024-1.853]). Other clinico-demographic factors associated with the cardiovascular outcome included Black race, smoking status, anemia, leukocytosis, physiologic risk factors, symptomatic disease, preoperative beta-blocker use, and operative time ≥ 150 min. CONCLUSIONS: MetS is associated with cardiovascular complications, stroke, prolonged LOS, and unplanned readmissions following CEA. Surgeons should provide optimized care to this high-risk population and strive to reduce operative durations.

Application of Biosafety Principles in Laboratory Analysis of Clinical Samples from Patients with COVID-19.

COVID-19 poses a great challenge to clinical and diagnostic services around the world. The need of biosafety practices can never be emphasised more than under current circumstances. The four pillars of biosafety namely, leadership, standard operating procedures, personal protective equipment (PPE) and engineering controls must be employed for effective and safe practices in the clinical setting in general and laboratory settings in particular. Risk assessment must be carried out before meeting up the diagnostic challenge for COVID-19 and essential biorisk management measures are required to be taken. In our resource-poor settings, we need to adapt safe but cost-effective and improvised solutions to ensure safe handling of clinical samples from COVID-19 patients in the laboratories. The correct use of PPE and their suitable alternatives are available for selection and use. Disinfection of the lab areas and safe disposal of the clinical samples from such patients is also of paramount importance.

Evaluation of galactomannan and beta-d-glucan assays for the diagnosis of invasive aspergillosis in clinically suspected cases.

OBJECTIVE: To assess the utility of galactomannan and beta-D-glucan assays in the diagnosis of invasive aspergillosis in clinically suspected cases, and to compare their diagnostic potential to determine whether a combination of the two may result in an early and specific diagnosis. METHODS: The descriptive cross-sectional case-control study was conducted at the Armed Forces Institute of Pathology, Rawalpindi, Pakistan, from April 1, 2017, to March 31, 2018, and comprised serum samples from clinically suspected invasive aspergillosis patients and healthy controls. The sera were tested for galactomannan and beta-D-glucan detection. Proven, probable and possible categories of invasive aspergillosis according to European Organisation for Research and Treatment of Cancer / Invasive Fungal Infections Cooperative Group and the National Institute of Allergy and Infectious Diseases Mycoses Study Group criteria. Galactomannan antigen was detected using a one-stage immunoenzymatic sandwich microplate assay. Beta-D-Glucan antigen was detected using a protease zymogen-based colorimetric assay. Sensitivity and positive / negative likelihood ratio of both the cases and the controls were calculated and compared. RESULTS: Of the 178 subjects, 119(67%) were cases and 59(33%) were controls. Beta-D-glucan assay was more sensitive than galactomannan assay (91.6% versus 80.67%) whereas galactomannan assay was more specific than beta-D-glucan assay (86.44% versus 76.27%) in the diagnosis of invasive aspergillosis. The sensitivities of both assays decreased with decreasing probability of invasive aspergillosis, i.e., maximum sensitivities of both beta-D-glucan and galactomannan assays were for proven cases (100% versus 87.5%), followed by probable cases (89.29% versus 85.71%), and possible cases (91.57% versus 78.31%). CONCLUSIONS: Both beta-D-glucan and galactomannan assays seemed to play an encouraging role in the diagnosis of invasive aspergillosis in high-risk clinically suspected cases, with the former assay being more sensitive and the latter assay being more specific.

Breast Cancer Detection and Diagnosis Using Mammographic Data: Systematic Review.

BACKGROUND: Machine learning (ML) has become a vital part of medical imaging research. ML methods have evolved over the years from manual seeded inputs to automatic initializations. The advancements in the field of ML have led to more intelligent and self-reliant computer-aided diagnosis (CAD) systems, as the learning ability of ML methods has been constantly improving. More and more automated methods are emerging with deep feature learning and representations. Recent advancements of ML with deeper and extensive representation approaches, commonly known as deep learning (DL) approaches, have made a very significant impact on improving the diagnostics capabilities of the CAD systems. OBJECTIVE: This review aimed to survey both traditional ML and DL literature with particular application for breast cancer diagnosis. The review also provided a brief insight into some well-known DL networks. METHODS: In this paper, we present an overview of ML and DL techniques with particular application for breast cancer. Specifically, we search the PubMed, Google Scholar, MEDLINE, ScienceDirect, Springer, and Web of Science databases and retrieve the studies in DL for the past 5 years that have used multiview mammogram datasets. RESULTS: The analysis of traditional ML reveals the limited usage of the methods, whereas the DL methods have great potential for implementation in clinical analysis and improve the diagnostic capability of existing CAD systems. CONCLUSIONS: From the literature, it can be found that heterogeneous breast densities make masses more challenging to detect and classify compared with calcifications. The traditional ML methods present confined approaches limited to either particular density type or datasets. Although the DL methods show promising improvements in breast cancer diagnosis, there are still issues of data scarcity and computational cost, which have been overcome to a significant extent by applying data augmentation and improved computational power of DL algorithms.

Sentinel Lymph Node Biopsy for Recurrent Melanoma: A Multicenter Study.

BACKGROUND: Sentinel lymph node biopsy (SLNB) is routinely performed for primary cutaneous melanomas; however, limited data exist for SLNB after locally recurrent (LR) or in-transit (IT) melanoma. METHODS: Data from three centers performing SLNB for LR/IT melanoma (1997 to the present) were reviewed, with the aim of assessing (1) success rate; (2) SLNB positivity; and (3) prognostic value of SLNB in this population. RESULTS: The study cohort included 107 patients. Management of the primary melanoma included prior SLNB for 56 patients (52%), of whom 10 (18%) were positive and 12 had complete lymph node dissections (CLNDs). In the present study, SLNB was performed for IT disease (48/107, 45%) or LR melanoma (59/107, 55%). A sentinel lymph node (SLN) was removed in 96% (103/107) of cases. Nodes were not removed for four patients due to lymphoscintigraphy failures (2) or nodes not found during surgery (2). SLNB was positive in 41 patients (40%, 95% confidence interval (CI) 31.5-50.5), of whom 35 (88%) had CLND, with 13 (37%) having positive nonsentinel nodes. Median time to disease progression after LR/IT metastasis was 1.4 years (95% CI 0.75-2.0) for patients with a positive SLNB, and 5.9 years (95% CI 1.7-10.2) in SLNB-negative patients (p = 0.18). There was a trend towards improved overall survival for patients with a negative SLNB (p = 0.06). CONCLUSION: SLNB can be successful in patients with LR/IT melanoma, even if prior SLNB was performed. In this population, the rates of SLNB positivity and nonsentinel node metastases were 40% and 37%, respectively. SLNB may guide management and prognosis after LR/IT disease.

Assessment of the importance and catalytic role of chromium oxide and chromium carbide for hydrogen generation via hydrolysis of magnesium.

Increasing energy demands and low-carbon emission energy carriers are global challenges for renewable energy resources. Regarding the aforementioned issues, magnesium-based composites are promising candidates for energy carriers. However, rapid initial hydrolysis kinetics and higher hydrogen yields are the objectives for practical applications. In this study, chromium-based catalysts (Cr2O3 and Cr3C2) were employed via ball milling to activate Mg. Finally, we used Mg-X wt% Y (X = 1, 3, 5, and 10; Y = Cr2O3 and Cr3C2) composites to produce hydrogen. Mg-10 wt% Cr2O3 can produce 798 and 812 mL g-1 hydrogen, while Mg-10 wt% Cr3C2 can produce 821 and 831.6 mL g-1 hydrogen in seawater and 0.5 M MgCl2 solutions, respectively. Additionally, Cr2O3 and Cr3C2 significantly improve the Mg hydrolysis activation energies. However, by incorporating Cr2O3 and Cr3C2, the activation energies for the hydrolysis of Mg with seawater achieved were 19.5 kJ mol-1 and 17.3 kJ mol-1, while they reduced to 15.7 kJ mol-1 and 14.4 kJ mol-1 with 0.5 M MgCl2 solutions, respectively. In comparison, Mg-10 wt% Cr3C2 composite exhibits superior performance, which is attributed to the higher anode potential value of Cr3C2. This work accelerates the hydrolysis kinetics and provides a sufficient technique to produce hydrogen from Mg composites for application in portable devices.

Diagnostic Accuracy of Polymerase Chain Reaction Against Giemsa Staining on Tissue Biopsy for Cutaneous Leishmaniasis.

OBJECTIVE: To evaluate the diagnostic accuracy of a commercial real-time polymerase chain reaction (PCR) kit targeting 18S rRNA against Giemsa-stained tissue slides in patients clinically suspected of cutaneous leishmaniasis (CL). STUDY DESIGN: Cross-sectional analytical study. Place and Duration of the Study: Department of Microbiology, Armed Forces Institute of Pathology / National University of Medical Sciences, Rawalpindi, Pakistan, from July to December 2022. METHODOLOGY: Samples of skin tissue in 98 patients suspected of CL were evaluated. These samples were subjected to Giemsa-staining for microscopy and real-time PCR. Sensitivity, specificity, and accuracy of the PCR were calculated keeping Giemsa-stained tissue slide microscopy as gold standard. RESULTS: Out of the 98 tissue samples, 37 were found positive for leishmaniasis on PCR while 13 were found Leishmania positive on microscopy of Giemsa-stained slides. The sensitivity, specificity, and accuracy of the PCR for the detection of Leishmania species were 100%, 71.8%, and 91.8%, respectively with 100% negative predictive value. CONCLUSION: This study demonstrates that the commercial PCR is a reliable diagnostic test for the diagnosis of CL. The ease, rapidity, and reliability of the PCR make it a dependable tool in diagnostic repertoire of CL. KEY WORDS: Giemsa stain, Leishmania spp., Polymerase chain reaction, Viasure.

Unfavorable social determinants of health and risk of mortality in adults with diabetes: findings from the National Health Interview Survey.

INTRODUCTION: Understanding the role of social determinants of health as predictors of mortality in adults with diabetes may help improve health outcomes in this high-risk population. Using population-based, nationally representative data, this study investigated the cumulative effect of unfavorable social determinants on all-cause mortality in adults with diabetes. RESEARCH DESIGN AND METHODS: We used data from the 2013-2018 National Health Interview Survey, linked to the National Death Index through 2019, for mortality ascertainment. A total of 47 individual social determinants of health were used to categorize participants in quartiles denoting increasing levels of social disadvantage. Poisson regression was used to report age-adjusted mortality rates across increasing social burden. Multivariable Cox proportional hazards models were used to assess the association between cumulative social disadvantage and all-cause mortality in adults with diabetes, adjusting for traditional risk factors. RESULTS: The final sample comprised 182 445 adults, of whom 20 079 had diabetes. In the diabetes population, mortality rate increased from 1052.7 per 100 000 person-years in the first quartile (Q1) to 2073.1 in the fourth quartile (Q4). In multivariable models, individuals in Q4 experienced up to twofold higher mortality risk relative to those in Q1. This effect was observed similarly across gender and racial/ethnic subgroups, although with a relatively stronger association for non-Hispanic white participants compared with non-Hispanic black and Hispanic subpopulations. CONCLUSIONS: Cumulative social disadvantage in individuals with diabetes is associated with over twofold higher risk of mortality, independent of established risk factors. Our findings call for action to screen for unfavorable social determinants and design novel interventions to mitigate the risk of mortality in this high-risk population.

Risk Factors of Acute Ischemic Stroke and Mortality Among Adults With Endocardial Fibroelastosis.

OBJECTIVES: Endocardial fibroelastosis (EFE) is a rare form of restrictive cardiomyopathy associated with high morbidity and mortality. The literature is sparse on information pertaining to risk stratification. Thus, we sought to highlight the risk factors of acute ischemic stroke (AIS) and mortality in adults with EFE. METHODS: The National Inpatient Sample (NIS) database was queried from 2001 to 2020 using the International Classification of Diseases 9th Revision (ICD-9) and 10th Revision (ICD-10) codes for adult patients with EFE. Factors associated with AIS and mortality were identified. RESULTS: In all, 18495 cases of EFE fit the inclusion criteria, of which 2370 (12.82%) had AIS. The mean ages for patients with and without AIS were 62.37 and 54.24, respectively. Multivariate regression suggested greater odds of AIS in patients with hypertension (aOR 2.329, P<0.01), dyslipidemia (aOR: 1.566, P<0.01), peripheral vascular disease (PVD) (aOR: 1.736, P<0.01), alcohol abuse (aOR: 1.817, P<0.01), age >60 y (aOR: 1.646, P<0.01), females (vs. males, aOR: 1.238, P<0.01), and smokers (aOR: 1.697, P<0.01). Patients with cirrhosis (aOR: 0.174, P<0.01), CKD (aOR: 0.369, P<0.01), COPD (aOR: 0.402, P<0.01), atrial fibrillation (aOR: 0.542, P<0.01) had lower odds of AIS. 3.1% of EFE patients with AIS died. Diabetes (aOR: 11.665, P<0.01) and COPD (aOR: 3.201, P=0.017) were associated with the greatest odds of all-cause mortality. Dyslipidemia (aOR: 0.387, P=0.010) and females (vs. males, aOR: 0.432, P=0.012) had reduced odds of all-cause mortality. CONCLUSION: Several risk factors are associated with AIS in EFE, while diabetes, COPD, and being male are associated with mortality in EFE.

Merlin: A Vision Language Foundation Model for 3D Computed Tomography.

Over 85 million computed tomography (CT) scans are performed annually in the US, of which approximately one quarter focus on the abdomen. Given the current shortage of both general and specialized radiologists, there is a large impetus to use artificial intelligence to alleviate the burden of interpreting these complex imaging studies while simultaneously using the images to extract novel physiological insights. Prior state-of-the-art approaches for automated medical image interpretation leverage vision language models (VLMs) that utilize both the image and the corresponding textual radiology reports. However, current medical VLMs are generally limited to 2D images and short reports. To overcome these shortcomings for abdominal CT interpretation, we introduce Merlin - a 3D VLM that leverages both structured electronic health records (EHR) and unstructured radiology reports for pretraining without requiring additional manual annotations. We train Merlin using a high-quality clinical dataset of paired CT scans (6+ million images from 15,331 CTs), EHR diagnosis codes (1.8+ million codes), and radiology reports (6+ million tokens) for training. We comprehensively evaluate Merlin on 6 task types and 752 individual tasks. The non-adapted (off-the-shelf) tasks include zero-shot findings classification (31 findings), phenotype classification (692 phenotypes), and zero-shot cross-modal retrieval (image to findings and image to impressions), while model adapted tasks include 5-year chronic disease prediction (6 diseases), radiology report generation, and 3D semantic segmentation (20 organs). We perform internal validation on a test set of 5,137 CTs, and external validation on 7,000 clinical CTs and on two public CT datasets (VerSe, TotalSegmentator). Beyond these clinically-relevant evaluations, we assess the efficacy of various network architectures and training strategies to depict that Merlin has favorable performance to existing task-specific baselines. We derive data scaling laws to empirically assess training data needs for requisite downstream task performance. Furthermore, unlike conventional VLMs that require hundreds of GPUs for training, we perform all training on a single GPU. This computationally efficient design can help democratize foundation model training, especially for health systems with compute constraints. We plan to release our trained models, code, and dataset, pending manual removal of all protected health information.

The Impact of Non-Adherence to Antihypertensive Drug Therapy.

Medication non-adherence is a major healthcare barrier, especially among diseases that are largely asymptomatic, such as hypertension. The impact of poor medication adherence ranges from patient-specific adverse health outcomes to broader strains on health care system resources. The Centers for Disease Control (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database was used to retrieve Centers for Medicare and Medicaid Services' data pertaining to blood pressure (BP) medication adherence, socio-economic variables, and cardiovascular (CV) outcomes across the United States. Multivariable linear regression models were used to estimate the change in total CV deaths as a function of non-adherence to BP medications. For every percent increase in the non-adherence rate, the total number of CV deaths increased by 7.13 deaths per 100,000 adults (95% CI: 6.34-7.92), even after controlling for the percentage of residents with access to insurance, the percentage of residents who were eligible for Medicaid, the percentage of residents without a college education, median home value, income inequality, and the poverty rate (p < 0.001). There is a significant association between non-adherence to BP medications and total CV deaths. Even a one percent increase in the adherence rate in the United States could result in tens of thousands of preventable CV deaths. Based on recently published CDC data, this could also have a tremendous impact on health care costs. This provides compelling evidence for increased efforts to improve adherence.

Diagnosis of cardiac sarcoidosis in patients presenting with cardiac arrest or life-threatening arrhythmias.

OBJECTIVE: Cardiac sarcoidosis (CS) may present with cardiac arrest or life-threatening arrhythmias. There are limited data on this subgroup of patients with CS. Advanced imaging including cardiovascular magnetic resonance (CMR) and cardiac 18-fluorodeoxyglucose (FDG) positron emission tomography (PET) are used for diagnosis. This study aimed to describe advanced imaging patterns suggestive of CS among patients presenting with cardiac arrest or life-threatening arrhythmias. METHODS: An imaging database of a CS referral centre (Royal Brompton Hospital, London) was screened for patients presenting with cardiac arrest or life-threatening arrhythmias and having imaging features of suspected CS. Patients diagnosed with definite or probable/possible CS were included. RESULTS: Study population included 60 patients (median age 49 years) with male predominance (76.7%). The left ventricle was usually non-dilated with mildly reduced ejection fraction (53.4±14.8%). CMR studies showed extensive late gadolinium enhancement (LGE) with 5 (4-8) myocardial segments per patient affected; the right ventricular (RV) side of the septum (28/45) and basal anteroseptum (28/45) were most frequently involved. Myocardial inflammation by FDG-PET was detected in 45 out of 58 patients vs 11 out of 33 patients with oedema imaging available on CMR. When PET was treated as reference to detect myocardial inflammation, CMR oedema imaging was 33.3% sensitive and 77% specific. CONCLUSIONS: In patients with CS presenting with cardiac arrest or life-threatening arrhythmias, LGE was located in areas where the cardiac conduction system travels (basal anteroseptal wall and RV side of the septum). While CMR was the imaging technique that raised possibility of cardiac scarring, oedema imaging had low sensitivity to detect myocardial inflammation compared with FDG-PET.

Evaluating Dental Fear and Anxiety in Pediatric Patients Visiting a Private and a Public Dental Hospital in Lahore, Pakistan.

Background One of the biggest hurdles in treating pediatric patients is managing dental fear and anxiety. Some factors that contribute to an increase in dental anxiety are fear of pain, the presence of unknown individuals, a change in the setting of an environment, and separation from parents. Aim The aim of this study was to evaluate dental fear and anxiety in pediatric patients, between the ages of 6 and 12 years, visiting private and public dental hospitals using the Children's Fear Survey Schedule-Dental Subscale (CFSS-DS). Methods A total of 280 children, 140 in a private dental hospital setting and 140 in a public dental hospital setting, were enrolled in this study. The purpose of the study was explained to the accompanying guardian of the patient and written consent was taken. The CFSS-DS was explained verbally in Urdu and the questionnaire was given to guardians alongside the patients which they were asked to fill out following their dental treatment. Result The data obtained from the questionnaires were analyzed using the unpaired t-test. The highest dental fear mean scores and standard deviation in a private dental hospital were for "choking" (3.25 ± 1.21), "the noise of the dentist drilling" (3.24 ± 1.04), and "having somebody put instruments in your mouth" (3.19 ± 1.06), whereas, for a public dental hospital, the highest fear score was recorded in "choking" (3.17 ± 1.69), "injections" (3.07 ± 1.72), and "people in white uniforms" (1.90 ± 1.21). Conclusion The study showed a higher prevalence of dental fear and anxiety in a private dental setting when compared to a public dental setting. Factors responsible for an increase in dental fear need to be assessed for each patient and then treatment given accordingly.

Biological and Hypoglycemic Effects of a Polyherbal Extract on Alloxanized Diabetic Rats.

The current study investigates the antioxidant, antidiabetic, hepatoprotective, and nephroprotective potentials of a polyherbal mixture containing the methanolic extracts of seeds from Nigella sativa, Cicer arietinum, Silybum marianum, and Citrullus colocynthis and the rhizome of Zingiber officinale. The polyherbal extract (PHE) showed significant total phenolic contents (187.17 GAE/g), ferric reducing power (28%), and radical-scavenging activity (86.16%). The PHE also showed a substantial hypoglycemic effect in alloxan-induced diabetic rats by reducing the blood glucose level of the PHE-treated rats (-48.64%) and increasing the insulin level (107.5%) as compared with the diabetic control group. Likewise, an increase in high-density lipoprotein (HDL) contents (22.95%) with an associated decrease in low-density lipoprotein (LDL) levels (-43.93%) was also noted. A significant decrease in serum levels of liver marker enzymes, e.g., SGPT (-36%), SGOT (-31%), and serum ALP (-12%), was also observed as compared with the standard drug-treated group. Based on the findings of the study, it may be suggested that PHE helps ameliorate the severity of diabetes as a herbal remedy and might be employed in nutra-pharmaceuticals, replacing synthetic antidiabetic compounds.

Incidence and prevalence of venous thromboembolism in chronic liver disease: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Historically, bleeding was thought to be a frequent and fatal complication of liver disease. However, thrombosis due to coagulation disorders in cirrhosis remains a real risk. We aim to systematically analyse published articles to evaluate epidemiology of venous thromboembolism (VTE) in chronic liver disease (CLD). METHOD: Electronic search was conducted on Ovid Medline, EMBASE and Scopus from inception to November 2021 to identify studies presenting epidemiology VTE (deep vein thrombosis and pulmonary embolism) in CLD in inpatients and/or community settings. Random-effects meta-analysis was performed to determine pooled per-year cumulative incidence, incidence rate and prevalence. Heterogeneity was measured by I2 test, and, potential sources of heterogeneity by meta-regression and sensitivity analysis. PROSPERO registration-CRD42021239117. RESULTS: Twenty-nine studies comprising 19,157,018 participants were included, of which 15,2049 (0.79%) had VTE. None of the included studies were done in the community. In hospitalised patients with CLD: pooled cumulative incidence of VTE was 1.07% (95% CI 0.80,1.38) per-year, incidence rate was 157.15 (95% CI 14.74,445.29) per 10,000 person-years, and period prevalence was 1.10% (95% CI 0.85,1.38) per year. There was significant heterogeneity and publication bias. Pooled relative risk (RR) of studies reporting incidence rate was 2.11 (95% CI 1.35,3.31). CLD patients (n = 1644), who did not receive pharmacological prophylaxis were at 2.78 times (95% CI 1.11, 6.98) increased risk of VTE compared to those receiving prophylaxis. CONCLUSION: Hospitalised patients with CLD may be at an increased risk of VTE. For every 1000 hospitalised patients with CLD ten have new, and eleven have pre-existing diagnoses of VTE per-year.

Soil applied potassium improves productivity and fiber quality of cotton cultivars grown on potassium deficient soils.

Cotton (Gossypium hirsutum L.) is considered as the most valuable cash crop of Pakistan. During last decade, its yield has been declined due to various biotic and abiotic factors. Among abiotic factors, improper use of fertilizers is considered very important specially regarding plant defense and yield. This study was conducted to evaluate the effect of different levels (0, 40, 80 and 120 kg ha-1) of K fertilizer (K2O) on different growth parameters of two commercial Bt cotton cultivars (CYTO-301 and IUB-2013) and one non-Bt cultivar (CYTO-142) during 2016 and 2017. Maximum plant height (124-134 cm), dry matter contents (915-1005%), fruiting point (441-462), bolls per plant (96-139), average boll weight (4.2-5.2 g) and seed cotton yield (2524-3175 kg ha-1) and minimum shedding (43-73%) were observed in plots receiving highest dose of K (120 kg ha-1). The CYTO-103 cultivar was found more responsive to K fertilizer as compared to rest of cultivars (CYTO-142 and IUB-2013). Concluding, ideal dose of fertilizer is very important (120 kg ha-1 in our case) for optimum growth and production of good quality fiber with enhanced seed cotton yield.

Thrombosis with Thrombocytopenia Syndrome After Administration of AZD1222 or Ad26.COV2.S Vaccine for COVID-19: A Systematic Review.

BACKGROUND: Cases of thrombosis with thrombocytopenia syndrome (TTS) have been reported following vaccination with AZD1222 or Ad26.COV2.S. This review aimed to explore the pathophysiology, epidemiology, diagnosis, management, and prognosis of TTS. METHODS: A systematic review was conducted to identify evidence on TTS till 4th September 2021. Case reports and series reporting patient-level data were included. Descriptive statistics were reported and compared across patients with different sexes, age groups, vaccines, types of thrombosis, and outcomes. FINDINGS: Sixty-two studies reporting 160 cases were included from 16 countries. Patients were predominantly females with a median age of 42.50 (22) years. AZD1222 was administered to 140 patients (87·5%). TTS onset occurred in a median of 9 (4) days after vaccination. Venous thrombosis was most common (61.0%). Most patients developed cerebral venous sinus thrombosis (CVST; 66.3%). CVST was significantly more common in female vs male patients (p = 0·001) and in patients aged <45 years vs ≥45 years (p = 0·004). The mortality rate was 36.2%, and patients with suspected TTS, venous thrombosis, CVST, pulmonary embolism, or intraneural complications, patients not managed with non-heparin anticoagulants or IVIG, patients receiving platelet transfusions, and patients requiring intensive care unit admission, mechanical ventilation, or inpatient neurosurgery were more likely to expire than recover. INTERPRETATION: These findings help to understand the pathophysiology of TTS while also recommending diagnostic and management approaches to improve prognosis in patients. FUNDING: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Incidence, pattern and severity of abnormal liver blood tests among hospitalised patients with SARS-COV2 (COVID-19) in South Wales.

INTRODUCTION: SARS-CoV-2 (COVID-19) is a novel coronavirus that emerged in Wuhan, China in late 2019 and since become a global pandemic. As such, its clinical behaviour is a subject of much interest. Initial reports suggested a significant proportion of patients have abnormal liver blood tests. Gwent has experienced one of the highest incidences of COVID-19 infection in the UK, which itself has among the highest COVID-19 impacts worldwide. METHOD: We set out to report the incidence, clinical pattern and severity of liver blood test abnormalities in hospitalised patients with confirmed COVID-19 in our institution over a 3-week period. Data on clinical outcomes such as admission to intensive therapy unit (ITU), hospital discharge and mortality were recorded. RESULTS: 318 hospitalised COVID-19 positive had liver blood tests available for analysis. Ninety-seven patients (31%) had one or more abnormal liver blood tests and were abnormal admission in 64%. Liver tests were predominantly cholestatic (72%) in contrast to other studies to date. Male gender and abnormal liver blood tests were associated with ITU admission. CONCLUSIONS: Almost one-third of admissions with COVID-19 have abnormal LBTs which are typically mild and are associated with male gender. Importantly, we have identified that cholestatic patterns dominate but were not clearly associated with ITU admission or death.

GP-GAN: Brain tumor growth prediction using stacked 3D generative adversarial networks from longitudinal MR Images.

Brain tumors are one of the major common causes of cancer-related death, worldwide. Growth prediction of these tumors, particularly gliomas which are the most dominant type, can be quite useful to improve treatment planning, quantify tumor aggressiveness, and estimate patients' survival time towards precision medicine. Studying tumor growth prediction basically requires multiple time points of single or multimodal medical images of the same patient. Recent models are based on complex mathematical formulations that basically rely on a system of partial differential equations, e.g. reaction diffusion model, to capture the diffusion and proliferation of tumor cells in the surrounding tissue. However, these models usually have small number of parameters that are insufficient to capture different patterns and other characteristics of the tumors. In addition, such models consider tumor growth independently for each subject, not being able to get benefit from possible common growth patterns existed in the whole population under study. In this paper, we propose a novel data-driven method via stacked 3D generative adversarial networks (GANs), named GP-GAN, for growth prediction of glioma. Specifically, we use stacked conditional GANs with a novel objective function that includes both l1 and Dice losses. Moreover, we use segmented feature maps to guide the generator for better generated images. Our generator is designed based on a modified 3D U-Net architecture with skip connections to combine hierarchical features and thus have a better generated image. The proposed method is trained and tested on 18 subjects with 3 time points (9 subjects from collaborative hospital and 9 subjects from BRATS 2014 dataset). Results show that our proposed GP-GAN outperforms state-of-the-art methods for glioma growth prediction and attain average Jaccard index and Dice coefficient of 78.97% and 88.26%, respectively.