COVID-19 and pregnancy- review of cases from a tertiary public hospital in Mumbai

Background: In December 2019 a novel strain of coronavirus, was first isolated by the Chinese Center for Disease Control and Prevention. This strain connected to the cluster of acute respiratory illness cases from Wuhan, China was later officially named as severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). On 30th January 2020, WHO declared the outbreak of SARS-Cov-2 a public health emergency of international concern, and on 11th March 2020 declared it to be a pandemic. Pregnant women are known to be at higher risk of severe morbidity and mortality from respiratory infections such as influenza and SARS, making a strong case for pregnant women to be considered an at-risk population for COVID-19. This study aimed to assess the clinical picture, obstetric outcome and neonatal outcome in COVID positive pregnant cases.Methods: We did a retrospective observational cohort study in the department of Obstetrics and Gynecology at a tertiary teaching hospital in Mumbai.Results: In the study duration, 148 were diagnosed as COVID positive (~12%). 9 patients had COVID related symptoms on admission. The obstetric outcome in symptomatic patients was noted to be good. We noted 79.01% of the pregnancies reached term. Cesarean section rate in COVID positive patients was comparable to non-COVID patients in the study duration. Neonatal outcome was only 4 babies of COVID positive mothers were diagnosed positive.Conclusions: Our study shows pregnancy outcomes are not significantly worsened by the COVID-19 infection in spite of the risk factors associated with pregnancy per se and influenza infection in pregnancy

Fistulotomy versus fistulectomy for simple fistula in ano: a retrospective cohort study

OBJECTIVE: To compare fistulotomy with fistulectomy for wound healing, duration of surgery, post-operative pain, incontinence and recurrence in patients with fistula in ano. METHODS: This retrospective cohort study was conducted at the Aga Khan University Hospital, Karachi, and comprised data of adults who had undergone fistulotomy/fistulectomy for simple fistula in ano from January 2007 to August 2012. Data collection was done in August 2013 using questionnaire and telephonic interviews. Outcome variables like duration of wound healing, recurrence, incontinence, duration of surgery and post-operative pain were compared in both the groups. SPSS 19 was used for data analysis. RESULTS: Of the 192 cases, there were 96(50%) in each group. The mean age was 40.51 years (range: 21-72 years) in the fistulotomy group and 41.14 years (range: 21-66 years) in the fistulectomy group (p=0.66). Both groups were comparable for baseline demographic variables. The median duration of wound healing was shorter in the fistulotomy group 15 days (Interquartile range: 7-20 days) compared to the fistulectomy group 30 days (Interquartile range: 15-42 days) (p\u3c0.001). The incidence of recurrence was comparable in fistulotomy vs. fistulectomy (3[3.12%] vs. 4[4.16%]; p=0.70). The incidence of incontinence was higher in fistulotomy compared to fistulectomy (5[5.3%] vs. 12[12.5%]; p=0.07). The severity of incontinence was also compared but the difference was insignificant (p=0.06). The median duration of surgery was significantly shorter in fistulotomy group 17 minutes (Interquartile range: 12-25 minutes) compared to fistulectomy group 25 minutes Interquartile range: 20-35 minutes (p\u3c0.001). The median post-operative pain in the surgical day care unit and at the first follow-up in clinic was zero for both groups. CONCLUSIONS: Fistulotomy yielded better results than fistulectomy since it significantly decreased the duration of wound healing and duration of surgery without increasing the incidence of recurrence, incontinence and post-operative pain

Investigation of the Role of Machine Learning and Deep Learning in Improving Clinical Decision Making for Musculoskeletal Rehabilitation

Musculoskeletal rehabilitation is an important aspect of healthcare that involves the treatment and management of injuries and conditions affecting the muscles, bones, joints, and related tissues. Clinical decision-making in musculoskeletal rehabilitation involves complex and multifactorial considerations that can be challenging for healthcare professionals. Machine learning and deep learning techniques have the potential to enhance clinical judgement in musculoskeletal rehabilitation by providing insights into complex relationships between patient characteristics, treatment interventions, and outcomes. These techniques can help identify patterns and predict outcomes, allowing for personalized treatment plans and improved patient outcomes. In this investigation, we explore the various applications of machine learning and deep learning in musculoskeletal rehabilitation, including image analysis, predictive modelling, and decision support systems. We also examine the challenges and limitations associated with implementing these techniques in clinical practice and the ethical considerations surrounding their use. This investigation aims to highlight the potential benefits of using machine learning and deep learning in musculoskeletal rehabilitation and the need for further research to optimize their use in clinical practice

COVID-19 and pregnancy- review of cases from a tertiary public hospital in Mumbai

Background: In December 2019 a novel strain of coronavirus, was first isolated by the Chinese Center for Disease Control and Prevention. This strain connected to the cluster of acute respiratory illness cases from Wuhan, China was later officially named as severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). On 30th January 2020, WHO declared the outbreak of SARS-Cov-2 a public health emergency of international concern, and on 11th March 2020 declared it to be a pandemic. Pregnant women are known to be at higher risk of severe morbidity and mortality from respiratory infections such as influenza and SARS, making a strong case for pregnant women to be considered an at-risk population for COVID-19. This study aimed to assess the clinical picture, obstetric outcome and neonatal outcome in COVID positive pregnant cases.Methods: We did a retrospective observational cohort study in the department of Obstetrics and Gynecology at a tertiary teaching hospital in Mumbai.Results: In the study duration, 148 were diagnosed as COVID positive (~12%). 9 patients had COVID related symptoms on admission. The obstetric outcome in symptomatic patients was noted to be good. We noted 79.01% of the pregnancies reached term. Cesarean section rate in COVID positive patients was comparable to non-COVID patients in the study duration. Neonatal outcome was only 4 babies of COVID positive mothers were diagnosed positive.Conclusions: Our study shows pregnancy outcomes are not significantly worsened by the COVID-19 infection in spite of the risk factors associated with pregnancy per se and influenza infection in pregnancy.</jats:p

Gender-based Genetic Variability of Ailanthus excelsa Roxb, Populations Using, RAPD, ISSR and SCoT Markers

Ailanthus excelsa Roxb. is an economically important and multipurpose dioecious tree species of India, mainly used for fodder and timber. Gender-based genetic diversity of five populations of two sites (Jodhpur, Rajasthan and Deesa, Gujarat) of A. excelsa was assessed. A total of 42 RAPD, 20 ISSR and 23 SCoT primers were screened for DNA amplification of 232 individuals. Out of which only 25 primers (13 RAPD, 6 ISSR and 6 SCoT) were found polymorphic. The SCoT markers were showed the highest value for PIC, MI, Rp value, Nei’s gene diversity and Shannon’s index, as compared with the other two markers. Female individuals in all five populations had slightly higher genetic diversity as compared with male individuals. A high level of genetic diversity (55%) was detected within the populations of male and female individuals. High gene flow (6.70) and low genetic differentiation (0.069) values were found between Jodhpur and Deesa sites. Principal component analysis for all populations were accounted for 48.7% of the genetic variation. The Mantel test showed significant correlation (R = 0.178, P = .01) between genetic and geographic distances. The present study showed that SCoT markers were best for genetic diversity assessment in A. excelsa over RAPD and ISSR markers. High gene flow and low genetic differentiation in A. excelsa indicates its poor population fragmentation despite long geographic distances.</jats:p

Screening of Multitarget Compounds against Acetaminophen Hepatic Toxicity Using In Silico, In Vitro, and In Vivo Approaches

Combination therapy and multitarget drugs have recently attracted much attention as promising tools to fight against many challenging diseases and, thus, represent a new research focus area. The aim of the current project was to screen multitarget compounds and to study their individual and combined effects on acetaminophen-induced liver injury. In this study, 2 of the best hepatoprotective multitargeting compounds were selected from a pool of 40 major compounds present in Curcuma longa and Cinnamomum zeylanicum by using molecular docking, ADMET profiling, and Pfizer&rsquo;s rule of five. The two selected compounds, quercetin and curcumin, showed a high binding affinity for the CYP2E1 enzyme, MAPK, and TLR4 receptors that contribute to liver injury. The candidates caused the decreased viability of cancer cell lines (HepG2 and Huh7) but showed no effect on a normal cell line (Vero). Examination of biochemical parameters (ALT, AST, ALP, and bilirubin) showed the hepatoprotective effect of the candidate drugs in comparison with the control group, which was confirmed by histological findings. Taken together, quercetin and curcumin not only satisfied the drug-like assessment criterion and proved to be multitargeting by preventing liver damage but also showed anticancer activities