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Background: Commonly used prognostic scores for acute on-chronic liver failure (ACLF) have complex calculations. We tried to compare the simple counting of numbers and types of organ dysfunction to these scores, to predict mortality in ACLF patients. Methods: In this prospective cohort study, ACLF patients diagnosed on the basis of Asia Pacific Association for Study of the Liver (APASL) definition were included. Severity scores were calculated. Prognostic factors for outcome were analysed. A new score, the Number of Organ Dysfunctions in Acute-on-Chronic Liver Failure (NOD-ACLF) score was developed. Results: Among 80 ACLF patients, 74 (92.5%) were male, and 6 were female (7.5%). The mean age was 41.0±10.7 (18-70) years. Profile of acute insult was; alcohol 48 (60%), sepsis 30 (37.5%), variceal bleeding 22 (27.5%), viral 8 (10%), and drug-induced 3 (3.8%). Profiles of chronic insults were alcohol 61 (76.3%), viral 20 (25%), autoimmune 3 (3.8%), and non-alcoholic steatohepatitis 2 (2.5%). Thirty-eight (47.5%) were discharged, and 42 (52.5%) expired. The mean number of organ dysfunction (NOD-ACLF score) was ->4.5, simple organ failure count (SOFC) score was >2.5, APASL ACLF Research Consortium score was >11.5, Model for End-Stage Liver Disease-Lactate (MELD-LA) score was >21.5, and presence of cardiovascular and respiratory dysfunctions were significantly associated with mortality. NOD-ACLF and SOFC scores had the highest area under the receiver operating characteristic to predict mortality among all these. Conclusion: The NOD-ACLF score is easy to calculate bedside and is a good predictor of mortality in ACLF patients performing similar or better to other scores.
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Background: Diagnostic and therapeutic algorithms given by various societies for hepatitis B are fragmented and complex. The clinico-epidemiologic spectrum of hepatitis B is not studied with large-scale data from our region. We aimed to develop a comprehensive algorithm for the treatment of hepatitis B and study its clinico-epidemiological spectrum. Methods: From 2014-2019, the clinico-laboratory data of hepatitis B surface antigen (HbsAg)-positive patients were prospectively recorded. King George's Medical University hepatitis B therapeutic algorithm (KGHeBTA) was developed on the basis of the standard existing guidelines. The prevalence of different clinical stages of HBsAg-positive patients was calculated and their treatment records reviewed. Testing circumstances and risk factors were noted. Results: Among 1,508 data record sheets, 421 were complete. According to the KGHeBTA algorithm, 221 had detectable hepatitis B virus DNA. 21% were cirrhotic and 79% non-cirrhotic. 72% were incidentally detected asymptomatic hepatitis B, 7% were hepatitis B with acute symptoms, 0.7% were acute hepatitis B, and 22% were chronic hepatitis B. 20% patients were eligible for antivirals and 80% patients were not eligible. 32% patients were actually treated with antivirals due to the inclusion of some special indications as pregnancy and family history. Screening during various medical illnesses (40%) was the most common and during health camps (0.2%), the least common testing approach. Road-side shaving (52%) was the most common and intravenous drug abuse (0.2%) and the least common risk factor for the detection of hepatitis B in our data pool. Conclusions: HBsAg-positive patients can be easily worked up and treated based on the proposed algorithm (KGHeBTA). About one fourth to one fifth of all HBsAg-positive patients were eligible and treated with oral antivirals. Most of the patients were incidentally detected asymptomatic hepatitis B screened during medical illnesses. Roadside shaving and intravenous drug abuse were the most and the least common risk factors.
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BACKGROUND: Coronavirus disease 2019 (COVID-19) is a novel infectious disease caused by SARS CoV-2 that emerged in Wuhan, China, and has rapidly spread worldwide. The mortality rate of critically ill COVID-19 patients is high. OBJECTIVE: To assess the severity, different clinical symptoms, and comorbidities of COVID-19 pneumonia in vaccinated vs. non-vaccinated patients. METHODS: In this single-center, cross-sectional study, 142 patients with COVID-19 were enrolled. The clinical characteristics, comorbidities, severity, and outcomes were also assessed. RESULTS: Of the 142 patients, 92 (64.8%) were males, with a mean age of (56.00±14.81) years. Among them, 62 (43.7%) were aged above 60 years. Of these, 92 (64.7%) had comorbidities. The patients were divided into two groups: unvaccinated and those who received at least one dose of the vaccine within six months. The demographic characteristics of the two groups were similar except for gender. In the vaccinated group, most of the patients were males. Most patients in the non-vaccinated group had a severe illness, whereas most patients in the vaccinated group had mild to moderate disease. Only 26% of the vaccinated group experienced severe illness compared to 71.5% in the unvaccinated group. In addition, the all-cause 30-day mortality in the non-vaccinated population was higher than that in the vaccinated population. However, this difference was not statistically significant (12.5% vs. 7.1%). On the contrary, there was no difference in the length of the intensive care unit or total hospital stay between the two groups. CONCLUSION: Severe COVID-19 had the worst outcome in the unvaccinated patients. Most partially vaccinated patients got infected before developing immunity, and a small percentage of completely immunized patients who were infected were likely non-responders. Receiving at least one vaccination dose significantly reduced illness severity.
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Introduction: Government runs teaching hospitals to impart a high-quality medical education to budding medicos and paramedical students in training. The experiences these trainees at various tenure positions get then and there shape their worldview for rest of the life and have an indelible impression. The Covid-19 pandemic disrupted all the routines at the hospitals around the world-including ours-and we make an attempt to measure it in one dimension in this study. Materials and Methods: We obtained attendance data of patients at out patient department and in patient department of our hospital. During the pandemic for a certain duration offline (physical) registrations were closed and they were attended only by online ones. Hence that data (actually a part of it) got captured electronically and we analyzed it to get an idea of the traversed course of the scourge. Results: When the pandemic surged during the spring and summer of 2021, our hospital was turned into a Covid facility. Hence average routine attendance of patients got reduced to a significant extent, elective surgeries/interventions and procedures were postponed and this data is reflected in an electronic system, perhaps making a long-lasting effect on the budding trainees. This fact needs to be realized so as to take appropriate action. Conclusion: We need to realize that the effects of the viral communicable disease may be enduring, not only for the infected patients and their families but also for those who learn on those patients. Therefore, the transmissible diseases disabled not only our society, economy, and health care services when they ascended but pedagogy too. Online learning came to rescue but only up to a certain extent and with several caveats and limitations.
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Introduction: Covid-19 is an unprecedented challenge in our times leaving a trail of destruction and mayhem affecting almost all of us during the last 2 years. Various data sources are available around the globe to measure its impact using various yardsticks. Material and Methods: By carefully looking at data available at the website maintained by Government of India, we can draw some useful conclusions. Results: There is a dip in the number of online registrations at our hospital coinciding with second wave and resultant lockdown. Conclusion: Tracing digital footprints of an event as huge as the Covid pandemic may help us for future planning when we learn its lessons well.