Functional outcomes of Total Hip Replacement using modified Harris Hip Score

Background: Total hip replacement (THR) is a common surgery for relieving pain and improving the quality of life in patients with moderate to severe hip arthritis. The primary reason for THR is severe hip osteoarthritis, when conservative measures fail to relieve pain. The objective of the study was to examine functional outcomes, indications, and complications of THR using mHHS at different stages. Methods: A prospective observational study was carried out at the Department of Orthopedics, National Trauma Center, NAMS, from September 2019 to December 2020. The study included first 35 hips of 35 patients who underwent Total Hip Replacement at our hospital and met the inclusion criteria. Follow-up assessments were conducted at 6 weeks, 3 months, and 6 months after the surgery. Each visit involved thorough clinical and radiological examinations, as well as documentation of the mHHS chart. All continuous variables were expressed as mean ± standard deviation and two sample t test was used to compare means of two sub groups. Results: The study enrolled participants aged 26 to 66, with 60% male and 40% female. Right sided involvement was observed in 55% of cases, while the left side was affected in 45%. The most common reason for surgery was osteoarthritis caused by avascular necrosis of the femoral head. The average preoperative mHHS was 28, which increased to 64 at six weeks, 86 at three months, and 92 at six months. The study found that 80% of participants achieved excellent results. Complications, including a 2.85% dislocation rate, were reported. Conclusion: THR is a safe and effective procedure, providing excellent functional outcomes and minimal complications when performed carefully and precisely. Long-term studies are needed to investigate late complications and further establish the efficacy of the implants and the procedure

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Non-Menstrual Toxic Shock Syndrome Following Breast Abscess: A Rare Case Report From Nepal

Toxic Shock Syndrome is an acute illness caused by exotoxin producing Staphylococcus or Group A Streptococcus. TSS was traditionally associated with high absorbency tampon use in menstruating women until eventually, these were taken off the market. Since then, non-menstrual causes including wound infections, abscess, mastitis, burns, osteomyelitis, retained foreign bodies, etc are leading causes of TSS. TSS is characterized by fever, headache, myalgia, abdominal pain, hypotension, non-blanchable erythematous rash progressing to multi-organ damage. The mainstay of treatment includes removal of the source of infection, adequate volume resuscitation, vasopressors, and antibiotic coverage. Despite adequate treatment, the case fatality rate of Streptococcal TSS is 50% and Staphylococcal TSS is 3%. Here we present a unique case of 24-year-old women who presented with fever, headache, abdominal pain, and hypotension 6 days after self-drainage and self-medication of breast abscess. She was diagnosed with TSS secondary to breast abscess and admitted to the Intensive Care Unit (ICU), resuscitated and successfully treated with antibiotics.</jats:p

Antibiotic Resistance Pattern in Pediatric Deep Neck Space Infection

Abstract Introduction Neck space infection in the pediatric age group is common but can be life-threatening if not diagnosed properly. Since it is a polymicrobial disease, antibiotic usage should be guided by culture sensitivity pattern. Objectives To assess the microbiology, antibiotic resistance pattern and the outcome of the medical and surgical management of deep neck space infection in children. Methods This was a prospective study of children admitted for management of neck space infection from August 2017 to August 2018. The age, gender, organisms isolated, sensitivity and resistance to antibiotics, length of hospital stay, complications, and recurrence were noted. The descriptive data were analyzed. Results Out of 108 cases, there were 51 males (47.2%) and 57 females (52.8%) ranging from 1 month to 15 years, with a mean age of 5.32 +/− 4.35 years. The mean period of hospitalization was 6.98 days. Staphylococcus aureus was the most common organism isolated with less coagulase-negative staphylococci and streptococci. Clindamycin was the most sensitive drug (82.35%) followed by vancomycin and cloxcillin, while amoxicillin/ampicillin, a commonly used drug, was the least sensitive (20.58%). The abscess recurrence rate was 9.28%. The outcomes of either medical treatment or a combined medical or surgical treatment in properly selected cases were comparable. Conclusion Clindamycin or cloxacillin can be used as a first-line option for neck infection in children. Ampicillin/amoxicillin alone has a small role in neck abscess because of high resistance to this type of antibiotic.</jats:p

A Comparative Study on Three Different Combinations of Ketofol for Induction of General Anaesthesia

BACKGROUND Ketamine and propofol are one of the commonly used drugs for induction of general anaesthesia. Ketofol, is the combination of ketamine and propofol in varying concentrations. Due to the paucity of information in the literature regarding comparison of different combinations of ketofol for use as an induction agent, we intend to study the various doses of propofol ketamine combination in view of its haemodynamic stability and its relevance to speed of induction as well as side effect profile. METHODS This is a double blinded randomised controlled trial study. 60 patients posted for elective surgery under general anaesthesia were selected. They were randomly allotted to three groups with 20 patients in each group. Group 1 received ketofol in the ratio of 1:1, group 2 in the ratio of 1:2, group 3 in the ratio of 1:3. The time from the start of injection till the loss of verbal command, induction time, was noted. Mean arterial pressure, incidence of apnoea, awareness, hallucinations and post-operative nausea and vomiting (PONV) were noted. RESULTS Induction time was fastest in group 3 followed by group 2 followed by group 1. It was statistically significant. Mean arterial pressure (MAP) was comparable in all the three groups at different time intervals except at 5 minutes after induction, the fall in group 3 was significant. The change in MAP as compared to baseline in group 1 and 2 in different time intervals was not significant. But the fall in MAP was significant as compared to baseline in all the different time intervals in group 3. There was no reported incidence of apnoea, awareness and hallucinations in all the three groups. There were two reported cases of PONV in group 1, one in group 2 and zero in group 3. CONCLUSIONS Ketofol with the maximum propofol and least ketamine combination has the fastest induction time. Ketofol in the combination of 1:1 and 1:2 offers more haemodynamic stability as compared to 1:3 combination and ketofol has minimal side effects. KEY WORDS Ketofol, Different Combinations, Induction Time, Haemodynamic Stability</jats:p

Carcinosarcoma of the Cervix: A Case Report

Cervical carcinoma is the most common cause of mortality due to cancer in Nepal. Carcinosarcoma is a very rare subtype of cervical cancer which is characterized by the presence of both epithelial and mesenchymal malignant component. It constitutes less than 1% of cervical carcinoma. Due to the low occurrence of the disease, most of the data on treatment and prognosis are based on case reports and series. Here, we report a case of 69 years, female with cervical cancer (FIGO IIA2). Histopathological and immunohistochemical analysis of cervical biopsy initially showed primary adenosarcoma of the cervix. The tumor was non-responsive to primary treatment with concurrent chemoradiation. Later she was treated with abdominal hysterectomy and bilateral salpingo-oophorectomy. The final histopathology of the resected specimen showed a sarcomatous component along with carcinomatous changes in the endocervical glands favouring the diagnosis of carcinosarcoma of the cervix