Outcomes of Dynamic Condylar Screw Fixation in Subtrochanteric Femoral Fractures

Aim: To determine the union rate in subtrochanteric femoral fractures fixed with dynamic condylar screw system. Study Design: Descriptive study Place and duration of study: This study was conducted in the Department of Orthopaedic Surgery, Shaikh Zayed Hospital, Lahore from June 2019 to December 2021. Methodology: This study included 100 patients with subtrochanteric femoral fractures. Sampling was done with the consecutive sampling technique. Male and female patients were included in this study. The A.O classification was used to classify all the fractures. After 8 weeks, the fracture union was evaluated, and the results (in terms of yes/no) were documented on a pre-designed proforma. Results: This study included 100 patients with subtrochanteric femoral fractures. The patients' average age was 39.56±15.125 years, and the average duration of fracture was 4.10±1.973 days. There were fifty nine female patients (59%), and forty one male patients (41%). Type A fractures were reported in 19(19%) patients, type B in 48 (48%) patients, and type C in 33 (33%). Fracture union was reported in 79 (79%) of the 100 cases. Dynamic condylar screw is regarded as a very good implant for subtrochanteric fractures due to numerous advantages such as ease of availability, stable fixation, increased strength, resistance to stress failure and reduced surgical time. However, the union rate in our local population was not known prior to our research. Therefore, the purpose of this study is to find the union rates in subtrochanteric femoral fractures fixed with dynamic condylar screw. Conclusion: The results of this study revealed an increased union rate in patients with subtrochanteric femoral fractures fixed with DCS (dynamic condylar screw system). There was a significant relationship between patient age, fracture duration, and fracture type. Keywords: Subtrochanteric Femoral Fractures, Internal Fixation, Dynamic Condylar Screw.</jats:p

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

AbstractBackgroundWe describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients.MethodsThe data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV).ResultsData were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%.ConclusionsAge was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death.</jats:sec

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60&nbsp;years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death.&nbsp;The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use

The value of open-source clinical science in pandemic response: lessons from ISARIC

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