The Biography of Muslim Ibn Abi Maryam and the Issue of Dreading from Elevating the Hadith

This research deals with the biography of Muslim Ibn Abi Maryam and the issue of dreading from elevating the hadith. His biography was presented including his name and lineage, the names of his teachers and pupils, and the scholars’ sayings, including the saying of Al-Imam Maliki.  It has been found from the study that all of his teachers are Medinans. What he narrated from the hadith is not proportional with the number of his teachers, as his hadith via them is supposed to be more than what we have found. It has been shown by the researchers that Muslim’s dreading from elevating the hadith led him to shorten the Isnad and not to elevate the Marfou’ hadith، which in its turn forced his students to narrate the  accounts that he elevated and leave the non-elevated ones. The research adopted the inductive method by collecting the sayings of scholars about Muslim Ibn Abi Maryam, collecting his narrations, and tracking what serves the title of the research, the analytical method by analyzing what was collected from the scientific material, and extracting the issues that serve the topic and clarify its aspects and the critical method by criticizing the hadiths narrated by Muslim Ibn Abi Maryam. The research found that the contradiction between elevating or not elevating the hadith in the practice of Ibn Maryam is not a kind of (i'llah) (a hidden deceit), as he practiced that in purpose, i.e. deliberately not accidentally or mistakenly

Characteristics and predictors of mortality of patients with hematologic malignancies requiring invasive mechanical ventilation

Rationale: Acute respiratory failure (ARF) may complicate the course of hematologic malignancies (HMs). Our objective was to study the characteristics, outcomes and predictors of mortality of patients with HMs who required intubation for ARF. Methods: This retrospective cohort study evaluated all patients with HMs who were admitted to the Intensive Care Unit (ICU) of King Abdul-Aziz Medical City-Riyadh between 2008 and 2013 and required invasive mechanical ventilation. We noted their baseline characteristics, treatments and different outcomes. Multivariable logistic regression analysis was performed to evaluate predictors of hospital mortality. Results: During the 6-year period, 190 patients with HMs were admitted to the ICU and 122 (64.2%) required intubation for ARF. These patients had mean age of 57.2 ± 19.3 years and Acute Physiology and Chronic Health Evaluation II score of 28.0 ± 7.8 and were predominantly males (63.4%). Lymphoma (44.3%) and acute leukemia (38.5%) were the most common hematologic malignancy. Noninvasive ventilation (NIV) was tried in 22 patients (18.0%) but failed. The code status was changed to “Do-Not-Resuscitate” for 39 patients (32.0%) during ICU stay. Hospital mortality was 70.5% and most deaths (81.4%) occurred in the ICU. The mortality of patients with “Do-Not-Resuscitate” status was 97.4%. On multivariable logistic regression analysis, male gender (odds ratio (OR), 6.74; 95% confidence interval (CI), 2.24–20.30), septic shock (OR, 6.61; 95% CI, 1.93–22.66) were independent mortality predictors. Remission status, non-NIV failure and chemotherapy during ICU stay were not associated with mortality. Conclusions: Patients with HMs requiring intubation had high mortality (70.5%). Male gender and presence of septic shock were independent predictors of mortality

Stigma and mental health among professionals.

info:eu-repo/semantics/nonPublishe

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 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. 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

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

International audienc

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