Physicians for Human Rights documents systematic abuse against ethnic Albanian physicians and patients (original) (raw)
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Trials, 2021
Background: Evidence exists as to the criticality of the first 24 h in the management of cerebral malaria. The morbidity and the mortality rate (35%) with the current intravenous monotherapy for the initial treatment of cerebral malaria are unacceptably high. Combination therapy and a shorter course of effective medication have been shown to improve outcomes in human participants in the treatment of other diseases. This study outlines a protocol to conduct a triple blinded parallel randomized controlled trial on cerebral malaria using dual intravenous medications compared to the current standard of monotherapy. Methods: This is a parallel multi-site randomized controlled superiority triple blinded trial consisting of intravenous artesunate plus quinine and a control arm of intravenous artesunate only. Eligible and assenting children aged 6 months to 17 years will be recruited from 4 tertiary hospitals by random selection from the list of tertiary hospitals in Nigeria. Participants will be randomized and assigned in parallel into two arms using random numbers generated from GraphPad Prism (version 9) by a clinical pharmacologist who has no link with the investigators, the patients, or the statistician. The primary measurable outcome is survival at 12, 24, and 48 h post-randomization. A composite secondary outcome consists of the number of children that regained consciousness, parasitaemia and defervescence at 12 and 24 h post-randomization and haematological and inflammatory markers at 24 and 48 h post-randomization. Adverse events both solicited and unsolicited are recorded all through the study postrandomization. The study is approved by the State Research Ethics Review Committee. Data analysis will be performed in GraphPad Prism version 9.
Prevention of Neonatal Hypoglycemia With Oral Glucose Gel for High-Risk Newborns
WMJ : official publication of the State Medical Society of Wisconsin, 2021
BACKGROUND Neonatal hypoglycemia (glucose <47) is the most common metabolic problem in newborns (incidence 5% - 15%) and can cause adverse outcomes, even in the absence of noticeable symptoms. Oral glucose gel (OGG) is safe and effective for treatment of neonatal hypoglycemia. In order to reduce interventions such as intravenous (IV) dextrose administration and neonatal intensive care unit (NICU) transfer, in October 2017, we implemented a protocol in our Level 1 rural community hospital to identify newborns with asymptomatic hypoglycemia based on risk factors and treat them with OGG. Risk factors include large or small size for gestational age, maternal gestational diabetes, preterm and late preterm birth, and newborns requiring resuscitation. METHODS Chart review was performed for all infants born at our hospital from October 1, 2016 through September 30, 2018. Data for year 1-the period before protocol implementation (October 2016- September 2017)-was compared to post implemen...
Infection and Drug Resistance
Background: Most patients admitted to intensive care units (ICUs) with severe Corona Virus Disease 2019 (COVID-19) pneumonia receive antibacterial antibiotics with little evidence of bacterial infections. Objective: This study was designed to review the profiles of patients with severe COVID-19 pneumonia requiring intensive care, the rate of bacterial coinfection, the antibiotics used, and their relation to patient outcomes (death or recovery). Methods: This was a retrospective study that reviewed the medical records of all patients with confirmed COVID-19 (n = 120) severe pneumonia admitted directly from the emergency room to the intensive care unit, at a public hospital during the period from May 2020 to April 2021. The data collected included patients' demographic and laboratory data, comorbidities, antibiotic treatment, and their outcome. Descriptive statistics, bivariate inferential analysis tests (chi-square and unpaired T-Tests) and multivariable binary logistic regression were performed. Results: The mean age of the patients was 56.8 ± 16.5 years old, and among them, 74 (62.7%) were males. Of the included patients, 92 (77.0%) had comorbidities, 76 (63.3%) required mechanical ventilation and 30 (25%) died. All patients received empirical antibiotics for suspected bacterial coinfection. The most common antibiotics used were azithromycin (n = 97, 8%) and imipenem (n = 83, 9%). Ninety patients (75%) were on two empirical antibiotics. Early positive cultures for pathogens were found only in four patients (3.3%), whereas 36 (30%) patients had positive cultures 5-10 days after admission. The most frequently isolated pathogens were Acinetobacter baumannii (n = 16) and coagulasenegative Staphylococci (n = 14). In bivariate analysis empirical treatment with azithromycin resulted in a significantly lower mortality rate (p = 0.023), meanwhile mechanical ventilation, days of stay in intensive care unit, morbidities (e.g., lung disease), linezolid and, vancomycin use associated with mortality (p< 0.05). The adjusted logistic regression, controlling for age and gender, revealed that azithromycin antibiotic was more likely protective from mortality (OR= 0.22, 95%CI 0.06-0.85, p=0.028. However, patients with lung diseases and under mechanical ventilation were 35.21 and 19.57 more likely to die (95%CI =2.84-436.70, p=0.006; 95%CI=2.66-143.85, p=0.003, respectively). Conclusion: Bacterial coinfection with severe COVID-19 pneumonia requiring intensive care was unlikely. The benefit of Azithromycin over other antibiotics could be attributed to its anti-inflammatory properties rather than its antibacterial effect.
SMART COVID Navigator: A Clinical Decision Support for COVID-19 (Preprint)
Journal of Medical Internet Research, 2021
Background: COVID-19 caused by SARS-CoV-2 has infected 219 million individuals at the time of writing of this paper. A large volume of research findings from observational studies about disease interactions with COVID-19 is being produced almost daily, making it difficult for physicians to keep track of the latest information on COVID-19's effect on patients with certain pre-existing conditions. Objective: In this paper, we describe the creation of a clinical decision support tool, the SMART COVID Navigator, a web application to assist clinicians in treating patients with COVID-19. Our application allows clinicians to access a patient's electronic health records and identify disease interactions from a large set of observational research studies that affect the severity and fatality due to COVID-19. Methods: The SMART COVID Navigator takes a 2-pronged approach to clinical decision support. The first part is a connection to electronic health record servers, allowing the application to access a patient's medical conditions. The second is accessing data sets with information from various observational studies to determine the latest research findings about COVID-19 outcomes for patients with certain medical conditions. By connecting these 2 data sources, users can see how a patient's medical history will affect their COVID-19 outcomes. Results: The SMART COVID Navigator aggregates patient health information from multiple Fast Healthcare Interoperability Resources-enabled electronic health record systems. This allows physicians to see a comprehensive view of patient health records. The application accesses 2 data sets of over 1100 research studies to provide information on the fatality and severity of COVID-19 for several pre-existing conditions. We also analyzed the results of the collected studies to determine which medical conditions result in an increased chance of severity and fatality of COVID-19 progression. We found that certain conditions result in a higher likelihood of severity and fatality probabilities. We also analyze various cancer tissues and find that the probabilities for fatality vary greatly depending on the tissue being examined.
Journal of Medical Internet Research, 2021
Background COVID-19 caused by SARS-CoV-2 has infected 219 million individuals at the time of writing of this paper. A large volume of research findings from observational studies about disease interactions with COVID-19 is being produced almost daily, making it difficult for physicians to keep track of the latest information on COVID-19’s effect on patients with certain pre-existing conditions. Objective In this paper, we describe the creation of a clinical decision support tool, the SMART COVID Navigator, a web application to assist clinicians in treating patients with COVID-19. Our application allows clinicians to access a patient’s electronic health records and identify disease interactions from a large set of observational research studies that affect the severity and fatality due to COVID-19. Methods The SMART COVID Navigator takes a 2-pronged approach to clinical decision support. The first part is a connection to electronic health record servers, allowing the application to a...
JMIR medical informatics, 2016
The use of health information technology (HIT) may improve medication adherence, but challenges for implementation remain. The aim of this paper is to review the current state of HIT as it relates to medication adherence programs, acknowledge the potential barriers in light of current legislation, and provide recommendations to improve ongoing medication adherence strategies through the use of HIT. We describe four potential HIT barriers that may impact interoperability and subsequent medication adherence. Legislation in the United States has incentivized the use of HIT to facilitate and enhance medication adherence. The Health Information Technology for Economic and Clinical Health (HITECH) was recently adopted and establishes federal standards for the so-called "meaningful use" of certified electronic health record (EHR) technology that can directly impact medication adherence. The four persistent HIT barriers to medication adherence include (1) underdevelopment of data ...
Developing and validating a primary care EMR-based frailty definition using machine learning
International Journal of Population Data Science
Introduction. Individuals who have been identified as frail have an increased state of vulnerability, often leading to adverse health events, increased health spending, and potentially detrimental outcomes. Objective. The objective of this work is to develop and validate a case definition for frailty that can be used in a primary care electronic medical record database. Methods. This is a cross-sectional validation study using data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) in Southern Alberta. 52 CPCSSN sentinels assessed a random sample of their own patients using the Rockwood Clinical Frailty scale, resulting in a total of 875 patients to be used as reference standard. Patients must be over the age of 65 and have had a clinic visit within the last 24 months. The case definition for frailty was developed using machine learning methods using CPCSSN records for the 875 patients. Results. Of the 875 patients, 155 (17.7%) were frail and 720 (84.2%) were not ...