]. The informal caregivers’ psychological condition and quality of life can undergo many changes. Previous qualitative studies have suggested that the provision of care during the lockdown was even more challenging, as informal caregivers faced greater emotional strains due to increased care responsibilities.
patients admitted to this hospital were 200 . The participants were selected using convenience sampling. The main inclusion criterion was the patient’s dependency on care which was assessed by two questions about the patient’s ability to do his/her daily activities and his/her need for care. The informal caregivers of those patients who could do their daily activities were excluded from the study.
Bam is a city located in Kerman Province, southeastern Iran. There is a public hospital and a private hospital affiliated with Bam University of Medical Sciences. Since the thalassemia and hemodialysis departments are located only in the public hospital, so all the patients admitted to this hospital were included in this study based on census sampling. Therefore, we used no formula in the present study to estimate the sample size.
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Personalized hypertension treatment recommendations by a data-driven model - BMC Medical Informatics and Decision MakingBackground Hypertension is a prevalent cardiovascular disease with severe longer-term implications. Conventional management based on clinical guidelines does not facilitate personalized treatment that accounts for a richer set of patient characteristics. Methods Records from 1/1/2012 to 1/1/2020 at the Boston Medical Center were used, selecting patients with either a hypertension diagnosis or meeting diagnostic criteria (≥ 130 mmHg systolic or ≥ 90 mmHg diastolic, n = 42,752). Models were developed to recommend a class of antihypertensive medications for each patient based on their characteristics. Regression immunized against outliers was combined with a nearest neighbor approach to associate with each patient an affinity group of other patients. This group was then used to make predictions of future Systolic Blood Pressure (SBP) under each prescription type. For each patient, we leveraged these predictions to select the class of medication that minimized their future predicted SBP. Results The proposed model, built with a distributionally robust learning procedure, leads to a reduction of 14.28 mmHg in SBP, on average. This reduction is 70.30% larger than the reduction achieved by the standard-of-care and 7.08% better than the corresponding reduction achieved by the 2nd best model which uses ordinary least squares regression. All derived models outperform following the previous prescription or the current ground truth prescription in the record. We randomly sampled and manually reviewed 350 patient records; 87.71% of these model-generated prescription recommendations passed a sanity check by clinicians. Conclusion Our data-driven approach for personalized hypertension treatment yielded significant improvement compared to the standard-of-care. The model implied potential benefits of computationally deprescribing and can support situations with clinical equipoise.
Source: medical_xpress - 🏆 101. / 51 Read more »
Solving the U.S. Nursing Shortage Crisis Through ImmigrationFormer U.S. Secretaries of Health Alex Azar and Kathleen Sebelius argue that to address the nursing shortage crisis, we need to fix immigration
Source: TIME - 🏆 93. / 53 Read more »
Effect of the COVID-19 pandemic on obesity and it is risk factors: a systematic review - BMC Public HealthBackground Coronavirus disease (COVID-19) is a contagious disease caused by the severe acute new coronavirus called SARS-CoV-2. Devastating social, economic, and health service utilisation-related activities. Increased burden and lifestyle changes due to confinement. Objective This study aimed to investigate and determine the determinants of obesity during the coronavirus disease (COVID-19) pandemic from 2019 to 2023. Methods Observational studies published between December 2019 and January 2023 were thoroughly searched using a PRISMA flow chart. PubMed, Google Scholar, Web of Science, HINARI, Scopus, and Embase databases were used. Two reviewers independently identified and critically evaluated the relevant literature. Studies that reported weight gain or involved BMI measurements of 25 kg/m2 or BMI z-scores for children during the COVID-19 lockdown were selected for inclusion. The Newcastle–Ottawa Scale (NOS) was used as a quality assessment instrument in nonrandomised studies to evaluate study quality. All the contributing determinants of weight increase were identified, gathered, and synthesised. Results This systematic review identified 40 studies with a total population of 5,681,813 from 22 countries, of which 74.6% were male. The sample size from included articles ranged from 37 to 5,315,435. Of the 40 selected articles, 24 focused on adults, five on adolescents, three on children, and eight on children and adolescents. Physical inactivity, sedentary behaviour, bad eating habits, behavioural lifestyle, excessive stress, depression, anxiety, behavioural risk factors, sex, and ethnic minorities were associated with obesity during the COVID-19 pandemic lockdown. Conclusion During the COVID-19 pandemic, physical inactivity, sedentary lifestyle, and poor eating patterns were the most common risk factors for obesity. Additionally, unhealthy eating habits, excessive behavioural stress, depression, anxiety, low mood, age, gender, and ethnic minorities have been ident
Source: BioMedCentral - 🏆 22. / 71 Read more »