Conectar
This study aimed to quantify how patient risk factors relate to COVID-19 severity across categories 1–5 in a prospective, hospital-based cohort. We hypothesised that greater severity would be associated with higher odds of intensive care unit (ICU) admission and in-hospital mortality. Secondary aims were to assess associations with age, viral variants, symptom clusters, lymphocyte count, fasting blood glucose and cytokine profiles.
Prospective cohort study.
A secondary-care/tertiary-care hospital and linked community settings in Cheras, Kuala Lumpur, Malaysia.
This study was nested within the COVGEN project, a prospective COVID-19 cohort conducted at Hospital Canselor Tuanku Muhriz UKM (HCTM), Cheras Health Clinic and the Bandar Tun Razak COVID-19 Assessment Centre in Cheras, Kuala Lumpur, Malaysia, from 1 August 2021 to 31 October 2022. 2532 participants were enrolled at baseline. Eligible participants were Malaysian citizens aged 12–18 years (paediatric/adolescent) or ≥18 years who had reverse transcription-polymerase chain reaction–confirmed COVID-19 at recruitment and resided in Kuala Lumpur or Selangor. Patients who had a clinically unstable condition and those who declined participation (personally or via a next-of-kin or legal representative) were excluded. This analysis included 559 patients hospitalised at HCTM; after excluding five with incomplete questionnaires, 554 remained for analysis (413 admitted to general wards and 141 to ICUs). Categories 3–5 comprised hospitalised patients, whereas categories 1–2 included hospitalised individuals and a subset recruited from community settings.
Primary outcomes included disease severity (categories 4–5 vs 1–3), ICU admission and in-hospital mortality. Secondary outcomes included associations with age strata, viral variant (delta vs omicron), symptom clusters, lymphocyte count, fasting blood glucose and cytokines: interferon gamma-inducible protein 10, interferon gamma, interleukins 8, 10, 2, 6 and 7 and tumour necrosis factor alpha.
141 of 554 (25.5%) patients required ICU care. Compared with milder categories, category 5 was associated with markedly higher odds of ICU admission (OR 204.50; 95% CI 37.54 to 1114.18; p55 versus
An increasing clinical severity category was strongly associated with ICU admission and mortality. Age, delta infection, specific symptom clusters, lymphopenia, hyperglycaemia and pro-inflammatory cytokines identified higher-risk patients, supporting risk-stratified management and prioritisation for enhanced monitoring.
by Faten Al-hussein, Laleh Tafakori, Mali Abdollahian, Khalid Al-Shali
Type 2 diabetes (T2D) is a chronic condition affecting millions globally. A robust predictive model to estimate the number of new cases of T2D can facilitate precise monitoring and effective intervention strategies. This study aims to predict the number of new T2D cases per month in Saudi Arabia and identify the Key Performance Indicators (KPIs) associated with T2D, using count regression models, Poisson Regression (PR), Negative Binomial Regression (NBR), Poisson Inverse Gaussian Regression (PIGR), and Bell Regression (BR). De-identified data from 1,000 patients with T2D in Saudi Arabia were used to develop the models. The performance of the full models, which include recommended Key Performance Indicators (KPIs), is compared using metrics such as the coefficient of determination (R2), root mean squared error (RMSE), mean absolute error (MAE), 10-fold cross-validation (CV-10), Akaike information criterion (AIC), and Bayesian information criterion (BIC). The most significant KPIs identified by the full models were utilized to develop the reduced models. The full NBR model outperformed other models, achieving R² of 0.88, RMSE of 0.93, MAE of 0.69, CV-10 of 1.21, AIC = 873.23, and BIC = 880. The reduced NBR model, focusing solely on the five most influential variables (marital status, age, body mass index (BMI), total cholesterol (TC), and high-density lipoprotein (HDL)), with R² = 0.84, RMSE = 1.10, MAE = 0.86, CV-10 = 1.37, AIC = 899, and BIC = 910, also outperformed other reduced models. The Likelihood Ratio Test (LRT) did not show a significant difference between the full and reduced NBR models (p = 0.694), supporting the adequacy of the reduced model. The proposed reduced model, utilizing only five significant KPIs, can help healthcare providers develop effective, targeted strategies by monitoring a smaller number of KPIs to reduce the rising number of T2D cases in Saudi Arabia.To identify healthcare professionals' experiences of innovation competence and the factors associated with it; and to examine the instruments developed to assess innovation competence and its associated factors among healthcare professionals.
A mixed-methods systematic review.
Researchers independently screened original studies by title and abstract (n = 2996) and then full text (n = 189). Eighteen studies were included: 16 quantitative and two qualitative. Qualitative data were analysed using inductive content analysis, and quantitative data were tabulated and synthesised narratively.
The review followed the Joanna Briggs Institute Mixed Methods Systematic Review methodology. Searches were conducted in Scopus, CINAHL, Ovid Medline, ProQuest, Web of Science, PsycArticles, and Medic. Articles published in English or Finnish with no date restrictions were included. The search covered records from database inception to August 2024.
From qualitative studies, we identified three categories describing experiences of innovation competence: Competences for Innovation in Healthcare, Application and Impact of Innovation in Healthcare, and Challenges and Strategies for Implementing Innovation. Quantitative studies identified three conceptual domains: Individual Capacities in Innovation, Innovation-related Competence Behaviours, and Social and Organisational Enablers. Four categories of factors associated with innovation competence emerged: sociodemographic, career-related, organisational, and academic factors.
Healthcare professionals' innovation competence is a multifaceted construct encompassing individual abilities, behavioural expressions, and social and organisational engagement. A systematic and multilevel approach that targets both personal attributes and organisational enablers is needed to strengthen competence. Enhancing innovation competence can improve the healthcare sector's ability to respond to complex challenges and sustain innovation capacity.
Findings inform the development of education programmes and leadership strategies to enhance innovation competence among healthcare professionals, supporting innovation implementation in healthcare organisations.
No patient or public involvement was included in this study.
PROSPERO: CRD42024614551
by Jakub Jamárik, Jiří Vitouš, Radovan Jiřík, Daniel Schwarz, Eva Koriťáková
Neuropsychiatric malignancies frequently manifest at the level of individual cortical layers. The resolutions currently available for medical magnetic resonance imaging (MRI) prevent the study of these pathologies at clinically available field strengths of 3 T. Previous studies have claimed to have overcome these issues by extensions of quantitative MRI. Following this, the feasibility of multiexponential T1 relaxometry was assessed as a basis for in vivo delineation of cortical lamination. Three methods of non-linear least-squares-based multiexponential analysis were examined across key degrees of freedom identified in the literature. The methods employ a wide variety of ways to overcome the common pitfalls of multiexponential analysis, such as regularization, bound constraints, and repeated optimization from multiple starting points. A custom MRI phantom was 3D-printed and filled with various MnCL2 mixtures that represent the spin-lattice relaxation times that commonly occur in neocortical gray and white matter at 3 T. A 96 × 96-voxel image consisting of a single slice was acquired using a FLASH sequence and used to create 10 composite datasets with known distributions of T1 decay constants. The results showed that lowest relative error achieved across multiexponential models was approximately 20%. As achieving even this level of estimation accuracy requires either T1 ratios that rarely occur in the cerebral cortex or knowledge of the number of relaxation components and their expected values to a degree that is seldom feasible, the visualization of cortical layers based on these estimates is unlikely to represent their true distribution. In conclusion, the current methodological approaches do not allow for sufficiently precise estimation of T1 decay constants spanning the range of cortical gray and white matter.by Kenichi Shibuya, Rie Ibusuki, Daisaku Nishimoto, Shiroh Tanoue, Chihaya Koriyama, Shuhei Niiyama, Yasuyuki Kakihana, Toshiro Takezaki, Megumi Hara, Yuichiro Nishida, Sadao Suzuki, Takeshi Nishiyama, Mako Nagayoshi, Takashi Tamura, Yudai Tamada, Rieko Okada, Teruhide Koyama, Satomi Tomida, Kiyonori Kuriki, Jun Otonari, Hiroaki Ikezaki, Asahi Hishida, Masashi Ishizu, Sakurako Katsuura-Kamano, Kenji Wakai, Keitaro Matsuo, for the J-MICC Study group
Although the clinical importance of serum albumin and gamma gap levels is well established, it is unclear how these levels are associated with health risks in the general population. This cohort study aimed to clarify the association between serum albumin and gamma gap levels, and their combined effect, and mortality risk in a Japanese population. The participants totaled 35,746 (17,160 men and 18,586 women) aged 35–69 years from the Japan Multi-Institutional Collaborative Cohort (J-MICC) Study. The mean follow-up period was 11.8 years, with 1,529 deaths and 1,907 censoring. The Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals after adjusting for related factors. Increased HRs of low albumin and high gamma gap levels were respectively observed for deaths from all-causes, cancer, cardiovascular diseases, respiratory system diseases without pneumonia, and other-causes; and the HR was the highest on respiratory system diseases without pneumonia (HR = 7.31, 4.15–12.9). Low albumin and low gamma gap levels were strongly associated for pneumonia death (HR = 12.4, 3.98–38.5). The interaction between albumin and gamma gap levels was significant for deaths from all-causes, pneumonia and other-causes. The dose relationship for each association was dose-dependent in albumin and threshold-type in gamma gap, except for other-causes. This study suggests that albumin and gamma gap levels are independent indicators of an increased risk of mortality in a Japanese population. Combined effect was apparent for mortality from all-causes, pneumonia, and other-causes.Persons living with HIV (PLWH) have an augmented risk of cardiovascular disease, including atherosclerosis and myocardial dysfunction, despite effective viral suppression with antiretroviral therapy. Despite the majority of PLWH residing in sub-Saharan Africa, there are limited reports from the region on structural cardiovascular changes due to this residual risk.
The Early Structural Cardiovascular Disease, HIV, and Tuberculosis in East Africa (ASANTE) cross-sectional study will be conducted in a public hospital in Nairobi, Kenya. It will enrol 400 participants (50% women, 50% PLWH) to undergo cardiovascular phenotyping using multimodal imaging (coronary CT angiography (CCTA) and echocardiography) and banking of biological samples (whole blood, peripheral blood mononuclear cells, plasma and urine). We will define the prevalence of subclinical coronary atherosclerosis by CCTA and subclinical myocardial dysfunction by transthoracic echocardiography and evaluate both traditional and non-traditional risk factors, including endemic infections such as latent tuberculosis. This study will contribute important data on phenotypes of and risk factors for HIV-associated cardiovascular disease in this understudied region.
Ethical approval for the ASANTE study was granted by the University of Nairobi-Kenyatta National Hospital Ethical Review Committee, Nairobi, Kenya, and the University of Washington Institutional Review Board, USA. Results will be submitted for publication in peer-reviewed journals.
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