Background: The risk factors for prevalent delirium in older hospitalised adults in Sub-Saharan Africa (SSA) remain poorly characterised. Methods: A total of 510 consecutive admissions of adults aged ≥60 years to acute medical wards of Kilimanjaro Christian Medical Centre in northern Tanzania were recruited. Patients were assessed within 24 h of admission with a risk factor questionnaire, physiological observations, neurocognitive assessment, and informant interview. Delirium and dementia diagnoses were made according to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM V) and DSM IV respectively, by an expert panel. Results: Being male, current alcohol use, dementia, and physiological markers of illness severity were significant independent risk factors for delirium on multivariable analysis. Conclusions: The risk factors for prevalent delirium in older medical inpatients in SSA include pre-existing dementia, and are similar to those identified in high-income countries. Our data could help inform the development of a delirium risk stratification tool for older adults in SSA.

Both instruments appeared useful for delirium screening in this inpatient setting, but had significant limitations. The combination of assessment items identified may form the basis of a brief, simple delirium screening tool suitable for use by non-specialist clinicians. Further development work is needed.

No abstract

No abstract

Purpose Before being marketed, hernia mesh must undergo in vivo testing, which often includes biomechanical and histological assessment. Currently, there are no universal standards for this testing and methods vary greatly within the literature. A scoping review of relevant studies was undertaken to analyse the methodologies used for in vivo mesh testing. Methods Medline and Embase databases were searched for relevant studies. 513 articles were identified and 231 duplicates excluded. 126 papers were included after abstract and full text review. The data extraction was undertaken using standardised forms. Results Mesh is most commonly tested in rats (53%). 78% of studies involve the formation of a defect; in 52% of which the fascia is not opposed. The most common hernia models use mesh to bridge an acute defect (50%). Tensile strength testing is the commonest form of mechanical testing (63%). Testing strip widths and test speeds vary greatly (4–30 mm and 1.625–240 mm/min, respectively). There is little consensus on which units to use for tensile strength testing. Collagen is assessed for its abundance (54 studies) more than its alignment (18 studies). Alignment is not measured quantitatively. At least 21 histological scoring systems are used for in vivo mesh testing. Conclusions The current practice of in vivo mesh testing lacks standardisation. There is significant inconsistency in every category of testing, both in methodology and comparators. We would call upon hernia organisations and materials testing institutions to discuss the need for a standardised approach to this field.

Background: In sub-Saharan Africa, there are no validated screening tools for delirium in older adults. This study assesses clinical utility of two instruments, the IDEA cognitive screen and the Confusion Assessment Method (CAM) for identification of delirium in older adults admitted to medical wards of a tertiary referral hospital in Tanzania. Method: The IDEA cognitive screen and CAM were administered to a consecutive cohort of older individuals on admission to Kilimanjaro Christian Medical Centre using a blinded protocol. Consensus diagnosis for delirium was established against DSM-V criteria and dementia by DSM-IV criteria Results: Of 507 admission assessments, 95 (18.7%) had DSM-V delirium and 95 (18.7%) had DSM-IV dementia (33 (6.5%) delirium superimposed on dementia). The CAM and IDEA cognitive screen had very good diagnostic accuracy for delirium (AUROC curve 0.94 and 0.87 respectively). However, a number of participants (10.5% and 16.4% respectively) were unable to complete these screening assessments due to reduced consciousness, or other causes of reduced verbal response and were excluded from this analysis; many of whom met DSM-V criteria for delirium. Secondary analysis suggests that selected cognitive and observational items from the CAM and IDEA cognitive screen may be as effective as the full screening tools in identifying delirium even in unresponsive patients. Conclusion: Both instruments appeared useful for delirium screening in this inpatient setting, but had significant limitations. The combination of assessment items identified may form the basis of a brief, simple delirium screening tool suitable for use by non-specialist clinicians. Further development work is needed.

Introduction Mesh implants are regularly used to help repair both hiatus hernias (HH) and diaphragmatic hernias (DH). In vivo studies are used to test not only mesh safety, but increasingly comparative efficacy. Our work examines the field of in vivo mesh testing for HH and DH models to establish current practices and standards. Method This systematic review was registered with PROSPERO. Medline and Embase databases were searched for relevant in vivo studies. Forty-four articles were identified and underwent abstract review, where 22 were excluded. Four further studies were excluded after full-text review—leaving 18 to undergo data extraction. Results Of 18 studies identified, 9 used an in vivo HH model and 9 a DH model. Five studies undertook mechanical testing on tissue samples—all uniaxial in nature. Testing strip widths ranged from 1–20 mm (median 3 mm). Testing speeds varied from 1.5–60 mm/minute. Upon histology, the most commonly assessed structural and cellular factors were neovascularisation and macrophages respectively (n = 9 each). Structural analysis was mostly qualitative, where cellular analysis was equally likely to be quantitative. Eleven studies assessed adhesion formation, of which 8 used one of four scoring systems. Eight studies measured mesh shrinkage. Discussion In vivo studies assessing mesh for HH and DH repair are uncommon. Within this relatively young field, we encourage surgical and materials testing institutions to discuss its standardisation.

variables and construct prediction models that optimize detection and classification, and show that ML methods improve diagnostic accuracy compared to existing CDT scoring systems. Methods: We applied our novel dCDT software to categorize every pen stroke from 3994 neurologically impaired and cognitively healthy (CH) subjects, computing approximately 1000 novel variables on that data. Using ML techniques (e.g., regularized logistic regression) we created models that best classify subjects into four categories: memory impaired, vascular related disorders, Parkinson's disease, CH. We embodied in code eight manual scoring systems (MSS), then adjusted their parameters to optimize their performance. We measured our ML model performances using 5-fold cross-validation, reporting AUCs averaged over the 5 folds and compared predictive performance to the MSS optimized versions. Results: Classifiers produced by ML methods significantly outperformed MSS: ML methods had an AUC performance ranging from 0.87 to 0.92 (depending on the algorithm and condition being classified), while corresponding AUCs for MSS ranged from 0.63 to 0.74. The MSS AUC ranges were higher than what those manual scoring systems would produce in practice, as optimization ensured their best performance and embodying them in code eliminated all interrater reliability error. Conclusions: ML methods combined with precise spatial and temporal analysis of drawing behavior enables the creation of new ways to detect and classify cognitive functions with far greater accuracy, enabling improved diagnostic capabilities with little to no manual effort. Applying ML to theoretical models improves predictive value by using features not typically considered under existing frameworks. Combining new technology and advanced analytics with theoretical neurosciences enables new opportunities for early diagnosis and treatment.