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Falls are a major concern for people with Parkinson's disease (PwPD), but accurately assessing real-world fall risk beyond the clinic is challenging. Contemporary technologies could enable the capture of objective and high-resolution data to better inform fall risk through measurement of everyday factors (e.g., obstacles) that contribute to falls. Wearable inertial measurement units (IMUs) capture objective high-resolution walking/gait data in all environments but are limited by not providing absolute clarity on contextual information (i.e., obstacles) that could greatly influence how gait is interpreted. Video-based data could compliment IMU-based data for a comprehensive free-living fall risk assessment. The objective of this study was twofold. First, pilot work was conducted to propose a novel artificial intelligence (AI) algorithm for use with wearable video-based eye-tracking glasses to compliment IMU gait data in order to better inform free-living fall risk in PwPD. The suggested approach (based on a fine-tuned You Only Look Once version 8 (YOLOv8) object detection algorithm) can accurately detect and contextualize objects (mAP50 = 0.81) in the environment while also providing insights into where the PwPD is looking, which could better inform fall risk. Second, we investigated the perceptions of PwPD via a focus group discussion regarding the adoption of video technologies and AI during their everyday lives to better inform their own fall risk. This second aspect of the study is important as, traditionally, there may be clinical and patient apprehension due to ethical and privacy concerns on the use of wearable cameras to capture real-world video. Thematic content analysis was used to analyse transcripts and develop core themes and categories. Here, PwPD agreed on ergonomically designed wearable video-based glasses as an optimal mode of video data capture, ensuring discreteness and negating any public stigma on the use of research-style equipment. PwPD also emphasized the need for control in AI-assisted data processing to uphold privacy, which could overcome concerns with the adoption of video to better inform IMU-based gait and free-living fall risk. Contemporary technologies (wearable video glasses and AI) can provide a holistic approach to fall risk that PwPD recognise as helpful and safe to use.
Subject(s)
Accidental Falls , Algorithms , Artificial Intelligence , Gait , Parkinson Disease , Humans , Accidental Falls/prevention & control , Parkinson Disease/physiopathology , Risk Assessment/methods , Gait/physiology , Male , Aged , Female , Video Recording/methods , Wearable Electronic Devices , Middle Aged , Walking/physiologyABSTRACT
BACKGROUND: The African Stroke Organization (ASO) in partnership with the University of Central Lancashire's Stroke Research Team launched the Africa-UK Stroke Partnership (AUKSP). AUKSP undertook two (stroke expert and hospital Stroke Unit (SU)) on-line surveys mapping existing capacity and capability to deliver African stroke care. METHODS: An on-line expert survey tool was sent to 139 stroke experts in 54 African countries October 2021-March 2022 and the hospital SU survey to 120 hospital SUs (identified from the expert survey) June-October 2022. Both survey tools were prepared according to the World Stroke Organisation's Roadmap for Delivering Quality Stroke Care. Completed responses were exported from Qualtrics into Microsoft excel and were analysed descriptively. RESULTS: Forty-five expert responses and 62 hospital SU responses were analysed, representing 54(87%) public hospitals, 7(11%) private and 1(2%) charitable organization. In both surveys, three main priorities for improvement of stroke services were: a rapid and prompt stroke diagnosis; effective primary and secondary stroke prevention, and acute stroke management. Survey findings suggest that there is a low presence of national stroke surveillance systems and registries, and heterogeneity in availability of diagnostic services, SUs, endovascular treatments, and rehabilitation. CONCLUSION: Significant gaps exist in Africa's capacity and capability to deliver essential elements of effective and quality stroke care. Tackling these challenges requires urgent and sustained multi-stakeholder action including: government, administrators, policy makers and other partners. Our survey findings highlight key priority areas for multi-stakeholder engagement and crafting of a pragmatic, prioritized and context-sensitive African Stroke Action Plan.
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BACKGROUND: The accessibility of Parkinson's disease medicines is limited across sub-Saharan Africa, which can have negative health, social and financial consequences for people with Parkinson's disease and their families. However, there is a stark gap in the literature regarding the impact of poor access to medicines on individuals. OBJECTIVES: The study objective was to understand the accessibility of Parkinson's disease medicines in Kenya from the perspective of people with Parkinson's disease, their caregivers and neurologists. METHODS: In-depth qualitative interviews were conducted with 55 people with Parkinson's disease, 23 caregivers and 8 neurologists to understand their experience regarding challenges with accessing Parkinson's disease medicines and the health, social and financial impact of poor availability and affordability. RESULTS: Medicines for Parkinson's disease were deemed to be largely unavailable and unaffordable across Kenya. People with Parkinson's disease, caregivers and neurologists expressed the financial burden caused by long-term treatment in the absence of health insurance coverage. Further, barriers accessing medicines negatively impacted symptom control, social relations, and quality of life. CONCLUSIONS: Access to Parkinson's disease medicines in Kenya is limited, with severe implications for symptom management and quality of life. People with Parkinson's disease should be able to access and afford the medicines they need to manage their condition.
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HIV-associated neurocognitive disorders (HAND) are highly prevalent in those ageing with HIV. High-income country data suggest that vascular risk factors (VRFs) may be stronger predictors of HAND than HIV-disease severity, but data from sub-Saharan Africa are lacking. We evaluated relationships of VRFs, vascular end-organ damage and HAND in individuals aged ≥ 50 in Tanzania. c-ART-treated individuals were assessed for HAND using consensus criteria. The prevalence of VRFs and end organ damage markers were measured. The independent associations of VRFs, end organ damage and HAND were examined using multivariable logistic regression. Data were available for 153 individuals (median age 56, 67.3% female). HAND was highly prevalent (66.7%, 25.5% symptomatic) despite well-managed HIV (70.5% virally suppressed). Vascular risk factors included hypertension (34%), obesity (10.5%), hypercholesterolemia (33.3%), diabetes (5.3%) and current smoking (4.6%). End organ damage prevalence ranged from 1.3% (prior myocardial infarction) to 12.5% (left ventricular hypertrophy). Measured VRFs and end organ damage were not independently associated with HAND. The only significant association was lower diastolic BP (p 0.030, OR 0.969 (0.943-0.997). Our results suggest that vascular risk factors are not major drivers of HAND in this setting. Further studies should explore alternative aetiologies such as chronic inflammation.
Subject(s)
HIV Infections , Humans , Female , Male , Tanzania/epidemiology , Middle Aged , Risk Factors , HIV Infections/complications , HIV Infections/epidemiology , Aged , Prevalence , AIDS Dementia Complex/epidemiology , Anti-HIV Agents/therapeutic use , Antiretroviral Therapy, Highly Active , Neurocognitive Disorders/epidemiology , Neurocognitive Disorders/etiologyABSTRACT
Enterotoxigenic Escherichia coli (ETEC) is the most prevalent bacterial pathogen causing young children to suffer acute watery diarrhea in Low- and Middle-Income Countries (LMICs) [...].
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BACKGROUND: Associations between procedure volumes and outcomes can inform minimum volume standards and the regionalization of health services. Robot-assisted surgery continues to expand globally; however, data are limited regarding which hospitals should be using the technology. STUDY DESIGN: Using administrative health data for all residents of Ontario, Canada, this retrospective cohort study included adult patients who underwent a robot-assisted radical prostatectomy (RARP), total robotic hysterectomy (TRH), robot-assisted partial nephrectomy (RAPN), or robotic portal lobectomy using 4 arms (RPL-4) between January 2010 and September 2021. Associations between yearly hospital volumes and 90-day major complications were evaluated using multivariable logistic regression models adjusted for patient characteristics and clustering at the level of the hospital. RESULTS: A total of 10,879 patients were included, with 7567, 1776, 724, and 812 undergoing a RARP, TRH, RAPN, and RPL-4, respectively. Yearly hospital volume was not associated with 90-day complications for any procedure. Doubling of yearly volume was associated with a 17-min decrease in operative time for RARP (95% confidence interval [CI] - 23 to - 10), 8-min decrease for RAPN (95% CI - 14 to - 2), 24-min decrease for RPL-4 (95% CI - 29 to - 19), and no significant change for TRH (- 7 min; 95% CI - 17 to 3). CONCLUSION: The risk of 90-day major complications does not appear to be higher in low volume hospitals; however, they may not be as efficient with operating room utilization. Careful case selection may have contributed to the lack of an observed association between volumes and complications.
Subject(s)
Hospitals, High-Volume , Hospitals, Low-Volume , Nephrectomy , Postoperative Complications , Prostatectomy , Robotic Surgical Procedures , Humans , Robotic Surgical Procedures/statistics & numerical data , Male , Female , Retrospective Studies , Middle Aged , Ontario , Prostatectomy/methods , Nephrectomy/methods , Aged , Hospitals, High-Volume/statistics & numerical data , Postoperative Complications/epidemiology , Postoperative Complications/etiology , Hospitals, Low-Volume/statistics & numerical data , Operative Time , Hysterectomy/methods , Hysterectomy/statistics & numerical data , AdultABSTRACT
Objectives: This study aimed to understand the care needs, care arrangements and burden of care for people with dementia in Northern Tanzania. Methods: This was a cross-sectional, observational study. People with dementia and their carers (n = 53) were recruited from an outpatient clinic, and data on carer burden and independence in activities of daily living were collected. Associations with carer burden and characteristics were explored through non-parametric tests and regression analyses. Results: Thirty-six carers were female (68%). Levels of impairment in instrumental activities of daily living were high, with a median score of 38 out of 44 on the Identification and Intervention for Dementia in Elderly Africans - Instrumental Activities of Daily Living (IDEA-IADL). Carer burden was moderate with a median Zarit Burden Interview (ZBI) score of 46 out of 88. Being a female carer was associated with higher carer burden (odds ratio 3.68, 95% CI 1.04-12.99). Discussion: Carer burden was found to be higher than in previous studies based in low-and-middle income countries. Further research is needed to explore this difference, and to identify interventions to support care needs and reduce carer burden.
Subject(s)
Activities of Daily Living , Caregivers , Dementia , Humans , Female , Cross-Sectional Studies , Male , Dementia/nursing , Dementia/psychology , Caregivers/psychology , Aged , Tanzania , Middle Aged , Aged, 80 and over , Cost of Illness , Adult , Health Services Needs and DemandABSTRACT
SummaryThe adoption of robotic surgery has surged globally across multiple surgical specialties, but uptake in Canada has unfolded at a slower pace. Surgical educators and trainees in Canada face potential challenges related to sufficient exposure, experience, and competence in robotic surgical procedures. We conducted a cross-sectional national survey to gain insight into the perspectives of program directors overseeing general surgery residency and fellowship programs on the integration of robotic surgery into Canadian surgical training programs. Despite the presence of robotic surgery platforms at most academic and academic-affiliated hospitals, few trainees have exposure to any robotic surgery. Furthermore, a gap exists between the training provided in robotic surgery and its anticipated relevance to trainees upon graduation. Increased focus on the integration of robotic surgery within general surgical training in Canada is required to equip trainees for their careers.
Subject(s)
Internship and Residency , Robotic Surgical Procedures , Canada , Robotic Surgical Procedures/education , Humans , Cross-Sectional Studies , General Surgery/education , Surveys and Questionnaires , Fellowships and Scholarships , Clinical Competence , Education, Medical, Graduate/methodsABSTRACT
INTRODUCTION: Traumatic bone marrow lesions (BML) are frequently identified on knee MRI scans in patients following an acute full-thickness, complete ACL tear. BMLs coincide with regions of elevated localized bone loss, and studies suggest these may act as a precursor to the development of post-traumatic osteoarthritis. This study addresses the labour-intensive manual assessment of BMLs by using a 3D U-Net for automated identification and segmentation from MRI scans. METHODS: A multi-task learning approach was used to segment both bone and BML from T2 fat-suppressed (FS) fast spin echo (FSE) MRI sequences for BML assessment. Training and testing utilized datasets from individuals with complete ACL tears, employing a five-fold cross-validation approach and pre-processing involved image intensity normalization and data augmentation. A post-processing algorithm was developed to improve segmentation and remove outliers. Training and testing datasets were acquired from different studies with similar imaging protocol to assess the model's performance robustness across different populations and acquisition conditions. RESULTS: The 3D U-Net model exhibited effectiveness in semantic segmentation, while post-processing enhanced segmentation accuracy and precision through morphological operations. The trained model with post-processing achieved a Dice similarity coefficient (DSC) of 0.75 ± 0.08 (mean ± std) and a precision of 0.87 ± 0.07 for BML segmentation on testing data. Additionally, the trained model with post-processing achieved a DSC of 0.93 ± 0.02 and a precision of 0.92 ± 0.02 for bone segmentation on testing data. This demonstrates the approach's high accuracy for capturing true positives and effectively minimizing false positives in the identification and segmentation of bone structures. CONCLUSION: Automated segmentation methods are a valuable tool for clinicians and researchers, streamlining the assessment of BMLs and allowing for longitudinal assessments. This study presents a model with promising clinical efficacy and provides a quantitative approach for bone-related pathology research and diagnostics.
Subject(s)
Anterior Cruciate Ligament Injuries , Bone Marrow , Deep Learning , Magnetic Resonance Imaging , Humans , Magnetic Resonance Imaging/methods , Anterior Cruciate Ligament Injuries/diagnostic imaging , Bone Marrow/diagnostic imaging , Male , Female , Adult , Image Interpretation, Computer-Assisted/methodsABSTRACT
BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait. METHOD: The approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset. RESULTS: VARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications. CONCLUSION: The instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common.
Subject(s)
Accidental Falls , Deep Learning , Walking , Accidental Falls/prevention & control , Humans , Risk Assessment/methods , Walking/physiology , Male , Female , Adult , Eye-Tracking Technology , Eye Movements/physiology , Gait/physiology , Video Recording , Young AdultABSTRACT
BACKGROUND: Of the neurodegenerative diseases, Parkinson's disease is recognised to have the fastest growing prevalence. It is unclear whether this is due to the ageing global population alone, with several environmental factors increasingly implicated in changing prevalence rates. Large data sets have been used nationally and globally to help predict future disease burden. However, the reliability of such sources is yet unknown for Parkinson's disease. SUMMARY: This review discusses the methods used in all published UK prevalence studies conducted to date. Direct comparison between prevalence figures obtained from the 10 to discussed prevalence studies is precluded due to differences in methodology for case ascertainment and diagnosis. Age adjusted estimates vary from 105/100,000 to 168/100,000. KEY MESSAGES: These studies demonstrate no overall trend in changing prevalence figures between 1961 and 2007. No difference in prevalence trends were seen for those living in rural or urban areas. Differences between ethnic groups, for example, remains an under explored area.
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OBJECTIVE: Human immunodeficiency virus (HIV)-associated neurocognitive disorder (HAND) prevalence is expected to increase in East Africa as treatment coverage increases, survival improves, and this population ages. This study aimed to better understand the current cognitive phenotype of this newly emergent population of older combination antiretroviral therapy (cART)-treated people living with HIV (PLWH), in which current screening measures lack accuracy. This will facilitate the refinement of HAND cognitive screening tools for this setting. METHOD: This is a secondary analysis of 253 PLWH aged ≥50 years receiving standard government HIV clinic follow-up in Kilimanjaro, Tanzania. They were evaluated with a detailed locally normed low-literacy neuropsychological battery annually on three occasions and a consensus panel diagnosis of HAND by Frascati criteria based on clinical evaluation and collateral history. RESULTS: Tests of verbal learning and memory, categorical verbal fluency, visual memory, and visuoconstruction had an area under the receiver operating characteristic curve >0.7 for symptomatic HAND (s-HAND) (0.70-0.72; p < 0.001 for all tests). Tests of visual memory, verbal learning with delayed recall and recognition memory, psychomotor speed, language comprehension, and categorical verbal fluency were independently associated with s-HAND in a logistic mixed effects model (p < 0.01 for all). Neuropsychological impairments varied by educational background. CONCLUSIONS: A broad range of cognitive domains are affected in older, well-controlled, East African PLWH, including those not captured in widely used screening measures. It is possible that educational background affects the observed cognitive impairments in this setting. Future screening measures for similar populations should consider assessment of visual memory, verbal learning, language comprehension, and executive and motor function.
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INTRODUCTION: Loss to follow-up (LTFU) distorts results of randomized controlled trials (RCTs). Understanding trial characteristics that contribute to LTFU may enable investigators to anticipate the extent of LTFU and plan retention strategies. The objective of this systematic review and meta-analysis was to investigate the extent of LTFU in surgical RCTs and evaluate associations between trial characteristics and LTFU. METHODS: MEDLINE, Embase, and PubMed Central were searched for surgical RCTs published between January 2002 and December 2021 in the 30 highest impact factor surgical journals. Two-hundred eligible RCTs were randomly selected. The pooled LTFU rate was estimated using random intercept Poisson regression. Associations between trial characteristics and LTFU were assessed using metaregression. RESULTS: The 200 RCTs included 37,914 participants and 1307 LTFU events. The pooled LTFU rate was 3.10 participants per 100 patient-years (95% confidence interval [CI] 1.85-5.17). Trial characteristics associated with reduced LTFU were standard-of-care outcome assessments (rate ratio [RR] 0.17; 95% CI 0.06-0.48), surgery for transplantation (RR 0.08; 95% CI 0.01-0.43), and surgery for cancer (RR 0.10; 95% CI 0.02-0.53). Increased LTFU was associated with patient-reported outcomes (RR 14.21; 95% CI 4.82-41.91) and follow-up duration ≥ three months (odds ratio 10.09; 95% CI 4.79-21.28). CONCLUSIONS: LTFU in surgical RCTs is uncommon. Participants may be at increased risk of LTFU in trials with outcomes assessed beyond the standard of care, surgical indications other than cancer or transplant, patient-reported outcomes, and longer follow-up. Investigators should consider the impact of design on LTFU and plan retention strategies accordingly.
Subject(s)
Lost to Follow-Up , Randomized Controlled Trials as Topic , Humans , Randomized Controlled Trials as Topic/statistics & numerical data , Surgical Procedures, Operative/statistics & numerical dataABSTRACT
Introduction: musculoskeletal (MSK) disorders account for approximately 20% of all years lived with disability worldwide however studies of MSK disorders in Africa are scarce. This pilot study aimed to estimate the community-based prevalence of MSK disorders, identify predictors, and assess the associated disability in a Tanzanian population. Methods: a cross-sectional study was conducted in one village in the Kilimanjaro region from March to June 2019. The Gait, Arms, Legs, Spine (GALS) or paediatric GALS (pGALS) examinations were used during household and school visits. Individuals positive in GALS/pGALS screening were assessed by the regional examination of the musculoskeletal system (REMS) and Modified Health Assessment Questionnaire (MHAQ). Results: among the 1,172 individuals enrolled in households, 95 (8.1%, 95% CI: 6.6 - 9.8) showed signs of MSK disorders using the GALS/pGALS examination and 37 (3.2%, 95% CI: 2.2 - 4.3) using the REMS. Among 682 schools enrolled children, seven showed signs of MSK disorders using the GALS/pGALS examination (1.0%, 95% CI: 0.4 - 2.1) and three using the REMS (0.4%, 95% CI: 0.0 - 1.3). In the household-enrolled adult population, female gender and increasing age were associated with GALS and REMS-positive findings. Among GALS-positive adults, increasing age was associated with REMS-positive status and increasing MHAQ score. Conclusion: this Tanzanian study demonstrates a prevalence of MSK disorders and identifies predictors of MSK disorders comparable to those seen globally. These findings can inform the development of rheumatology services and interventions in Tanzania and the design of future investigations of the determinants of MSK disorders, and their impacts on health, livelihoods, and well-being.
Subject(s)
Mitoxantrone/analogs & derivatives , Musculoskeletal Diseases , Adult , Humans , Female , Child , Cross-Sectional Studies , Tanzania/epidemiology , Pilot Projects , Prevalence , Musculoskeletal Diseases/epidemiology , GaitABSTRACT
A wide-field microscope with epi-fluorescence and selective plane illumination was combined with a single-photon avalanche diode (SPAD) array camera to enable live-cell fluorescence lifetime imaging (FLIM) using time-correlated single-photon counting (TCSPC). The camera sensor comprised of 192 × 128 pixels, each integrating a single SPAD and a time-to-digital converter. Jointly, they produced a stream of single-photon images of photon arrival times with ≈ 38 ps accuracy. The photon arrival times were subject to systematic delays and nonlinearities, which were corrected by a Monte-Carlo algorithm. The SPAD camera was then applied to FLIM where histogramming the resulting photon arrival times in each pixel resulted in decays compatible with common data processing pipelines for fluorescence lifetime analysis. The capabilities of the TCSPC camera-based FLIM microscope were demonstrated by imaging living unicellular photosynthetic algae and artificial lipid vesicles. Epi-fluorescence illumination enabled rapid fluorescence lifetime imaging of living cells and selective-plane illumination enabled 3-dimensional FLIM of stationary samples.
Subject(s)
Algorithms , Microscopy, Fluorescence/methodsABSTRACT
Wearable inertial measurement units (IMUs) are being used to quantify gait characteristics that are associated with increased fall risk, but the current limitation is the lack of contextual information that would clarify IMU data. Use of wearable video-based cameras would provide a comprehensive understanding of an individual's habitual fall risk, adding context to clarify abnormal IMU data. Generally, there is taboo when suggesting the use of wearable cameras to capture real-world video, clinical and patient apprehension due to ethical and privacy concerns. This perspective proposes that routine use of wearable cameras could be realized within digital medicine through AI-based computer vision models to obfuscate/blur/shade sensitive information while preserving helpful contextual information for a comprehensive patient assessment. Specifically, no person sees the raw video data to understand context, rather AI interprets the raw video data first to blur sensitive objects and uphold privacy. That may be more routinely achieved than one imagines as contemporary resources exist. Here, to showcase/display the potential an exemplar model is suggested via off-the-shelf methods to detect and blur sensitive objects (e.g., people) with an accuracy of 88%. Here, the benefit of the proposed approach includes a more comprehensive understanding of an individual's free-living fall risk (from free-living IMU-based gait) without compromising privacy. More generally, the video and AI approach could be used beyond fall risk to better inform habitual experiences and challenges across a range of clinical cohorts. Medicine is becoming more receptive to wearables as a helpful toolbox, camera-based devices should be plausible instruments.
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BACKGROUND: Populations are ageing globally and Low- and Middle-Income Countries (LMICs) are experiencing the fastest rates of demographic change. Few studies have explored the burden of frailty amongst older people in hospital in LMICs, where healthcare services are having to rapidly adapt to align with the needs of older people. This study aimed to measure the prevalence of frailty amongst older people admitted to hospital in Tanzania and to explore their demographic and clinical characteristics. METHODS: This study had a prospective observational design. Over a six-month period, all adults ≥ 60 years old admitted to medical wards in four hospitals in northern Tanzania were invited to participate. They were screened for frailty using the Clinical Frailty Scale (CFS) and the Frailty Phenotype (FP). Demographic and clinical characteristics of interest were recorded in a structured questionnaire. These included the Barthel Index, the Identification of Elderly Africans Instrumental Activities of Daily Living (IADEA-IADL) and Cognitive (IDEA-Cog) screens, the EURO-D depression scale and Confusion Assessment Method. RESULTS: 540 adults aged ≥ 60 were admitted, and 308 completed assessment. Frailty was present in 66.6% using the CFS and participants with frailty were significantly older, with lower levels of education and literacy, greater disability, greater comorbidity, poorer cognition and higher levels of delirium. Using the FP, 57.0% of participants were classed as frail though a majority of participants (n = 159, 51.6%) could not be classified due to a high proportion of missing data. CONCLUSIONS: This study indicates that the prevalence of frailty on medical wards in northern Tanzania is high according to the CFS. However, the challenges in operationalising the FP in this setting highlight the need for future work to adapt frailty screening tools for an African context. Future investigations should also seek to correlate frailty status with long-term clinical outcomes after admission in this setting.
Subject(s)
Frailty , Aged , Humans , Frailty/diagnosis , Frailty/epidemiology , Frailty/psychology , Frail Elderly/psychology , Activities of Daily Living , Tanzania/epidemiology , Geriatric Assessment/methods , HospitalsABSTRACT
OBJECTIVE: Direct magnetic resonance arthrography (dMRA) is often considered the most accurate imaging modality for the evaluation of intra-articular structures, but utilization and performance vary widely without consensus. The purpose of this white paper is to develop consensus recommendations on behalf of the Society of Skeletal Radiology (SSR) based on published literature and expert opinion. MATERIALS AND METHODS: The Standards and Guidelines Committee of the SSR identified guidelines for utilization and performance of dMRA as an important topic for study and invited all SSR members with expertise and interest to volunteer for the white paper panel. This panel was tasked with determining an outline, reviewing the relevant literature, preparing a written document summarizing the issues and controversies, and providing recommendations. RESULTS: Twelve SSR members with expertise in dMRA formed the ad hoc white paper authorship committee. The published literature on dMRA was reviewed and summarized, focusing on clinical indications, technical considerations, safety, imaging protocols, complications, controversies, and gaps in knowledge. Recommendations for the utilization and performance of dMRA in the shoulder, elbow, wrist, hip, knee, and ankle/foot regions were developed in group consensus. CONCLUSION: Although direct MR arthrography has been previously used for a wide variety of clinical indications, the authorship panel recommends more selective application of this minimally invasive procedure. At present, direct MR arthrography remains an important procedure in the armamentarium of the musculoskeletal radiologist and is especially valuable when conventional MRI is indeterminant or results are discrepant with clinical evaluation.