Short-term risk of fracture is increased by deficits in cortical and trabecular bone microarchitecture independent of DXA BMD and FRAX: bone microarchitecture international consortium (BoMIC) prospective cohorts.

Identifying individuals at risk for short-term fracture is essential to offer prompt beneficial treatment, especially since many fractures occur in those without osteoporosis by DXA-aBMD. We evaluated whether deficits in bone microarchitecture and density predict short-term fracture risk independent of the clinical predictors, DXA-BMD and FRAX. We combined data from eight cohorts to conduct a prospective study of bone microarchitecture at the distal radius and tibia (by HR-pQCT) and 2-year incidence of fracture (non-traumatic and traumatic) in 7327 individuals (4824 women, 2503 men, mean 69 ± 9 years). We estimated sex-specific hazard ratios (HR) for associations between bone measures and 2-year fracture incidence, adjusted for age, cohort, height and weight, and then additionally adjusted for femoral neck (FN) aBMD or FRAX for major osteoporotic fracture. Only 7% of study participants had FN T-score ≤ -2.5, whereas 53% had T-scores between -1.0 to -2.5 and 37% had T-scores ≥-1.0. Two-year cumulative fracture incidence was 4% (296/7327). Each SD decrease in radius cortical bone measures increased fracture risk by 38%-76% for women and men. After additional adjustment for FN-aBMD, risks remained increased by 28%-61%. Radius trabecular measures were also associated with 2-year fracture risk independently of FN-aBMD in women (HRs range: 1.21 per SD for trabecular separation to 1.55 for total vBMD). Decreased failure load was associated with increased fracture risk in both women and men (FN-aBMD ranges of adjusted HR = 1.47-2.42). Tibia measurement results were similar to radius results. Findings were also similar when models were adjusted for FRAX. In older adults, failure load and HR-pQCT measures of cortical and trabecular bone microarchitecture and density with strong associations to short-term fractures improved fracture prediction beyond aBMD and FRAX. Thus, HR-pQCT may be a useful adjunct to traditional assessment of short-term fracture risk in older adults, including those with T-scores above the osteoporosis range.

Identifying individuals at risk for short-term fracture (within 2-years) is essential to offer prompt treatment. We examined bone microarchitecture at arm and lower leg for prediction of short-term fractures in 7327 older adults, independent of the common clinical practice measures ­ DXA-BMD and FRAX. After adjusting for other factors, we found that measures of failure load, cortical and trabecular bone microarchitecture and density predicted short-term risk of fracture beyond the usual clinical measures of DXA and FRAX. These measures of bone that indicate deficits in microarchitecture may be a useful adjunct to traditional assessment of fracture risk in older adults.

Correlates and predictors of sarcopenia among men with metastatic castrate-resistant prostate cancer.

INTRODUCTION: Sarcopenia is a predictor of clinical outcomes in men with metastatic castrate-resistant prostate cancer (mCRPC); however, correlates and predictors of sarcopenia are poorly understood in this population. The aim of this study was to examine correlates and predictors of sarcopenia in men with mCRPC prior to treatment. METHODS: A secondary analysis of an observational study was performed. Participants were receiving care for mCRPC at the Princess Margaret Cancer Centre. Sarcopenia was assessed prior to treatment and was defined as the combination of low grip strength (<35.5 kg), low gait speed (<0.8 m/s), and computed tomography-derived low muscle mass or density. Participants' sociodemographic and clinical characteristics, comorbidity information, and clinically relevant blood markers were collected prior to treatment and were used to identify correlates and predictors of sarcopenia through Spearman correlations and multivariable logistic regression, respectively. RESULTS: In total, 110 men had complete data on sarcopenia measures and were included in the analysis. Sarcopenia was identified in 30 (27.3%) participants. Pre-treatment sarcopenia was moderately correlated with dependence in one or more instrumental activities of daily living (IADLs) (r=0.412), Vulnerable Elders Survey-13 (r=0.404), and a lower hemoglobin (r=0.407 per 10 g/L decrease). In adjusted logistic regression, dependence in one or more IADLs (odds ratio [OR] 4.37, 95% confidence interval [CI] 1.37-13.86, p=0.012), and a 10 g/L decrease in hemoglobin (OR 1.70, 95% CI 1.13-2.57, p=0.012) were significantly associated with sarcopenia. CONCLUSIONS: In settings where assessment of sarcopenia is not feasible, evaluation of IADLs and hemoglobin may be used to identify high-risk patients that can benefit from supportive care strategies aiming to improve muscle mass and function.

Assessing the Utility, Impact, and Adoption Challenges of an Artificial Intelligence-Enabled Prescription Advisory Tool for Type 2 Diabetes Management: Qualitative Study.

BACKGROUND: The clinical management of type 2 diabetes mellitus (T2DM) presents a significant challenge due to the constantly evolving clinical practice guidelines and growing array of drug classes available. Evidence suggests that artificial intelligence (AI)-enabled clinical decision support systems (CDSSs) have proven to be effective in assisting clinicians with informed decision-making. Despite the merits of AI-driven CDSSs, a significant research gap exists concerning the early-stage implementation and adoption of AI-enabled CDSSs in T2DM management. OBJECTIVE: This study aimed to explore the perspectives of clinicians on the use and impact of the AI-enabled Prescription Advisory (APA) tool, developed using a multi-institution diabetes registry and implemented in specialist endocrinology clinics, and the challenges to its adoption and application. METHODS: We conducted focus group discussions using a semistructured interview guide with purposively selected endocrinologists from a tertiary hospital. The focus group discussions were audio-recorded and transcribed verbatim. Data were thematically analyzed. RESULTS: A total of 13 clinicians participated in 4 focus group discussions. Our findings suggest that the APA tool offered several useful features to assist clinicians in effectively managing T2DM. Specifically, clinicians viewed the AI-generated medication alterations as a good knowledge resource in supporting the clinician's decision-making on drug modifications at the point of care, particularly for patients with comorbidities. The complication risk prediction was seen as positively impacting patient care by facilitating early doctor-patient communication and initiating prompt clinical responses. However, the interpretability of the risk scores, concerns about overreliance and automation bias, and issues surrounding accountability and liability hindered the adoption of the APA tool in clinical practice. CONCLUSIONS: Although the APA tool holds great potential as a valuable resource for improving patient care, further efforts are required to address clinicians' concerns and improve the tool's acceptance and applicability in relevant contexts.

Fracture risk based on high-resolution peripheral quantitative computed tomography measures does not vary with age in older adults-the bone microarchitecture international consortium prospective cohort study.

Fracture risk increases with lower areal bone mineral density (aBMD); however, aBMD-related estimate of risk may decrease with age. This may depend on technical limitations of 2-dimensional (2D) dual energy X-ray absorptiometry (DXA) which are reduced with 3D high-resolution peripheral quantitative computed tomography (HR-pQCT). Our aim was to examine whether the predictive utility of HR-pQCT measures with fracture varies with age. We analyzed associations of HR-pQCT measures at the distal radius and distal tibia with two outcomes: incident fractures and major osteoporotic fractures. We censored follow-up time at first fracture, death, last contact or 8 years after baseline. We estimated hazard ratios (HR) and 95%CI for the association between bone traits and fracture incidence across age quintiles. Among 6835 men and women (ages 40-96) with at least one valid baseline HR-pQCT scan who were followed prospectively for a median of 48.3 months, 681 sustained fractures. After adjustment for confounders, bone parameters at both the radius and tibia were associated with higher fracture risk. The estimated HRs for fracture did not vary significantly across age quintiles for any HR-pQCT parameter measured at either the radius or tibia. In this large cohort, the homogeneity of the associations between the HR-pQCT measures and fracture risk across age groups persisted for all fractures and for major osteoporotic fractures. The patterns were similar regardless of the HR-pQCT measure, the type of fracture, or the statistical models. The stability of the associations between HR-pQCT measures and fracture over a broad age range shows that bone deficits or low volumetric density remain major determinants of fracture risk regardless of age group. The lower risk for fractures across measures of aBMD in older adults in other studies may be related to factors which interfere with DXA but not with HR-pQCT measures.

Fulminant type 1 diabetes, an underrecognized and unique subtype of type 1 diabetes: A case series from Singapore.

Fulminant type 1 diabetes (FT1D) is a unique subtype of type 1 diabetes, characterized by acute absolute insulin deficiency, severe ketosis, and increased risk of hypoglycemia, glycemic variability and microvascular complications. Seven people with FT1D were identified from two tertiary centers in Singapore. Six were Chinese, the mean age was 35 years and all were lean (mean body mass index 20.3 kg/m2). All presented with diabetes ketosis or ketoacidosis and low C-peptide. All but one had low glutamic acid decarboxylase antibodies. Nearly half had a missed/delayed diagnosis of FT1D. Three had frequent hypoglycemia, which improved after transition to continuous subcutaneous insulin infusion therapy. Individuals with FT1D experience unique diagnostic and management challenges associated with rapid absolute insulin deficiency. Greater awareness about this clinical entity is required.

General value functions for fault detection in multivariate time series data.

One of the greatest challenges to the automated production of goods is equipment malfunction. Ideally, machines should be able to automatically predict and detect operational faults in order to minimize downtime and plan for timely maintenance. While traditional condition-based maintenance (CBM) involves costly sensor additions and engineering, machine learning approaches offer the potential to learn from already existing sensors. Implementations of data-driven CBM typically use supervised and semi-supervised learning to classify faults. In addition to a large collection of operation data, records of faulty operation are also necessary, which are often costly to obtain. Instead of classifying faults, we use an approach to detect abnormal behaviour within the machine's operation. This approach is analogous to semi-supervised anomaly detection in machine learning (ML), with important distinctions in experimental design and evaluation specific to the problem of industrial fault detection. We present a novel method of machine fault detection using temporal-difference learning and General Value Functions (GVFs). Using GVFs, we form a predictive model of sensor data to detect faulty behaviour. As sensor data from machines is not i.i.d. but closer to Markovian sampling, temporal-difference learning methods should be well suited for this data. We compare our GVF outlier detection (GVFOD) algorithm to a broad selection of multivariate and temporal outlier detection methods, using datasets collected from a tabletop robot emulating the movement of an industrial actuator. We find that not only does GVFOD achieve the same recall score as other multivariate OD algorithms, it attains significantly higher precision. Furthermore, GVFOD has intuitive hyperparameters which can be selected based upon expert knowledge of the application. Together, these findings allow for a more reliable detection of abnormal machine behaviour to allow ideal timing of maintenance; saving resources, time and cost.

Correlates of Circulating Osteoprotegerin in Women with a Pathogenic or Likely Pathogenic Variant in the BRCA1 Gene.

BACKGROUND: Lower levels of osteoprotegerin (OPG), the decoy receptor for receptor activator of NFκB (RANK)-ligand, have been reported among women with a BRCA1 mutation, suggesting OPG may be marker of cancer risk. Whether various reproductive, hormonal, or lifestyle factors impact OPG levels in these women is unknown. METHODS: BRCA1 mutation carriers enrolled in a longitudinal study, no history of cancer, and a serum sample for OPG quantification, were included. Exposure information was collected through self-reported questionnaire at study enrollment and every 2 years thereafter. Serum OPG levels (pg/mL) were measured using an ELISA, and generalized linear models were used to assess the associations between reproductive, hormonal, and lifestyle exposures at the time of blood collection with serum OPG. Adjusted means were estimated using the fully adjusted model. RESULTS: A total of 701 women with a median age at blood collection of 39.0 years (18.0-82.0) were included. Older age (Spearman r = 0.24; P < 0.001) and current versus never smoking (98.82 vs. 86.24 pg/mL; Pcat < 0.001) were associated with significantly higher OPG, whereas ever versus never coffee consumption was associated with significantly lower OPG (85.92 vs. 94.05 pg/mL; Pcat = 0.03). There were no other significant associations for other exposures (P ≥ 0.06). The evaluated factors accounted for 7.5% of the variability in OPG. CONCLUSIONS: OPG is minimally influenced by hormonal and lifestyle factors among BRCA1 mutation carriers. IMPACT: These findings suggest that circulating OPG levels are not impacted by non-genetic factors in high-risk women.

Modelling a two-stream emergency department segregation and admission system from COVID-19 early rapid antigen testing: A pilot study.

OBJECTIVE: Many factors influence patient flow through an ED, including streaming, treatment spaces and staff resources. This pilot study explored and compared real time patient flow using a single-stream system versus varying configurations of possible two-stream systems using computer simulation. METHODS: Simulation modelling was used to assess the delay in treatment of a rapid-antigen-tested-based, two-stream model for patient flow through ED during the peak phase of the COVID pandemic. RESULTS: Modelling two-stream configuration for all patients (minimum time to be seen for both COVID-positive and COVID-negative patients) showed that in the case study ED, a two-stream system and linked changes in bed configuration for managing the risks of infection can impact delays in treatment. CONCLUSIONS: Data-driven modelling within specific clinical settings can inform the (in)efficiency of patient flow processes and help clinicians and managers make evidence-based decisions about patient transition through EDs. This can assist with reconfiguration of ED patient streaming particularly during periods of unique need, such as the recent COVID-19 pandemic.

The impact of sarcopenia on clinical outcomes in men with metastatic castrate-resistant prostate cancer.

INTRODUCTION: Sarcopenia is common in men with metastatic castrate-resistant prostate cancer (mCRPC) and has been largely assessed opportunistically through computed-tomography (CT) scans, excluding measures of muscle function. Therefore, the impact of a comprehensive assessment of sarcopenia on clinical outcomes in men with mCRPC is poorly understood. The objectives of this study were to comprehensively assess sarcopenia through CT scans and measures of muscle function and examine its impact on severe treatment toxicity, time to first emergency room (ER) visit, disease progression, and overall mortality in men initiating chemotherapy or androgen receptor-targeted axis (ARAT) therapy for mCRPC. METHODS: This was a secondary analysis of a prospective observational study of men with mCRPC at the Princess Margaret Cancer Centre between July 2015-May 2021. Participants were classified as sarcopenic if they had CT-based low muscle mass or low muscle density, a grip strength and gait speed score of <35.5kg and <0.8m/s, respectively, prior to treatment initiation. The impact of sarcopenia on severe treatment toxicity was assessed using multivariable logistic regression. Multivariable Cox regression models were used to determine the impact of sarcopenia on risk of visiting the ER, prostate-specific antigen progression, radiographic progression, and overall mortality. RESULTS: A total of 110 men (mean age: 74.6) were included in the analysis. At baseline, 30 (27.3%) were classified as sarcopenic. Sarcopenia was a significant predictor of severe toxicity (aOR = 6.26, 95%CI = 1.17-33.58, P = 0.032) and ER visits (aHR = 4.41, 95%CI = 1.26-15.43, p = 0.020) in men initiating ARAT but not in men initiating chemotherapy. Sarcopenia was also a predictor of radiographic progression (aHR = 2.39, 95%CI = 1.06-5.36, p = 0.035) and overall mortality (aHR = 2.44, 95%CI = 1.17-5.08, p = 0.018) regardless of treatment type. CONCLUSIONS: Baseline sarcopenia predicts radiographic progression and overall mortality in men with mCRPC regardless of the type of treatment and may also predict severe treatment toxicity and ER visits in men initiating ARAT.

A Fracture Risk Assessment Tool for High Resolution Peripheral Quantitative Computed Tomography.

Most fracture risk assessment tools use clinical risk factors combined with bone mineral density (BMD) to improve assessment of osteoporosis; however, stratifying fracture risk remains challenging. This study developed a fracture risk assessment tool that uses information about volumetric bone density and three-dimensional structure, obtained using high-resolution peripheral quantitative compute tomography (HR-pQCT), to provide an alternative approach for patient-specific assessment of fracture risk. Using an international prospective cohort of older adults (n = 6802) we developed a tool to predict osteoporotic fracture risk, called µFRAC. The model was constructed using random survival forests, and input predictors included HR-pQCT parameters summarizing BMD and microarchitecture alongside clinical risk factors (sex, age, height, weight, and prior adulthood fracture) and femoral neck areal BMD (FN aBMD). The performance of µFRAC was compared to the Fracture Risk Assessment Tool (FRAX) and a reference model built using FN aBMD and clinical covariates. µFRAC was predictive of osteoporotic fracture (c-index = 0.673, p < 0.001), modestly outperforming FRAX and FN aBMD models (c-index = 0.617 and 0.636, respectively). Removal of FN aBMD and all clinical risk factors, except age, from µFRAC did not significantly impact its performance when estimating 5-year and 10-year fracture risk. The performance of µFRAC improved when only major osteoporotic fractures were considered (c-index = 0.733, p < 0.001). We developed a personalized fracture risk assessment tool based on HR-pQCT that may provide an alternative approach to current clinical methods by leveraging direct measures of bone density and structure. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Single-cell RNA sequencing reveals maturation trajectory in human pluripotent stem cell-derived cardiomyocytes in engineered tissues.

Cardiac in vitro models have become increasingly obtainable and affordable with the optimization of human pluripotent stem cell-derived cardiomyocyte (hPSC-CM) differentiation. However, these CMs are immature compared to their in vivo counterparts. Here we study the cellular phenotype of hPSC-CMs by comparing their single-cell gene expression and functional profiles in three engineered cardiac tissue configurations: human ventricular (hv) cardiac anisotropic sheet, cardiac tissue strip, and cardiac organoid chamber (hvCOC), with spontaneously aggregated 3D cardiac spheroids (CS) as control. The CM maturity was found to increase with increasing levels of complexity of the engineered tissues from CS to hvCOC. The contractile components are the first function to mature, followed by electrophysiology and oxidative metabolism. Notably, the 2D tissue constructs show a higher cellular organization whereas metabolic maturity preferentially increases in the 3D constructs. We conclude that the tissue engineering models resembling configurations of native tissues may be reliable for drug screening or disease modeling.

Ankle flexor torque, size and density are differential determinants of distal tibia trabecular plate-rod morphometry and bone strength: The Ankle Quality Study.

HYPOTHESIS: Greater peak torque and higher myotendinous density at the ankle are associated with a more plate-like architecture at the distal tibia. METHODS: In this cross-sectional study, women and men ≥ 50 years old with no metal implants, reconstructive surgery, muscular dystrophies, or tendinopathies in any leg were recruited by convenience. Isometric ankle dorsi-plantar flexion and inversion-eversion peak torques were measured using dynamometry. HR-pQCT distal tibia scans were completed. Both assessments were completed on the same day on the non-dominant leg. Integral and trabecular vBMD were derived from standard analyses, failure load (FL) was obtained from finite element analysis, plate-specific parameters were computed from individual trabecula segmentation (ITS) analysis, myotendinous density (MyD) and volume fraction (MyV/TV) were computed from soft tissue analysis. pQCT scans of the 66 % mid-leg were performed (500 µm at 15 mm/s) to obtain muscle density (MD) and muscle cross-sectional area (MCSA). STATISTICAL ANALYSIS: General linear models estimated how ankle muscle group torque and muscle size and density differentially related, both separately and together, to whole-bone properties (integral vBMD, FL) and trabecular morphometry (ITS plate parameters). Models were adjusted for age, sex, BMI, use of glucocorticoids, current osteoarthritis, and participation in moderate to vigorous recreational or sport activities. RESULTS: Among 105 participants (77 % female, mean age: 63 (10) years, BMI: 25.8 (5.4) kg/m2, 25 % with OA, 17 % fracture history, 42 % falls history), all torque measures, particularly ankle dorsiflexion and eversion, were correlates of plate-plate/rod junction density and failure load. However, muscle size and density measures were further associated with vBMD. The effect of greater ankle flexor-extensor torque on more connected bone was stronger when MyD was higher (interaction p < 0.001). CONCLUSION: Strength of muscles around the ankle are correlates of plate-like trabeculae at the distal tibia, while leaner muscle and myotendinous tissues facilitates better quality bone for stronger ankle muscle torque.

Monthly Identification of High Frequency Emergency Presenters to Improve Care Delivery and Evaluation: A Unique Methodological Approach.

Background: Frequent presenters to emergency departments (EDs) pose many challenges around care delivery and health service management. The aim of this study was to investigate the presentation patterns of people with 5 or more ED visits in any calendar month (5+ frequent presenter [FP5+]) to develop a useful methodological framework on which the real impact of interventions may be assessed. Methods: This study is a retrospective analysis of de-identified frequent ED presentation data using segmented regression analysis of an interrupted time series (ITS). Results: A total of 82 FP5+ to this single ED were identified in a year. Of these presenters, 77% had 10 or more presentations in a year. The total FP5+ presentations in the 12 months preceding and after each participant's ≥5 presentations in 1 month (the trigger month for inclusion in the study) accounted for 1,064 and 1,606 visits, respectively. ITS analysis of frequent ED presentations did not show a significant level change or trend change during the data collection period. Monthly review of people who frequently present to a single ED showed that presentations typically occurred in bouts that may span calendar years. Presentation bouts then typically slow, potentially distorting evaluation of the effects of interventions. Conclusion: Rolling monthly examination of presentation data may facilitate timely case review and care delivery, as well as provide a holistic picture of the impacts of interventions targeting patient care needs. This unique analysis demands a reconsideration of the typical before-and-after analysis of interventions for this vulnerable and high-cost group of patients.

Stabilizing large pores in a flexible metal-organic framework via chemical cross-linking.

A barrier to the isoreticular expansion of flexible metal-organic frameworks is their complex breathing behavior, which can lead to pore closure upon solvent exchange and removal. Here we show that chemical cross-linking stabilizes the open form of a flexible aluminum framework with large 17 Å pores.

Validation of High-Resolution peripheral Quantitative Computed Tomography-Derived Achilles Tendon Properties Against Diagnostic Ultrasound.

OBJECTIVES: 1) To assess the precision of high resolution peripheral quantitative computed tomography (HR-pQCT)-derived Achilles tendon (AT) cross-sectional area (HR AT-CSA) and density, and 2) to validate HR AT-CSA against ultrasound-derived AT-CSA (US AT-CSA). METHODS: Women and men (≥50 years) had HR-pQCT (0.082mm isotropic) and US scans (B-mode) performed on the non-dominant ankle. Linear regression and Bland-Altman analyses assessed systematic differences between HR-pQCT and US-derived AT-CSA. Precision measured by % root mean square coefficients of variation (%RMSCV) and agreement by type 2,1 intraclass correlation coefficients (ICC2,1), were determined for test-retest US AT-CSA scans, and analysis-reanalysis of 30 HR-pQCT and US images. RESULTS: Among 44 participants, HR and US AT-CSA were strongly correlated (R2=0.84, p<0.01, B=1.05[0.90-1.19]), with no differences between modalities (p=0.37). Bland-Altman analysis revealed minimal systematic bias (-0.7mm2[-10.7-9.3]; 1.3%) between HR-pQCT and US-derived AT-CSA with smaller AT-CSA values showing larger inter-modality differences (R2=0.098, B=-0.137 [-0.268--0.008], p=0.039). US AT-CSA demonstrated excellent test-retest precision (ICC2,1=0.998, %RMSCV=1.04%). Analysis-reanalysis of HR-pQCT AT-density and both HR-pQCT and US AT-CSA displayed ICC2,1 above 0.95 and %RMSCV within 3%. CONCLUSION: HR-pQCT can examine AT-morphometry with acceptable analytical precision. Future studies should explore these metrics' association with functional outcomes and ankle-bone structural and mechanical properties.

Acute Flaccid Tetraparesis after COVID-19 Infection: Think of the Thyroid.

A previously well 32-year-old Chinese male presented with acute bilateral upper and lower limb paralysis upon waking, ten days after the onset of COVID-19 infection. Examination revealed areflexia over all four limbs, associated with reduced muscle strength, but no sensory or cranial nerve deficit. Initial concern was Guillain-Barre syndrome given the acute flaccid paralysis following COVID-19 infection. However, investigations revealed severe hypokalaemia (1.7 mmol/L) and primary hyperthyroidism. He was treated for thyrotoxic periodic paralysis (TPP) with ß-blockers, antithyroid medications, and intravenous potassium chloride (KCl). Despite frequent monitoring of potassium, rebound hyperkalaemia occurred with prompt resolution of paralysis.

Utilising a nurse navigator model of care to improve prisoner health care and reduce prisoner presentations to a tertiary emergency department.

BACKGROUND: Prisoners are a vulnerable population requiring complex care interventions in challenging environments, particularly around provision of emergency care. The aim of this study was to explore the effectiveness of a Nurse Navigator (NN) -led prisoner intervention from the perspective of the emergency department. METHODS: This study undertook a retrospective analysis of the prisoner presentations to a public emergency department. It used time-series analysis of publicly available deidentified data, collected during standard care evaluation, to explore the impact of this unique care model over 24 months (12-pre and 12-post). Synthesis of documents pertaining to this NN model of care provide a summary of key initiatives and interventions. RESULTS: With the introduction of NN, the rate of change of yearly prisoner presentations dropped from + 32.8% to - 2.7%. Interrupted time-series analysis on emergency department presentations per 1000 prisoners in custody confirmed a postintervention level drop of 15.1% (rate ratio 0.849; 95% CI 0.755-0.954) followed by a period of downward trending of presentations resulting in an absolute drop of 31.5% in twelve months (rate ratio 0.685; 95% CI 0.556-0.843). CONCLUSIONS: The bundle of capacity-building initiatives instigated by the NN appear to have contributed to a reduction of prisoner presentations.

Circulating microRNAs differentiate fast-progressing from slow-progressing and non-progressing knee osteoarthritis in the Osteoarthritis Initiative cohort.

Introduction: The objective of this study is to identify circulating microRNAs that distinguish fast-progressing radiographic knee osteoarthritis (OA) in the Osteoarthritis Initiative cohort by applying microRNA-sequencing. Methods: Participants with Kellgren-Lawrence (KL) grade 0/1 at baseline were included (N = 106). Fast-progressors were defined by an increase to KL 3/4 by 4-year follow-up (N = 20), whereas slow-progressors showed an increase to KL 2/3/4 only at 8-year follow-up (N = 35). Non-progressors remained at KL 0/1 by 8-year follow-up (N = 51). MicroRNA-sequencing was performed on plasma collected at baseline and 4-year follow-up from the same participants. Negative binomial models were fitted to identify differentially expressed (DE) microRNAs. Penalized logistic regression (PLR) analyses were performed to select combinations of DE microRNAs that distinguished fast-progressors. Area under the receiver operating characteristic curves (AUC) were constructed to evaluate predictive ability. Results: DE analyses revealed 48 microRNAs at baseline and 2 microRNAs at 4-year follow-up [false discovery rate (FDR) < 0.05] comparing fast-progressors with both slow-progressors and non-progressors. Among these were hsa-miR-320b, hsa-miR-320c, hsa-miR-320d, and hsa-miR-320e, which were predicted to target gene families, including members of the 14-3-3 gene family, involved in signal transduction. PLR models included miR-320 members as top predictors of fast-progressors and yielded AUC ranging from 82.6 to 91.9, representing good accuracy. Conclusion: The miR-320 family is associated with fast-progressing radiographic knee OA and merits further investigation as potential biomarkers and mechanistic drivers of knee OA.

Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk.

Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a "one-size-fits-all" approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).

Retrospective identification of latent subgroups of emergency department patients: A machine learning approach.

OBJECTIVE: This research aims to (i) identify latent subgroups of ED presentations in Australian public EDs using a data-driven approach and (ii) compare clinical, socio-demographic and time-related characteristics of ED presentations broadly using the subgroups. METHODS: We examined presentations to four public hospital EDs in Queensland from 2009 to 2014. An unsupervised machine learning algorithm, Clustering Large Applications, was used to cluster ED presentations. RESULTS: There were six subgroups common across the EDs, primarily distinguishable by age, and subsequently by triage category, ED length of stay, arrival mode, departure status and several time-related attributes. Around 10% to 30% of the total presentations had high resource utilisation, with half of these from older patients (55+ years). ED resource utilisation per population was highest among the oldest cohort (75+ years). Children and young adults more frequently presented to the ED outside general-practitioner hours, mostly on Sundays. Older persons were more likely to present at any time, rather than specific hours, days or seasons. ED service performance measured against commonly used access-target indicators were rarely satisfied for older people and frequently satisfied for children. CONCLUSION: Clustering Large Applications is effective in finding latent groups in large-scale mixed-type data, as demonstrated in the present study. Six types of ED presentations were identified and described using clinically relevant characteristics. The present study provides evidence for policy makers in Australia to develop alternative ED models of care tailored around the care needs of the differing groups of patients and thereby supports the sustainable delivery of acute healthcare.