Simplified clinical frailty scale design, validation, and adaptation in older patients.

OBJECTIVE: The clinical frailty scale (CFS) evaluates the level of frailty based on clinical examination, comorbidities, and functional and activity levels of older patients. However, there are many difficulties for internists in evaluating frailty with this scale. Therefore, simplifying the CFS with good design and application is required for better treatment outcomes. Our study was conducted to design and evaluate the correlation of a simplified clinical frailty scale (sCFS) with CFS in older patients. PATIENTS AND METHODS: We undertook a cross-sectional analysis involving 279 older patients, which comprised two steps. Step 1 involves the implementation of sCFS, a protocol that has been endorsed by the Geriatrics Professional Council (GPC). Step 2 entails the enrollment of older patients for frailty assessment using sCFS, comparing it with CFS. RESULTS: The study was conducted on 279 older patients; the average age was 75.7 ± 8.4 (years old), and men accounted for 34.8%. There was a high correlation between the sCFS and CFS (Pearson's r = 0.996; p < 0.001). The similarity of the sCFS to the CFS was very high, with Kappa coefficient = 0.984 (p < 0.001). Compared with the CFS, the sCFS had a Youden index of 98% with 100% sensitivity and 98% specificity assessed through the receiver operating characteristic (ROC) with the CFS threshold of 5. CONCLUSIONS: The sCFS can be used to assess frailty with high sensitivity and specificity.

Clinical and technical factors in endoscopic skull base surgery associated with reconstructive success.

BACKGROUND: In this study, we identified key discrete clinical and technical factors that may correlate with primary reconstructive success in endoscopic skull base surgery (ESBS). METHODS: ESBS cases with intraoperative cerebrospinal fluid (CSF) leaks at four tertiary academic rhinology programs were retrospectively reviewed. Logistic regression identified factors associated with surgical outcomes by defect subsite (anterior cranial fossa [ACF], suprasellar [SS], purely sellar, posterior cranial fossa [PCF]). RESULTS: Of 706 patients (50.4% female), 61.9% had pituitary adenomas, 73.4% had sellar or SS defects, and 20.5% had high-flow intraoperative CSF leaks. The postoperative CSF leak rate was 7.8%. Larger defect size predicted ACF postoperative leaks; use of rigid reconstruction and older age protected against sellar postoperative leaks; and use of dural sealants compared to fibrin glue protected against PCF postoperative leaks. SS postoperative leaks occurred less frequently with the use of dural onlay. Body-mass index, intraoperative CSF leak flow rate, and the use of lumbar drain were not significantly associated with postoperative CSF leak. Meningitis was associated with larger tumors in ACF defects, nondissolvable nasal packing in SS defects, and high-flow intraoperative leaks in PCF defects. Sinus infections were more common in sellar defects with synthetic grafts and nondissolvable nasal packing. CONCLUSIONS: Depending on defect subsite, reconstructive success following ESBS may be influenced by factors, such as age, defect size, and the use of rigid reconstruction, dural onlay, and tissue sealants.

Efficient automated error detection in medical data using deep-learning and label-clustering.

Medical datasets inherently contain errors from subjective or inaccurate test results, or from confounding biological complexities. It is difficult for medical experts to detect these elusive errors manually, due to lack of contextual information, limiting data privacy regulations, and the sheer scale of data to be reviewed. Current methods for training robust artificial intelligence (AI) models on data containing mislabeled examples generally fall into one of several categories-attempting to improve the robustness of the model architecture, the regularization techniques used, the loss function used during training, or selecting a subset of data that contains cleaner labels. This last category requires the ability to efficiently detect errors either prior to or during training, either relabeling them or removing them completely. More recent progress in error detection has focused on using multi-network learning to minimize deleterious effects of errors on training, however, using many neural networks to reach a consensus on which data should be removed can be computationally intensive and inefficient. In this work, a deep-learning based algorithm was used in conjunction with a label-clustering approach to automate error detection. For dataset with synthetic label flips added, these errors were identified with an accuracy of up to 85%, while requiring up to 93% less computing resources to complete compared to a previous model consensus approach developed previously. The resulting trained AI models exhibited greater training stability and up to a 45% improvement in accuracy, from 69 to over 99% compared to the consensus approach, at least 10% improvement on using noise-robust loss functions in a binary classification problem, and a 51% improvement for multi-class classification. These results indicate that practical, automated a priori detection of errors in medical data is possible, without human oversight.

Vitrified before and after genome editing via electroporation.

BACKGROUND: Cryopreservation of bovine zygotes allows for a flexible schedule of genome editing via electroporation. However, vitrification-induced cell membrane damage may not only affect embryonic development but also genome mutation. OBJECTIVE: To investigate the effects of vitrification of zygotes before and after electroporation treatments on the development and genome mutation of bovine presumptive zygotes. MATERIALS AND METHODS: In vitro-derived bovine zygotes were electroporated with the CRISPR/Cas9 system immediately (Vitrified-EP) or 2 h after incubation (Vitrified-2h-EP) following vitrification and warming, or electroporated before vitrification (EP-vitrified). RESULTS: The development rates of vitrified-warmed zygotes were significantly lower (p < 0.05) than those of control zygotes that were not vitrified. Moreover, no differences were observed in the mutation rates and mutation efficiency of the blastocysts resulting from electroporated zygotes, irrespective of the timing of electroporation treatment. CONCLUSION: Our results suggest that vitrification before and after electroporation treatments does not affect the genome editing of zygotes.

Bioaccumulation and metabolic impact of environmental PFAS residue on wild-caught urban wetland tiger snakes (Notechis scutatus).

PFAS contamination of urban waters is widespread but understanding the biological impact of its accumulation is limited to humans and common ecotoxicological model organisms. Here, we combine PFAS exposure and bioaccumulation patterns with whole organism responses and omics-based ecosurveillance methods to investigate the potential impacts of PFAS on a top predator of wetlands, the tiger snake (Notechis scutatus). Tiger snakes (18 male and 17 female) were collected from four wetlands with varying PFAS chemical profiles and concentrations in Perth, Western Australia. Tiger snake livers were tested for 28 known PFAS compounds, and Σ28PFAS in liver tissues ranged between 322 ± 193 µg/kg at the most contaminated site to 1.31 ± 0.86 µg/kg at the least contaminated site. The dominant PFAS compound detected in liver tissues was PFOS. Lower body condition was associated with higher liver PFAS, and male snakes showed signs of high bioaccumulation whereas females showed signs of maternal offloading. Biochemical profiles of snake muscle, fat (adipose tissue), and gonads were analysed using a combination of liquid chromatography triple quadrupole (QqQ) and quadrupole time-of-flight (QToF) mass spectrometry methodologies. Elevated PFAS was associated with enriched energy production and maintenance pathways in the muscle, and had weak associations with energy-related lipids in the fat tissue, and lipids associated with cellular genesis and spermatogenesis in the gonads. These findings demonstrate the bioavailability of urban wetland PFAS in higher-order reptilian predators and suggest a negative impact on snake health and metabolic processes. This research expands on omics-based ecosurveillance tools for informing mechanistic toxicology and contributes to our understanding of the impact of PFAS residue on wildlife health to improve risk management and regulation.

The effect of medication event reminder monitoring on treatment adherence of TB patients.

BACKGROUND: TB control remains a serious public health problem, compounded by poor treatment adherence, which increases the likelihood of onward transmission. We evaluated the effectiveness of medication event reminder monitoring (MERM) upon treatment adherence in a high TB burden setting.METHODS: We conducted an open-label parallel group randomised controlled trial among pulmonary TB adults. Participants were provided with a MERM device to store their medications. In the intervention arm, the devices were set to provide daily medication intake reminders. Primary outcome was the proportion of patient-months in which at least 6/30 doses were missed. Secondary outcomes included 1) the proportion of patient-months in which at least 14/30 doses were missed, and 2) the proportion of doses missed.RESULTS: Of 2,142 patients screened, 798 (37.3%) met the inclusion criteria and 250 participants were enrolled. The mean ratio (MR) for poor adherence between the intervention and control groups was 0.72 (95% CI 0.55-0.86). The intervention was also associated with a reduction in the proportion of patients missing at least 14/30 doses (MR 0.61, 95% CI 0.54-0.68) and the percentage of total doses missed (MR 0.75, 95% CI 0.68-0.80).CONCLUSION: MERM is effective in improving TB treatment adherence in a resource-limited environment.

Sinus arrest in familial hypokalemic periodic paralysis caused by SCN4A mutation: a case report.

BACKGROUND: Primary hypokalemic periodic paralysis (HypoPP), a rare skeletal muscle channelopathy resulting in episodic muscle weakness or paralysis under hypokalemic conditions, is caused by autosomal-dominant genetic mutations. HypoPP limits physical activity, and cardiac arrhythmias during paralytic attacks have been reported. We describe a rare familial HypoPP case complicated by sinus arrest and syncope requiring urgent temporary pacemaker implantation. CASE REPORT: A 27-year-old Vietnamese man with a family history of periodic paralysis presented with his third attack of muscle weakness triggered by intense football training the previous day. Clinical and laboratory features justified a HypoPP diagnosis. During intravenous potassium replacement, the patient experienced syncopal sinus arrest requiring urgent temporary pacemaker implantation. The patient gradually improved, responding favorably to oral potassium supplements. Genetic testing revealed an Arg1132Gln mutation in the sodium ion channel (SCN4A, chromosome 17: 63947091). At discharge, the patient received expert consultation regarding nonpharmacological preventive strategies, including avoidance of vigorous exercise and carbohydrate-rich diet. CONCLUSIONS: No evidence has established a relationship between hypokalemia and sinus arrest, and no specific treatment exists for familial HypoPP due to SCN4A mutation. Clinician awareness of this rare condition will promote appropriate diagnostic approaches and management strategies for acute paralytic attacks. Treatment should be tailored according to HypoPP phenotypes and genotypes.

Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF.

STUDY QUESTION: Can an artificial intelligence (AI) model predict human embryo ploidy status using static images captured by optical light microscopy? SUMMARY ANSWER: Results demonstrated predictive accuracy for embryo euploidy and showed a significant correlation between AI score and euploidy rate, based on assessment of images of blastocysts at Day 5 after IVF. WHAT IS KNOWN ALREADY: Euploid embryos displaying the normal human chromosomal complement of 46 chromosomes are preferentially selected for transfer over aneuploid embryos (abnormal complement), as they are associated with improved clinical outcomes. Currently, evaluation of embryo genetic status is most commonly performed by preimplantation genetic testing for aneuploidy (PGT-A), which involves embryo biopsy and genetic testing. The potential for embryo damage during biopsy, and the non-uniform nature of aneuploid cells in mosaic embryos, has prompted investigation of additional, non-invasive, whole embryo methods for evaluation of embryo genetic status. STUDY DESIGN, SIZE, DURATION: A total of 15 192 blastocyst-stage embryo images with associated clinical outcomes were provided by 10 different IVF clinics in the USA, India, Spain and Malaysia. The majority of data were retrospective, with two additional prospectively collected blind datasets provided by IVF clinics using the genetics AI model in clinical practice. Of these images, a total of 5050 images of embryos on Day 5 of in vitro culture were used for the development of the AI model. These Day 5 images were provided for 2438 consecutively treated women who had undergone IVF procedures in the USA between 2011 and 2020. The remaining images were used for evaluation of performance in different settings, or otherwise excluded for not matching the inclusion criteria. PARTICIPANTS/MATERIALS, SETTING, METHODS: The genetics AI model was trained using static 2-dimensional optical light microscope images of Day 5 blastocysts with linked genetic metadata obtained from PGT-A. The endpoint was ploidy status (euploid or aneuploid) based on PGT-A results. Predictive accuracy was determined by evaluating sensitivity (correct prediction of euploid), specificity (correct prediction of aneuploid) and overall accuracy. The Matthew correlation coefficient and receiver-operating characteristic curves and precision-recall curves (including AUC values), were also determined. Performance was also evaluated using correlation analyses and simulated cohort studies to evaluate ranking ability for euploid enrichment. MAIN RESULTS AND THE ROLE OF CHANCE: Overall accuracy for the prediction of euploidy on a blind test dataset was 65.3%, with a sensitivity of 74.6%. When the blind test dataset was cleansed of poor quality and mislabeled images, overall accuracy increased to 77.4%. This performance may be relevant to clinical situations where confounding factors, such as variability in PGT-A testing, have been accounted for. There was a significant positive correlation between AI score and the proportion of euploid embryos, with very high scoring embryos (9.0-10.0) twice as likely to be euploid than the lowest-scoring embryos (0.0-2.4). When using the genetics AI model to rank embryos in a cohort, the probability of the top-ranked embryo being euploid was 82.4%, which was 26.4% more effective than using random ranking, and ∼13-19% more effective than using the Gardner score. The probability increased to 97.0% when considering the likelihood of one of the top two ranked embryos being euploid, and the probability of both top two ranked embryos being euploid was 66.4%. Additional analyses showed that the AI model generalized well to different patient demographics and could also be used for the evaluation of Day 6 embryos and for images taken using multiple time-lapse systems. Results suggested that the AI model could potentially be used to differentiate mosaic embryos based on the level of mosaicism. LIMITATIONS, REASONS FOR CAUTION: While the current investigation was performed using both retrospectively and prospectively collected data, it will be important to continue to evaluate real-world use of the genetics AI model. The endpoint described was euploidy based on the clinical outcome of PGT-A results only, so predictive accuracy for genetic status in utero or at birth was not evaluated. Rebiopsy studies of embryos using a range of PGT-A methods indicated a degree of variability in PGT-A results, which must be considered when interpreting the performance of the AI model. WIDER IMPLICATIONS OF THE FINDINGS: These findings collectively support the use of this genetics AI model for the evaluation of embryo ploidy status in a clinical setting. Results can be used to aid in prioritizing and enriching for embryos that are likely to be euploid for multiple clinical purposes, including selection for transfer in the absence of alternative genetic testing methods, selection for cryopreservation for future use or selection for further confirmatory PGT-A testing, as required. STUDY FUNDING/COMPETING INTEREST(S): Life Whisperer Diagnostics is a wholly owned subsidiary of the parent company, Presagen Holdings Pty Ltd. Funding for the study was provided by Presagen with grant funding received from the South Australian Government: Research, Commercialisation, and Startup Fund (RCSF). 'In kind' support and embryology expertise to guide algorithm development were provided by Ovation Fertility. 'In kind' support in terms of computational resources provided through the Amazon Web Services (AWS) Activate Program. J.M.M.H., D.P. and M.P. are co-owners of Life Whisperer and Presagen. S.M.D., M.A.D. and T.V.N. are employees or former employees of Life Whisperer. S.M.D, J.M.M.H, M.A.D, T.V.N., D.P. and M.P. are listed as inventors of patents relating to this work, and also have stock options in the parent company Presagen. M.V. sits on the advisory board for the global distributor of the technology described in this study and also received support for attending meetings. TRIAL REGISTRATION NUMBER: N/A.

A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data.

Training on multiple diverse data sources is critical to ensure unbiased and generalizable AI. In healthcare, data privacy laws prohibit data from being moved outside the country of origin, preventing global medical datasets being centralized for AI training. Data-centric, cross-silo federated learning represents a pathway forward for training on distributed medical datasets. Existing approaches typically require updates to a training model to be transferred to a central server, potentially breaching data privacy laws unless the updates are sufficiently disguised or abstracted to prevent reconstruction of the dataset. Here we present a completely decentralized federated learning approach, using knowledge distillation, ensuring data privacy and protection. Each node operates independently without needing to access external data. AI accuracy using this approach is found to be comparable to centralized training, and when nodes comprise poor-quality data, which is common in healthcare, AI accuracy can exceed the performance of traditional centralized training.

New trematode species Lecithostaphylus halongi n. sp. (Zoogonidae, Microphalloidea) and Gymnotergestia strongyluri n. sp. (Fellodistomidae, Gymnophalloidea) from beloniform fishes in Vietnam.

In this study we described two new trematode species, Lecithostaphylus halongi n. sp. (Zoogonidae, Lecithostaphylinae) and Gymnotergestia strongyluri n. sp. (Fellodistomidae, Tergestiinae), on the basis of morphological and molecular data. Adult worms of these two species were collected from, respectively, Hemiramphus spp. (Hemiramphidae) and Strongylura strongylura (Belonidae) caught in the coastal waters of Vietnam. Adult worms of L. halongi n. sp. are morphologically close to Lecithostaphylus gibsoni Cribb, Bray & Barker, 1992 ex Abudefduf whitleyi from Heron Island and Lecithostaphylus depauperati Yamaguti, 1970 ex Hemiramphus depauperatus from Hawaii, but differ from these species in having a larger cirrus sac and a different arrangement of vitelline fields. They also differ from Lecithostaphylus brayi Cabañas-Granillo, Solórzano-García, Mendoza-Garfias & Pérez-Ponce de León, 2020 in the 28S ribosomal DNA (rDNA) sequence data at the interspecific level. Adult worms of G. strongyluri n. sp. ex S. strongylura are morphologically similar to Gymnotergestia chaetodipteri, the only previously known species of this genus, described from Chaetodipterus faber in Jamaica. The new species differs from G. chaetodipteri in body shape, testicular arrangement and the size of the pharynx and eggs. The 28S rDNA-based phylogenetic analysis indicates that G. strongyluri n. sp. is closely related to Tergestia spp., rendering Tergestia paraphyletic. Genetic divergence values between G. strongyluri n. sp. and Tergestia spp. are similar to those among species in the genera Tergestia, Steringophorus and Proctoeces. Our molecular results indicate that G. strongyluri n. sp. and Tergestia spp. may belong the same genus, but additional molecular data are needed for the final conclusion.

Predictive performance of the Garvan Fracture Risk Calculator: a registry-based cohort study.

The G arvan Fracture Risk Calculator predicts risk of osteoporotic fractures. We evaluated its predictive performance in 16,682 women and 2839 men from Manitoba, Canada, and found significant risk stratification, with a strong gradient across scores. The tool outperformed clinical risk factors and bone mineral density for fracture risk stratification. INTRODUCTION: The optimal model for fracture risk estimation to guide treatment decision-making remains controversial. Our objective was to evaluate the predictive performance of the Garvan Fracture Risk Calculator (FRC) in a large clinical registry from Manitoba, Canada. METHODS: Using the population-based Manitoba Bone Mineral Density (BMD) registry, we identified women and men aged 50-95 years undergoing baseline BMD assessment from September 1, 2012, onwards. Five-year Garvan FRC predictions were generated from clinical risk factors (CRFs) with and without femoral neck BMD. We identified incident non-traumatic osteoporotic fractures (OFs) and hip fractures (HFs) from population-based healthcare data sources to March 31, 2018. Fracture risk was assessed from area under the receiver operating characteristic curve (AUROC). Cox regression analysis and calibration ratios (5-year observed/predicted) were assessed for risk quintiles. All analyses were sex stratified. RESULTS: We included 16,682 women (mean age 66.6 + / - SD 8.7 years) and 2839 men (mean age 68.7 + / - SD 10.2 years). During a mean observation time of 2.6 years, incident OFs were identified in 681 women and 140 men and HFs in 199 women and 22 men. AUROC showed significant fracture risk stratification with the Garvan FRC. Tool predictions without BMD were better than from age or decreasing weight, and the tool with BMD performed better than BMD alone. Garvan FRC with BMD performed better than without BMD, especially for HF prediction (AUROC 0.86 in women, 0.82 in men). There was a strong gradient of increasing risk across Garvan FRC quintiles (highest versus lowest, hazard ratios women 5.75 and men 3.43 for any OF; women 101.6 for HF). Calibration differences were noted, with both over- and underestimation in risk. CONCLUSIONS: Garvan FRC outperformed CRFs and BMD alone for fracture risk stratification, particularly for HF, but may require recalibration for accurate predictions in this population.

Automated detection of poor-quality data: case studies in healthcare.

The detection and removal of poor-quality data in a training set is crucial to achieve high-performing AI models. In healthcare, data can be inherently poor-quality due to uncertainty or subjectivity, but as is often the case, the requirement for data privacy restricts AI practitioners from accessing raw training data, meaning manual visual verification of private patient data is not possible. Here we describe a novel method for automated identification of poor-quality data, called Untrainable Data Cleansing. This method is shown to have numerous benefits including protection of private patient data; improvement in AI generalizability; reduction in time, cost, and data needed for training; all while offering a truer reporting of AI performance itself. Additionally, results show that Untrainable Data Cleansing could be useful as a triage tool to identify difficult clinical cases that may warrant in-depth evaluation or additional testing to support a diagnosis.

Development and validation of the risk engine for an Australian Health Economics Model of Osteoporosis.

The Australian Health Economics Model of Osteoporosis (AusHEMO) has shown good face, internal and cross validities, and can be used to assist healthcare decision-making in Australia. PURPOSE: This study aimed to document and validate the risk engine of the Australian Health Economics Model of Osteoporosis (AusHEMO). METHODS: AusHEMO is a state-transition microsimulation model. The fracture risks were simulated using fracture incidence rates from the Dubbo Osteoporosis Epidemiology Study. The AusHEMO was validated regarding its face, internal and cross validities. Goodness-of-fit analysis was conducted and Lin's coefficient of agreement and mean absolute difference with 95% limits of agreement were reported. RESULTS: The development of AusHEMO followed general and osteoporosis-specific health economics guidelines. AusHEMO showed good face validity regarding the model's structure, evidence, problem formulation and results. In addition, the model has been proven good internal and cross validities in goodness-of-fit test. Lin's coefficient was 0.99, 1 and 0.94 for validation against the fracture incidence rates, Australian life expectancies and residual lifetime fracture risks, respectively. CONCLUSIONS: In summary, the development of the risk engine of AusHEMO followed the best practice for osteoporosis disease modelling and the model has been shown to have good face, internal and cross validities. The AusHEMO can be confidently used to predict long-term fracture-related outcomes and health economic evaluations when costs data are included. Health policy-makers in Australia can use the AusHEMO to select which osteoporosis interventions such as medications and public health interventions represent good value for money.

Development of the Asia Pacific Consortium on Osteoporosis (APCO) Framework: clinical standards of care for the screening, diagnosis, and management of osteoporosis in the Asia-Pacific region.

Guidelines for doctors managing osteoporosis in the Asia-Pacific region vary widely. We compared 18 guidelines for similarities and differences in five key areas. We then used a structured consensus process to develop clinical standards of care for the diagnosis and management of osteoporosis and for improving the quality of care. PURPOSE: Minimum clinical standards for assessment and management of osteoporosis are needed in the Asia-Pacific (AP) region to inform clinical practice guidelines (CPGs) and to improve osteoporosis care. We present the framework of these clinical standards and describe its development. METHODS: We conducted a structured comparative analysis of existing CPGs in the AP region using a "5IQ" model (identification, investigation, information, intervention, integration, and quality). One-hundred data elements were extracted from each guideline. We then employed a four-round Delphi consensus process to structure the framework, identify key components of guidance, and develop clinical care standards. RESULTS: Eighteen guidelines were included. The 5IQ analysis demonstrated marked heterogeneity, notably in guidance on risk factors, the use of biochemical markers, self-care information for patients, indications for osteoporosis treatment, use of fracture risk assessment tools, and protocols for monitoring treatment. There was minimal guidance on long-term management plans or on strategies and systems for clinical quality improvement. Twenty-nine APCO members participated in the Delphi process, resulting in consensus on 16 clinical standards, with levels of attainment defined for those on identification and investigation of fragility fractures, vertebral fracture assessment, and inclusion of quality metrics in guidelines. CONCLUSION: The 5IQ analysis confirmed previous anecdotal observations of marked heterogeneity of osteoporosis clinical guidelines in the AP region. The Framework provides practical, clear, and feasible recommendations for osteoporosis care and can be adapted for use in other such vastly diverse regions. Implementation of the standards is expected to significantly lessen the global burden of osteoporosis.

Hidradenitis suppurativa: an update on epidemiology, phenotypes, diagnosis, pathogenesis, comorbidities and quality of life.

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease that severely impairs patients' quality of life. It is characterized by recurrent painful nodules, abscesses and draining sinus tracts in primarily intertriginous areas. We aimed to review the most up-to-date information regarding the epidemiology, clinical presentation, diagnostic studies, pathogenesis, comorbidities and quality of life of patients with hidradenitis suppurativa. We performed a systematic search of Medline, Embase database (from inception to September 2019) and review of bibliographies without restrictions on year or language. HS has an estimated global prevalence of 0.00033-4.1% (but most likely 0.7-1.2% in the European-US population). Patients still experience a significant diagnostic delay, up to several years. In the absence of pathognomonic tests, the diagnosis of HS is made from clinical observation and the disease narrative. Phenotypic variation renders diagnosis and severity assessment difficult. Ultrasound imaging is an emerging assessment tool for deep-seated lesions. The Hurley Staging System is still widely used in severity rating. Follicular hyperkeratosis and dilatation, follicular rupture and chronic inflammation with architectural tissue changes have been implicated in the pathogenesis of HS. HS has been associated with metabolic syndrome and other risk factors for cardiovascular disease, diabetes mellitus type II, polycystic ovarian syndrome, depression, suicide and substance use disorders. It has been linked to other immune-mediated diseases such as inflammatory bowel disease and spondyloarthropathy. Pain, pruritus, malodour, low self-esteem, sleep and sexual dysfunctions, and poor mental health are chronic symptoms or consequences of uncontrolled disease. HS is an under-diagnosed and under-treated disease with a profound negative impact on patients' quality of life. In the light of its associated comorbidities, an interdisciplinary management approach may be needed to ensure the best outcomes.

Assessing the clinical utility of genetic profiling in fracture risk prediction: a decision curve analysis.

Using decision curve analysis on 2188 women and 1324 men, we found that an osteogenomic profile constructed from 62 genetic variants improved the clinical net benefit of fracture risk prediction over and above that of clinical risk factors and BMD. INTRODUCTION: Genetic profiling is a promising tool for assessing fracture risk. This study sought to use the decision curve analysis (DCA), a novel approach to determine the impact of genetic profiling on fracture risk prediction. METHODS: The study involved 2188 women and 1324 men, aged 60 years and above, who were followed for up to 23 years. Bone mineral density (BMD) and clinical risk factors were obtained at baseline. The incidence of fracture and mortality were recorded. A weighted individual genetic risk score (GRS) was constructed from 62 BMD-associated genetic variants. Four models were considered: CRF (clinical risk factors); CRF + GRS; Garvan model (GFRC) including CRF and femoral neck BMD; and GFRC + GRS. The DCA was used to evaluate the clinical net benefit of predictive models at a range of clinically reasonable risk thresholds. RESULTS: In both women and men, the full model GFRC + GRS achieved the highest net benefits. For 10-year risk threshold > 18% for women and > 15% for men, the GRS provided net benefit above those of the CRF models. At 20% risk threshold, adding the GRS could help to avoid 1 additional treatment per 81 women or 1 per 24 men compared with the Garvan model. At lower risk thresholds, there was no significant difference between the four models. CONCLUSIONS: The addition of genetic profiling into the clinical risk factors can improve the net clinical benefit at higher risk thresholds of fracture. Although the contribution of genetic profiling was modest in the presence of BMD + CRF, it appeared to be able to replace BMD for fracture prediction.

Radiation therapy on primary tumour of synchronous metastatic head and neck squamous cell carcinomas.

PURPOSE: Patients with synchronous metastatic head and neck squamous cell carcinomas often present associated locoregional symptoms and a risk of life-threatening primary tumour progression. Few data have been published about the use of radiation therapy in the management of newly diagnosed metastatic disease associated with advanced locoregional disease. In this article, we aim to determine the role of radiation therapy of the primary tumour in the overall therapeutic strategy for these diseases. We further address radiation therapy modalities (technique, volumes, and fractionation) in such a context. MATERIAL AND METHODS: We conducted a literature survey on locoregional radiotherapy for newly diagnosed metastatic head and neck squamous cell carcinomas. RESULTS: Several retrospective studies have reported that locoregional radiotherapy is associated with improved overall survival of patients with synchronous metastatic head and neck squamous cell carcinomas. However, data about modalities such as timing of radiotherapy in the overall strategy, dose, fractionation and delineation volumes are scarce. Two schematic situations can be distinguished with respect to prognosis and treatment adaptations: polymetastatic/bulky or oligometastatic disease. In polymetastic/bulky disease associated with poor prognosis, standard-of-care is systemic therapy, but locoregional radiotherapy can be discussed either upfront, mainly for symptomatic palliation, or as consolidation after downsizing obtained by systemic therapy. As for oligometastatic disease, with the rise in use of efficacious and well-tolerated local ablative treatments of metastases, aggressive curative-intent locoregional radiotherapy can be considered with or without systemic therapy. CONCLUSION: Because locoregional disease is a major cause of disease failure in patients with synchronous metastatic head and neck squamous cell carcinomas, aggressive locoregional radiation therapy to the primary tumour may be discussed in the initial management of the disease where systemic therapy alone may not induce sufficient primary tumour reduction. With recent technological advances in radiotherapy, the delivery of radiotherapy is safe and feasible even in metastatic setting. Clinical trials assessing radiotherapy use for metastatic head and neck squamous cell carcinomas are warranted.

IQ driving QI: the Asia Pacific Consortium on Osteoporosis (APCO): an innovative and collaborative initiative to improve osteoporosis care in the Asia Pacific.

Asia Pacific Consortium on Osteoporosis (APCO) comprises of clinical experts from across the Asia Pacific region, uniting to develop solutions to problems facing osteoporosis management and care. The vision of APCO is to reduce the burden of osteoporosis and fragility fractures in the Asia Pacific region. INTRODUCTION: The Asia Pacific (AP) region comprises 71 countries with vastly different healthcare systems. It is predicted that by 2050, more than half the world's hip fractures will occur in this region. The Asia Pacific Consortium on Osteoporosis (APCO) was set up in May 2019 with the vision of reducing the burden of osteoporosis and fragility fractures in the AP region. METHODS: APCO has so far brought together 39 clinical experts from countries and regions across the AP to develop solutions to challenges facing osteoporosis management and fracture prevention in this highly populous region of the world. APCO aims to achieve its vision by engaging with relevant stakeholders including healthcare providers, policy makers and the public. The initial APCO project is to develop and implement a Framework of pan-AP minimum clinical standards for the screening, diagnosis and management of osteoporosis. RESULTS AND CONCLUSIONS: The Framework will serve as a platform upon which new national clinical guidelines can be developed or existing guidelines be revised, in a standardised fashion. The Framework will also facilitate benchmarking for provision of quality of care. It is hoped that the principles underlying the formation and functioning of APCO can be adopted by other regions and that every health care facility and progressively every country in the world can follow our aspirational path and progress towards best practice.