A Second Space Age Spanning Omics, Platforms, and Medicine Across Orbits.

The recent acceleration of commercial, private, and multi-national spaceflight has created an unprecedented level of activity in low Earth orbit (LEO), concomitant with the highest-ever number of crewed missions entering space and preparations for exploration-class (>1 year) missions. Such rapid advancement into space from many new companies, countries, and space-related entities has enabled a"Second Space Age." This new era is also poised to leverage, for the first time, modern tools and methods of molecular biology and precision medicine, thus enabling precision aerospace medicine for the crews. The applications of these biomedical technologies and algorithms are diverse, encompassing multi-omic, single-cell, and spatial biology tools to investigate human and microbial responses to spaceflight. Additionally, they extend to the development of new imaging techniques, real-time cognitive assessments, physiological monitoring, and personalized risk profiles tailored for astronauts. Furthermore, these technologies enable advancements in pharmacogenomics (PGx), as well as the identification of novel spaceflight biomarkers and the development of corresponding countermeasures. In this review, we highlight some of the recent biomedical research from the National Aeronautics and Space Administration (NASA), Japan Aerospace Exploration Agency (JAXA), European Space Agency (ESA), and other space agencies, and also detail the commercial spaceflight sector's (e.g. SpaceX, Blue Origin, Axiom, Sierra Space) entrance into aerospace medicine and space biology, the first aerospace medicine biobank, and the myriad upcoming missions that will utilize these tools to ensure a permanent human presence beyond LEO, venturing out to other planets and moons.

DERIVATION AND VALIDATION OF A MACHINE LEARNING MODEL FOR THE PREVENTION OF UNPLANNED DIALYSIS.

BACKGROUND: Approximately half of all patients with advanced chronic kidney disease (CKD) who progress to kidney failure initiate dialysis in an unplanned fashion which is associated with high morbidity, mortality, and healthcare costs. A novel prediction model designed to identify advanced CKD patients who are at high risk for developing kidney failure over short time frames (6-12 months) may help reduce the rates of unplanned dialysis and improve the quality of transitions from CKD to kidney failure. METHODS: We performed a retrospective study employing machine learning random forest algorithms incorporating routinely collected age and sex data along with time-varying trends in laboratory measurements to derive and validate six- and 12-month kidney failure risk prediction models in the advanced CKD population. The models were comprehensively characterized in three independent cohorts in Ontario, Canada - derived in a cohort of 1,849 consecutive advanced CKD patients (mean [standard deviation] age 66 [15] years, eGFR 19 [7] mL/min/1.73m2), and validated in two external advanced CKD cohorts (n=1,356; age 69 [14] years, eGFR 22 [7] mL/min/1.73m2). RESULTS: Across all cohorts, 55% of patients experienced kidney failure, of which 35% involved unplanned dialysis. The six- and 12-month models demonstrated excellent discrimination with area under the receiver operating characteristic curve of 0.88 (95%CI: 0.87-0.89) and 0.87 (95%CI: 0.86-0.87) along with high probabilistic accuracy with Brier scores of 0.10 (95%CI 0.09-0.10) and 0.14 (95%CI 0.13-0.14), respectively. The models were also well-calibrated and delivered timely alerts on a significant number of patients who ultimately initiated dialysis in an unplanned fashion. Similar results were found upon external validation testing. CONCLUSION: These machine-learning models using routinely collected patient data accurately predict near-future kidney failure risk among the advanced CKD population, and retrospectively deliver advanced warning on a substantial proportion of unplanned dialysis events. Optimal implementation strategies still need to be elucidated.

Demystifying Open Science in health psychology and behavioral medicine: a practical guide to Registered Reports and Data Notes.

Open Science practices are integral to increasing transparency, reproducibility, and accessibility of research in health psychology and behavioral medicine. Drives to facilitate Open Science practices are becoming increasingly evident in journal editorial policies, including the establishment of new paper formats such as Registered Reports and Data Notes. This paper provides: (i) an overview of the current state of Open Science policies within health psychology and behavioral medicine, (ii) a call for submissions to an Article Collection of Registered Reports and Data Notes as new paper formats within the journal of Health Psychology & Behavioral Medicine, (iii) an overview of Registered Reports and Data Notes, and (iv) practical considerations for authors and reviewers of Registered Reports and Data Notes.

ExROPPP: Fast, accurate, and spin-pure calculation of the electronically excited states of organic hydrocarbon radicals.

Recent years have seen an explosion of interest in organic radicals due to their promise for highly efficient organic light-emitting diodes and molecular qubits. However, accurately and inexpensively computing their electronic structure has been challenging, especially for excited states, due to the spin-contamination problem. Furthermore, while alternacy or "pseudoparity" rules have guided the interpretation and prediction of the excited states of closed-shell hydrocarbons since the 1950s, similar general rules for hydrocarbon radicals have not to our knowledge been found yet. In this article, we present solutions to both of these challenges. First, we combine the extended configuration interaction singles method with Pariser-Parr-Pople (PPP) theory to obtain a method that we call ExROPPP (Extended Restricted Open-shell PPP) theory. We find that ExROPPP computes spin-pure excited states of hydrocarbon radicals with comparable accuracy to experiment as high-level general multi-configurational quasi-degenerate perturbation theory calculations but at a computational cost that is at least two orders of magnitude lower. We then use ExROPPP to derive widely applicable rules for the spectra of alternant hydrocarbon radicals, which are completely consistent with our computed results. These findings pave the way for highly accurate and efficient computation and prediction of the excited states of organic radicals.

Simulating whole-body vibration for neonatal patients on a tire-coupled road simulator.

Exposure to excessive whole-body vibration is linked to health issues and may result in increased rates of mortality and morbidity in infants. Newborn infants requiring specialized treatment at neonatal intensive care units often require transportation by road ambulance to specialized care centers, exposing the infants to potentially harmful vibration and noise. A standardized Neonatal Patient Transport System (NPTS) has been deployed in Ontario, Canada, that provides life saving equipment to patients and safe operation for the clinical care staff. However, there is evidence that suggests patients may experience a higher amplitude of vibration at certain frequencies when compared with the vehicle vibration. In a multi-year collaborative project, we seek to create a standardized test procedure to evaluate the levels of vibration and the effectiveness of mitigation strategies. Previous studies have looked at laboratory vibration testing of a transport system or transport incubator and were limited to single degree of freedom excitation, neglecting the combined effects of rotational motion. This study considers laboratory testing of a full vehicle and patient transport system on an MTS Model 320 Tire-Coupled Road Simulator. The simulation of road profiles and discrete events on a tire-coupled road simulator allows for the evaluation of the vibration levels of the transport system and the exploration of mitigation strategies in a controlled setting. The tire-coupled simulator can excite six degrees-of-freedom motion of the transport system for vibration evaluation in three orthogonal directions including the contributions of the three rotational degrees of freedom. The vibration data measured on the transport system during the tire-coupled testing are compared to corresponding road test data to assess the accuracy of the vibration environment replication. Three runs of the same drive file were conducted during the laboratory testing, allowing the identification of anomalies and evaluation of the repeatability. The tire-coupled full vehicle testing revealed a high level of accuracy in re-creating the road sections and synthesized random profiles. The simulation of high amplitude discrete events, such as speed hump traverses, were highly repeatable, yet yielded less accurate results with respect to the peak amplitudes at the patient. The resulting accelerations collected at the input to the manikin (sensor located under the mattress) matched well between the real-world and road simulator. The sensors used during testing included series 3741B uni-axial and series 356A01 tri-axial accelerometers by PCB Piezotronics. These results indicate a tire-coupled road simulator can be used to accurately evaluate vibration levels and assess the benefits of future mitigation strategies in a controlled setting with a high level of repeatability.

Gender-affirming care in the assessment and treatment of psychosis risk: Considering minority stress in current practice and future research.

INTRODUCTION: Although research has documented the marked disparities in rates of psychosis-spectrum diagnoses in various socially marginalized populations, there is limited research addressing the needs of gender expansive individuals in the context of psychosis-spectrum illnesses using a minority stress lens. As clinical high-risk for psychosis (CHR-p) assessment and treatment becomes accessible to increasingly diverse populations, there is a need for clinicians to demonstrate greater clinical competency working with individuals across diverse social backgrounds and identities. METHODS: We examined rates of gender expansive (GE) patients seeking evaluation at an urban-based CHR-p clinic and compared the diagnostic profile of GE individuals to cisgender patients. Post-hoc analyses were conducted on clinical variables with significant differences between the cisgender and GE groups. RESULTS: The proportion of GE patients seeking evaluation increased from 2017 (9.3%) to 2021 (16.7%). Compared to cisgender youth, GE patients had significantly higher depressive, social anxiety, borderline personality disorder symptoms, higher levels of suicidality and non-suicidal self-injurious behaviour, and lower role functioning. Gender identity was predictive of suicidality controlling for social anxiety, borderline symptoms, and role functioning. CONCLUSIONS: We review implications for CHR-p treatment and discuss ways to integrate minority stress theory and gender-affirming practices into coordinated specialty care for CHR-p patients.

The Use of Hospital Services by Patients With Muscle Invasive Bladder Cancer in the Last Year of Life: Identifying the Areas to Improve Care.

INTRODUCTION: Muscle-invasive bladder cancer (MIBC) is associated with significant morbidity. However, patients' specific health needs have not been well defined. This study analyses the utilisation of hospital resources by MIBC patients in the 12 months before death, informing healthcare modelling and enabling service redesign to improve their quality of life. MATERIALS AND METHODS: All patients who died after being diagnosed with MIBC at a single hospital in the United Kingdom within four years were included. Patients' electronic health records were reviewed to collect data on all interactions with hospital services in their last year of life. RESULTS: A total of 41 patients were included, with survival times ranging from one to 88 months (with a median of nine months). In the last year of life, a patient from this cohort had an average of 5.2 outpatient appointments and 2.3 emergency admissions leading to 17.1 days of inpatient stay and 1.3 operations/procedures. The most common reasons for emergency admission were for the management of haematuria (23%), urinary tract infection (23%), or chest infection (12%). CONCLUSION: Patients with MIBC demonstrate significant utilisation of healthcare resources in their last year of life. An awareness of this should inform honest discussions with patients, earlier provision of palliative care, and proactive management of haematuria and urinary tract infections to improve care in this important stage of life.

Implementing Technologies to Enhance Coordinated Specialty Care Framework: Implementation Outcomes From a Development and Usability Study.

BACKGROUND: Coordinated specialty care (CSC) has demonstrated efficacy in improving outcomes in individuals at clinical high risk for psychosis and individuals with first-episode psychosis. Given the limitations of scalability and staffing needs, the augmentation of services using digital mental health interventions (DMHIs) may be explored to help support CSC service delivery. OBJECTIVE: In this study, we aimed to understand the methods to implement and support technology in routine CSC and offered insights from a quality improvement study assessing the implementation outcomes of DMHIs in CSC. METHODS: Patients and clinicians including psychiatrists, therapists, and supported education and employment specialists from a clinical-high-risk-for-psychosis clinic (Center for Early Detection Assessment and Response to Risk [CEDAR]) and a first-episode-psychosis clinic (Advancing Services for Psychosis Integration and Recovery [ASPIRE]) participated in a quality improvement project exploring the feasibility of DMHIs following the Access, Alignment, Connection, Care, and Scalability framework to implement mindLAMP, a flexible and evidenced-based DMHI. Digital navigators were used at each site to assist clinicians and patients in implementing mindLAMP. To explore the differences in implementation outcomes associated with the app format, a menu-style format was delivered at CEDAR, and a modular approach was used at ASPIRE. Qualitative baseline and follow-up data were collected to assess the specific implementation outcomes. RESULTS: In total, 5 patients (ASPIRE: n=3, 60%; CEDAR: n=2, 40%) were included: 3 (60%) White individuals, 2 (40%) male and 2 (40%) female patients, and 1 (20%) transgender man, with a mean age of 19.6 (SD 2.05) years. Implementation outcome data revealed that patients and clinicians demonstrated high accessibility, acceptability, interest, and belief in the sustainability of DMHIs. Clinicians and patients presented a wide range of interest in unique use cases of DMHI in CSC and expressed variable feasibility and appropriateness associated with nuanced barriers and needs. In addition, the results suggest that adoption, penetration, feasibility, and appropriateness outcomes were moderate and might continue to be explored and targeted. CONCLUSIONS: Implementation outcomes from this project suggest the need for a patient- and clinician-centered approach that is guided by digital navigators and provides versatility, autonomy, and structure. Leveraging these insights has the potential to build on growing research regarding the need for versatility, autonomy, digital navigator support, and structured applications. We anticipate that by continuing to research and improve implementation barriers impeding the adoption and penetration of DMHIs in CSC, accessibility and uptake of DMHIs will improve, therefore connecting patients to the demonstrated benefits of technology-augmented care.

Developing and centralising a nurse-led local anaesthetic transperineal biopsy service during COVID.

Introduction: Transperineal (TP) biopsy has recently replaced the transrectal ultrasound (TRUS) approach as the ideal method of biopsy in the United Kingdom with growing trends to adopt. To minimise transmission of COVID-19 during the first wave of the pandemic, the British Association of Urological Surgeons Section of Oncology issued guidelines reducing general anaesthesia (GA) procedures and initiate COVID-secure 'green' site diagnostics. As a result of these guidelines and reduction in clinical diagnostics trust-wide, we ceased all TRUS diagnostics and implemented a centralised, nurse-led LA TP biopsy service. Materials and methods: A waiting list was developed for those awaiting prostate cancer diagnostics across the network. A COVID-secure 'green' site was quickly identified with TP biopsies starting soon after. Quality improvement methodology was utilised and a run chart was used to show if changes were sustainable. Results: Successful implementation and centralisation of a TP biopsy service occurred with TRUS guided biopsies ceasing across all sites on 12 May 2020. The procedures were carried out by urology advanced nurse practitioners under local anaesthesia with a select few occurring under GA. Centralising the service in a COVID-secure manner freed up dedicated theatre sessions and personal leading to increased efficiency elsewhere. The service was robust and was maintained upon lifting of COVID restrictions. Conclusions: A centralised, nurse led LA TP biopsy service in a procedural unit was implemented successfully. The service has remained resilient upon lifting of restrictions and return to business as usual. This led to improved performance across trust by freeing up valuable resources and staff to undertake more duties. The service remains highly valued trust-wide.

Species-specific microRNA discovery and target prediction in the soybean cyst nematode.

The soybean cyst nematode (SCN) is a devastating pathogen for economic and food security considerations. Although the SCN genome has recently been sequenced, the presence of any miRNA has not been systematically explored and reported. This paper describes the development of a species-specific SCN miRNA discovery pipeline and its application to the SCN genome. Experiments on well-documented model nematodes (Caenorhabditis elegans and Pristionchus pacificus) are used to tune the pipeline's hyperparameters and confirm its recall and precision. Application to the SCN genome identifies 3342 high-confidence putative SCN miRNA. Prediction specificity within SCN is confirmed by applying the pipeline to RNA hairpins from known exonic regions of the SCN genome (i.e., sequences known to not be miRNA). Prediction recall is confirmed by building a positive control set of SCN miRNA, based on a limited deep sequencing experiment. Interestingly, a number of novel miRNA are predicted to be encoded within the intronic regions of effector genes, known to be involved in SCN parasitism, suggesting that these miRNA may also be involved in the infection process or virulence. Beyond miRNA discovery, gene targets within SCN are predicted for all high-confidence novel miRNA using a miRNA:mRNA target prediction system. Lastly, cross-kingdom miRNA targeting is investigated, where putative soybean mRNA targets are identified for novel SCN miRNA. All predicted miRNA and gene targets are made available in appendix and through a Borealis DataVerse open repository ( https://borealisdata.ca/dataset.xhtml?persistentId=doi:10.5683/SP3/30DEXA ).

Medical device legislation for custom-made devices after the UK has left the EU: answers to a further ten important questions.

A custom-made device is a medical device that is 'intended for the sole use of a particular patient' made 'in accordance with a written prescription'. In a dental setting, common examples of custom-made devices include crowns, dentures and orthodontic appliances. Until fairly recently, dental professionals who manufactured custom-made devices within the European Union (EU) were required to do so in accordance with Council Directive 93/42/EEC (Medical Devices Directive [MDD]), which was given effect in the UK by the Medical Devices Regulations 2002 (Statutory Instrument 2002/618 [UK MDR 2002]). The MDD has since been replaced by Regulation (EU) 2017/745 (Medical Device Regulation [EU MDR]). However, the withdrawal of the UK from the EU, the COVID-19 pandemic and the implementation of the Ireland/Northern Ireland Protocol has led to different parts of the UK following different legislative frameworks. Dental professionals in Great Britain (England, Scotland and Wales) who manufacture custom-made devices must follow the relevant requirements of the UK MDR 2002 (although devices may be placed on the market in accordance with the EU MDR until 30 June 2024), while those in Northern Ireland are subject to the EU MDR. This paper provides answers to some key questions regarding the ways in which these legislative changes have impacted the provision of custom-made devices in the UK.

Large-scale data mining pipeline for identifying novel soybean genes involved in resistance against the soybean cyst nematode.

The soybean cyst nematode (SCN) [Heterodera glycines Ichinohe] is a devastating pathogen of soybean [Glycine max (L.) Merr.] that is rapidly becoming a global economic issue. Two loci conferring SCN resistance have been identified in soybean, Rhg1 and Rhg4; however, they offer declining protection. Therefore, it is imperative that we identify additional mechanisms for SCN resistance. In this paper, we develop a bioinformatics pipeline to identify protein-protein interactions related to SCN resistance by data mining massive-scale datasets. The pipeline combines two leading sequence-based protein-protein interaction predictors, the Protein-protein Interaction Prediction Engine (PIPE), PIPE4, and Scoring PRotein INTeractions (SPRINT) to predict high-confidence interactomes. First, we predicted the top soy interacting protein partners of the Rhg1 and Rhg4 proteins. Both PIPE4 and SPRINT overlap in their predictions with 58 soybean interacting partners, 19 of which had GO terms related to defense. Beginning with the top predicted interactors of Rhg1 and Rhg4, we implement a "guilt by association" in silico proteome-wide approach to identify novel soybean genes that may be involved in SCN resistance. This pipeline identified 1,082 candidate genes whose local interactomes overlap significantly with the Rhg1 and Rhg4 interactomes. Using GO enrichment tools, we highlighted many important genes including five genes with GO terms related to response to the nematode (GO:0009624), namely, Glyma.18G029000, Glyma.11G228300, Glyma.08G120500, Glyma.17G152300, and Glyma.08G265700. This study is the first of its kind to predict interacting partners of known resistance proteins Rhg1 and Rhg4, forming an analysis pipeline that enables researchers to focus their search on high-confidence targets to identify novel SCN resistance genes in soybean.

Short Timeframe Prediction of Kidney Failure among Patients with Advanced Chronic Kidney Disease.

BACKGROUND: Development of a short timeframe (6-12 months) kidney failure risk prediction model may serve to improve transitions from advanced chronic kidney disease (CKD) to kidney failure and reduce rates of unplanned dialysis. The optimal model for short timeframe kidney failure risk prediction remains unknown. METHODS: This retrospective study included 1757 consecutive patients with advanced CKD (mean age 66 years, estimated glomerular filtration rate 18 mL/min/1.73 m2). We compared the performance of Cox regression models using (a) baseline variables alone, (b) time-varying variables and machine learning models, (c) random survival forest, (d) random forest classifier in the prediction of kidney failure over 6/12/24 months. Performance metrics included area under the receiver operating characteristic curve (AUC-ROC) and maximum precision at 70% recall (PrRe70). Top-performing models were applied to 2 independent external cohorts. RESULTS: Compared to the baseline Cox model, the machine learning and time-varying Cox models demonstrated higher 6-month performance [Cox baseline: AUC-ROC 0.85 (95% CI 0.84-0.86), PrRe70 0.53 (95% CI 0.51-0.55); Cox time-varying: AUC-ROC 0.88 (95% CI 0.87-0.89), PrRe70 0.62 (95% CI 0.60-0.64); random survival forest: AUC-ROC 0.87 (95% CI 0.86-0.88), PrRe70 0.61 (95% CI 0.57-0.64); random forest classifier AUC-ROC 0.88 (95% CI 0.87-0.89), PrRe70 0.62 (95% CI 0.59-0.65)]. These trends persisted, but were less pronounced, at 12 months. The random forest classifier was the highest performing model at 6 and 12 months. At 24 months, all models performed similarly. Model performance did not significantly degrade upon external validation. CONCLUSIONS: When predicting kidney failure over short timeframes among patients with advanced CKD, machine learning incorporating time-updated data provides enhanced performance compared with traditional Cox models.

Analysis of communication styles underpinning clinical decision-making in cancer multidisciplinary team meetings.

Introduction: In cancer care, multidisciplinary team (MDT) meetings are the gold standard. While they are trying to maximize productivity on the back of the steadily increasing workload, growing cancer incidence, financial constraints, and staff shortages, concerns have been raised with regards to the quality of team output, as reported by Cancer Research UK in 2017: "Sometimes we discuss up to 70 patients. This is after a whole day of clinics, and we do not finish until after 19.00. Would you want to be number 70?". This study aimed to explore systematically some of the dynamics of group interaction and teamwork in MDT meetings. Materials and methods: This was a prospective observational study conducted across three MDTs/university hospitals in the United Kingdom. We video-recorded 30 weekly meetings where 822 patient cases were reviewed. A cross-section of the recordings was transcribed using the Jefferson notation system and analyzed using frequency counts (quantitative) and some principles of conversation analysis (qualitative). Results: We found that, across teams, surgeons were the most frequent initiators and responders of interactional sequences, speaking on average 47% of the time during case discussions. Cancer nurse specialists and coordinators were the least frequent initiators, with the former speaking 4% of the time and the latter speaking 1% of the time. We also found that the meetings had high levels of interactivity, with an initiator-responder ratio of 1:1.63, meaning that for every sequence of interactions initiated, the initiator received more than a single response. Lastly, we found that verbal dysfluencies (laughter, interruptions, and incomplete sentences) were more common in the second half of meetings, where a 45% increase in their frequency was observed. Discussion: Our findings highlight the importance of teamwork in planning MDT meetings, particularly with regard to Cancer Research UK in 2017 cognitive load/fatigue and decision-making, the hierarchy of clinical expertise, and the increased integration of patients' psychosocial information into MDT discussion and their perspectives. Utilizing a micro-level methodology, we highlight identifiable patterns of interaction among participants in MDT meetings and how these can be used to inform the optimization of teamwork.

Impact of the COVID-19 pandemic on the career development of individuals with psychiatric disabilities.

OBJECTIVE: The purpose of this preliminary exploratory study was to explore the impact of the COVID-19 pandemic on the career development of diverse individuals with psychiatric disabilities. METHODS: Four hundred sixty-nine individuals with psychiatric disabilities and 147 individuals without psychiatric disabilities completed survey questions regarding their employment and educational experiences during the pandemic. We utilized chi-square analyses to explore the differences between those with and without psychiatric disabilities and between racial groups. RESULTS: Our results indicated that individuals with psychiatric disabilities, especially Black, Indigenous, and other people of color (BIPOC), experienced greater employment-related uncertainty during the COVID-19 pandemic than the population without psychiatric disabilities. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Individuals with psychiatric disabilities, particularly BIPOC, need access to more stable employment and supports to maintain their employment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Astaxanthin Reduces Heart Rate and Carbohydrate Oxidation Rates During Exercise in Overweight Individuals.

Astaxanthin (AX) is an antioxidant which may spare endogenous carbohydrates and improve fat oxidation rates, thus improving metabolic flexibility. To date, no studies have attempted to examine the impact of AX in an overweight cohort, whom often suffer from metabolic inflexibility. Nineteen subjects (mean ± SD: age: 27.5 ± 6.3 years; height: 169.7 ± 9.0 cm; body mass: 96.4 ± 17.9 kg; BF%: 37.9 ± 7.0%; BMI: 33.4 ± 5.6 kg/m2; VO2peak: 25.9 ± 6.7 ml·kg-1·min-1) were recruited and supplemented with either 12 mg of AX or placebo (PLA) for 4 weeks. Subjects completed a graded exercise test on a cycling ergometer to examine changes in substrate oxidation rates. A total of 5 stages, each lasting 5 min and resistance increased 15 W each stage, were completed to examine changes in levels of glucose and lactate, fat and carbohydrate (CHO) oxidation rates, heart rate, and rating of perceived exertion (RPE). Although there were no changes found in rates of fat oxidation, blood lactate or glucose, or RPE (all p > 0.05), a significant decrease was observed in CHO oxidation from pre to post supplementation in the AX group only. Further, the AX group demonstrated a 7% decrease in heart rate across the graded exercise test. These findings suggest that 4 weeks of AX supplementation may offer some cardiometabolic benefits to overweight individuals, and be a favorable supplement for these individuals beginning an exercise program.

Consensus clinical management guidelines for acid sphingomyelinase deficiency (Niemann-Pick disease types A, B and A/B).

BACKGROUND: Acid Sphingomyelinase Deficiency (ASMD) is a rare autosomal recessive disorder caused by mutations in the SMPD1 gene. This rarity contributes to misdiagnosis, delayed diagnosis and barriers to good care. There are no published national or international consensus guidelines for the diagnosis and management of patients with ASMD. For these reasons, we have developed clinical guidelines that defines standard of care for ASMD patients. METHODS: The information contained in these guidelines was obtained through a systematic literature review and the experiences of the authors in their care of patients with ASMD. We adopted the Appraisal of Guidelines for Research and Evaluation (AGREE II) system as method of choice for the guideline development process. RESULTS: The clinical spectrum of ASMD, although a continuum, varies substantially with subtypes ranging from a fatal infantile neurovisceral disorder to an adult-onset chronic visceral disease. We produced 39 conclusive statements and scored them according to level of evidence, strengths of recommendations and expert opinions. In addition, these guidelines have identified knowledge gaps that must be filled by future research. CONCLUSION: These guidelines can inform care providers, care funders, patients and their carers about best clinical practice and leads to a step change in the quality of care for patients with ASMD with or without enzyme replacement therapy (ERT).