A systematic review on the biochemical threshold of mitochondrial genetic variants.

Mitochondrial DNA (mtDNA) variants cause a range of diseases from severe pediatric syndromes to aging-related conditions. The percentage of mtDNA copies carrying a pathogenic variant, variant allele frequency (VAF), must reach a threshold before a biochemical defect occurs, termed the biochemical threshold. Whether the often-cited biochemical threshold of >60% VAF is similar across mtDNA variants and cell types is unclear. In our systematic review, we sought to identify the biochemical threshold of mtDNA variants in relation to VAF by human tissue/cell type. We used controlled vocabulary terms to identify articles measuring oxidative phosphorylation (OXPHOS) complex activities in relation to VAF. We identified 76 eligible publications, describing 69, 12, 16, and 49 cases for complexes I, III, IV, and V, respectively. Few studies evaluated OXPHOS activities in diverse tissue types, likely reflective of clinical access. A number of cases with similar VAFs for the same pathogenic variant had varying degrees of residual activity of the affected complex, alluding to the presence of modifying variants. Tissues and cells with VAFs <60% associated with low complex activities were described, suggesting the possibility of a biochemical threshold of <60%. Using Kendall rank correlation tests, the VAF of the m.8993T > G variant correlated with complex V activity in skeletal muscle (τ = -0.58, P = 0.01, n = 13); however, no correlation was observed in fibroblasts (P = 0.7, n = 9). Our systematic review highlights the need to investigate the biochemical threshold over a wider range of VAFs in disease-relevant cell types to better define the biochemical threshold for specific mtDNA variants.

Effectively teaching cultural competence in a pre-professional healthcare curriculum.

BACKGROUND: There has been research documenting the rising numbers of racial and ethnic minority groups in the United States. With this rise, there is increasing concern over the health disparities that often affect these populations. Attention has turned to how clinicians can improve health outcomes and how the need exists to educate healthcare professionals on the practice of cultural competence. Here we present one successful approach for teaching cultural competence in the healthcare curriculum with the development of an educational session on cultural competence consisting of case-based, role-play exercises, class group discussions, online discussion boards, and a lecture PowerPoint presentation. METHODS: Cultural competence sessions were delivered in a pre-dental master's program to 178 students between 2017 and 2020. From 2017 to 2019, the sessions were implemented as in-person, case-based, role-play exercises. In 2020, due to in-person limitations caused by the COVID-19 pandemic, students were asked to read the role-play cases and provide a reflection response using the online Blackboard Learn discussion board platform. Evaluation of each session was performed using post-session survey data. RESULTS: Self-reported results from 2017 to 2020 revealed that the role-play exercises improved participant's understanding of components of cultural competence such as communication in patient encounters (95%), building rapport with patients (94%), improving patient interview skills (95%), and recognition of students own cultural biases when working with patients (93%). CONCLUSIONS: Students were able to expand their cultural awareness and humility after completion of both iterations of the course session from 2017 to 2019 and 2020. This session can be an effective method for training healthcare professionals on cultural competence.

Anomaly Detection Methods in Autonomous Robotic Missions.

Since 2015, there has been an increase in articles on anomaly detection in robotic systems, reflecting its growing importance in improving the robustness and reliability of the increasingly utilized autonomous robots. This review paper investigates the literature on the detection of anomalies in Autonomous Robotic Missions (ARMs). It reveals different perspectives on anomaly and juxtaposition to fault detection. To reach a consensus, we infer a unified understanding of anomalies that encapsulate their various characteristics observed in ARMs and propose a classification of anomalies in terms of spatial, temporal, and spatiotemporal elements based on their fundamental features. Further, the paper discusses the implications of the proposed unified understanding and classification in ARMs and provides future directions. We envisage a study surrounding the specific use of the term anomaly, and methods for their detection could contribute to and accelerate the research and development of a universal anomaly detection system for ARMs.

A scoping review of how early-stage knee osteoarthritis has been defined.

BACKGROUND: Early-stage knee osteoarthritis (KOA) classification criteria will enable consistent identification and trial recruitment of individuals with knee osteoarthritis (OA) at an earlier stage of the disease when interventions may be more effective. Toward this goal, we identified how early-stage KOA has been defined in the literature. METHODS: We performed a scoping literature review in PubMed, EMBASE, Cochrane, and Web of Science, including human studies where early-stage KOA was included as a study population or outcome. Extracted data included demographics, symptoms/history, examination, laboratory, imaging, performance-based measures, gross inspection/histopathologic domains, and the components of composite early-stage KOA definitions. RESULTS: Of 6142 articles identified, 211 were included in data synthesis. An early-stage KOA definition was used for study inclusion in 194 studies, to define study outcomes in 11 studies, and in the context of new criteria development or validation in six studies. The element most often used to define early-stage KOA was Kellgren-Lawrence (KL) grade (151 studies, 72%), followed by symptoms (118 studies, 56%), and demographic characteristics (73 studies, 35%); 14 studies (6%) used previously developed early-stage KOA composite criteria. Among studies defining early-stage KOA radiographically, 52 studies defined early-stage KOA by KL grade alone; of these 52, 44 (85%) studies included individuals with KL grade 2 or higher in their definitions. CONCLUSION: Early-stage KOA is variably defined in the published literature. Most studies included KL grades of 2 or higher within their definitions, which reflects established or later-stage OA. These findings underscore the need to develop and validate classification criteria for early-stage KOA.

FedBranched: Leveraging Federated Learning for Anomaly-Aware Load Forecasting in Energy Networks.

Increased demand for fast edge computation and privacy concerns have shifted researchers' focus towards a type of distributed learning known as federated learning (FL). Recently, much research has been carried out on FL; however, a major challenge is the need to tackle the high diversity in different clients. Our research shows that using highly diverse data sets in FL can lead to low accuracy of some local models, which can be categorised as anomalous behaviour. In this paper, we present FedBranched, a clustering-based framework that uses probabilistic methods to create branches of clients and assigns their respective global models. Branching is performed using hidden Markov model clustering (HMM), and a round of branching depends on the diversity of the data. Clustering is performed on Euclidean distances of mean absolute percentage errors (MAPE) obtained from each client at the end of pre-defined communication rounds. The proposed framework was implemented on substation-level energy data with nine clients for short-term load forecasting using an artificial neural network (ANN). FedBranched took two clustering rounds and resulted in two different branches having individual global models. The results show a substantial increase in the average MAPE of all clients; the biggest improvement of 11.36% was observed in one client.

Evaluation of machine learning models as decision aids for anesthesiologists.

Machine Learning (ML) models have been developed to predict perioperative clinical parameters. The objective of this study was to determine if ML models can serve as decision aids to improve anesthesiologists' prediction of peak intraoperative glucose values and postoperative opioid requirements. A web-based tool was used to present actual surgical case and patient information to 10 practicing anesthesiologists. They were asked to predict peak glucose levels and post-operative opioid requirements for 100 surgical patients with and without presenting ML model estimations of peak glucose and opioid requirements. The accuracies of the anesthesiologists' estimates with and without ML estimates as reference were compared. A questionnaire was also sent to the participating anesthesiologists to obtain their feedback on ML decision support. The accuracy of peak glucose level estimates by the anesthesiologists increased from 79.0 ± 13.7% without ML assistance to 84.7 ± 11.5% (< 0.001) when ML estimates were provided as reference. The accuracy of opioid requirement estimates increased from 18% without ML assistance to 42% (p < 0.001) when ML estimates were provided as reference. When ML estimates were provided, predictions of peak glucose improved for 8 out of the 10 anesthesiologists, while predictions of opioid requirements improved for 7 of the 10 anesthesiologists. Feedback questionnaire responses revealed that the anesthesiologist primarily used the ML estimates as reference to modify their clinical judgement. ML models can improve anesthesiologists' estimation of clinical parameters. ML predictions primarily served as reference information that modified an anesthesiologist's clinical estimate.

Reproductive and pregnancy health care for women with intellectual and developmental disabilities: A scoping review.

BACKGROUND: Women with intellectual and developmental disabilities face poorer reproductive and pregnancy outcomes partially due to health care inequity. Our objective was to conduct a scoping review of reproductive and pregnancy related health care among women with intellectual and developmental disabilities. METHODS: We systematically reviewed three databases for keywords pertaining to pregnancy, reproductive health, and intellectual and developmental disabilities. Two reviewers screened abstracts and extracted full text. We synthesised included papers, identifying common themes. RESULTS: Thirty-six papers met review criteria. Women with intellectual and developmental disabilities had lower fertility rates and were less likely to receive adequate sexual education compared to peers. While most women received prenatal care, uptake was lower and received later than women without intellectual and developmental disabilities. CONCLUSIONS: Pregnancy-related health care is often lacking for women with intellectual and developmental disabilities. There are gaps inhibiting our understanding which prevents action to reduce health disparities.

National criteria for academic appointment in vascular surgery.

OBJECTIVE: Advancement in academic medicine is multifactorial. Our objectives were to characterize academic appointments in vascular surgery and to investigate what factors, particularly publications, influenced academic appointment. METHODS: Academic vascular surgeons at Accreditation Council for Graduate Medical Education vascular training programs or at primary sites of U.S. allopathic medical schools were included. Those with qualified titles, such as "adjunct" or a "clinical" prefix, were excluded. Sex, education, region, board certification, and affiliation details were recorded. Web of Science was queried for publication details and h-index. The h-index is a "personal impact factor" defined as "x" number of publications cited at least "x" number of times. After surgeons' information was deidentified, univariate and multivariable analyses were completed for academic appointment and appointment as division chief. RESULTS: There were 642 vascular surgeons who met criteria: 297 (46.3%) assistant professors, 150 (23.4%) associate professors, and 195 (30.4%) professors. There were 96 (15%) division chiefs and 10 (1.6%) chairs of surgery, and 83.2% were male. Surgeons worked in the Northeast (33.5%), Southern (32.6%), Central (20.1%), and Western (13.9%) United States. The mean (±standard deviation) number of publications was 13.7 ± 15.4 for assistant professors, 33.9 ± 28.8 for associate professors, and 86.8 ± 63.6 for professors (P < .001). Mean number of first or last author publications was 5.3 ± 6.4 for assistant professors, 12.2 ± 12.7 for associate professors, and 38.7 ± 35.3 for professors (P < .001). Mean h-index was 5.9 ± 5.4 for assistant professors, 12 ± 7.7 for associate professors, and 24.9 ± 12.6 for professors (P < .001). In multivariable analysis, vascular surgery board certification (adjusted odds ratio [OR], 6.08; 95% confidence interval [CI], 1.15-32.2; P = .03), academic appointment at a public medical school (OR, 1.99; 95% CI, 1.18-3.37; P = .01), years since medical school graduation (OR, 1.13; 95% CI, 1.09-1.18; P < .001, per year), and number of publications (OR, 1.05; 95% CI, 1.03-1.06; P < .001, per publication) were independently associated with associate professor. Factors independently associated with professor were years since medical school graduation (OR, 1.18; 95% CI, 1.12-1.24; P < .001, per year) and number of first or last author publications (OR, 1.05; 95% CI, 1.02-1.09; P = .003, per publication). Appointment as division chief was independently associated with h-index (OR, 1.04; 95% CI, 1.01-1.08; P = .016, per point). CONCLUSIONS: Total number of publications was independently associated with associate professor, with number of first or last author publications particularly important for professor. The h-index was not independently associated with academic appointment, but it was for appointment as division chief. This study provides relevant data for promotional guidance in academic vascular surgery.

The Impact of co-morbid severe mental illness and HIV upon mental and physical health and social outcomes: a systematic review.

Our aim was to review the evidence related to the impact of co-morbid severe mental illness SMI (schizophrenia, schizoaffective and bipolar disorder) and HIV upon mental health, physical health and social outcomes. We carried out a systematic review of scientific evidence, searching online databases (MEDLINE, PsychInfo, EMBASE, Global Health and Scopus) for studies between 1983 and 2017 using search terms for SMI and HIV. Studies were included if they compared health or social outcomes between people living with co-morbid SMI and HIV and people living with either: a) HIV only; or b) SMI only. Outcomes of interest were: mortality, health service use, HIV/SMI-related, co-morbidities, and social outcomes. We identified 20 studies which met our inclusion criteria. Although studies were generally high quality, there was heterogeneity in both selection of outcomes and choice of measure. It was therefore difficult to draw strong conclusions regarding the impact of co-morbid SMI and HIV across any outcome. We found little evidence that co-morbid SMI and HIV were associated with lower levels of treatment, care or poorer clinical outcomes compared to people living with SMI or HIV alone. However, mortality appeared to be higher among the co-morbid group in three out of four analyses identified. Physical and mental co-morbidities and social outcomes were rarely measured. Limited data mean that the impact of co-morbid SMI and HIV is uncertain. In order to develop evidence-based guidelines, there is an urgent need for further research. This may be realized by exploring opportunities for using data from existing cohort studies, routinely collected data and data linkage to investigate important questions relating to this neglected but potentially important area.

Hospital-Based Acute Care Within 7 Days of Discharge After Outpatient Arthroscopic Shoulder Surgery.

BACKGROUND: The rate of hospital-based acute care (defined as hospital transfer at discharge, emergency department [ED] visit, or subsequent inpatient hospital [IP] admission) after outpatient procedure is gaining momentum as a quality metric for ambulatory surgery. However, the incidence and reasons for hospital-based acute care after arthroscopic shoulder surgery are poorly understood. METHODS: We studied adult patients who underwent outpatient arthroscopic shoulder procedures in New York State between 2011 and 2013 using the Healthcare Cost and Utilization Project database. ER visits and IP admissions within 7 days of surgery were identified by cross-matching 2 independent Healthcare Cost and Utilization Project databases. RESULTS: The final cohort included 103,476 subjects. We identified 1867 (1.80%, 95% confidence interval [CI], 1.72%-1.89%) events, and the majority of these encounters were ER visits (1643, or 1.59%, 95% CI, 1.51%-1.66%). Direct IP admission after discharged was uncommon (224, or 0.22%, 95% CI, 0.19%-0.24%). The most common reasons for seeking acute care were musculoskeletal pain (23.78% of all events). Nearly half of all events (43.49%) occurred on the day of surgery or on postoperative day 1. Operative time exceeding 2 hours was associated with higher odds of requiring acute care (odds ratio [OR], 1.28; 99% CI, 1.08-1.51). High-volume surgical centers (OR, 0.67; 99% CI, 0.58-0.78) and regional anesthesia (OR, 0.72; 99% CI, 0.56-0.92) were associated with lower odds of requiring acute care. CONCLUSIONS: The rate of hospital-based acute care after outpatient shoulder arthroscopy was low (1.80%). Complications driving acute care visits often occurred within 1 day of surgery. Many of the events were likely related to surgery and anesthesia (eg, inadequate analgesia), suggesting that anesthesiologists may play a central role in preventing acute care visits after surgery.

What Incentives Are Created by Medicare Payments for Total Hip Arthroplasty?

BACKGROUND: Differences in profitability and contribution margin (CM) between various patient populations may make certain patients particularly attractive (or unattractive) to providers. This study seeks to identify patient characteristics associated with increased profit and CM among Medicare patients undergoing total hip arthroplasty (THA). METHODS: The expected Medicare reimbursement for consecutive patients of Medicare-eligible age (65+ years) undergoing primary unilateral elective THA (n = 498) was calculated in accordance with Center for Medicare and Medicaid Services policy. Costs were derived from the hospital's cost accounting system. Profit and CM were calculated for each patient as reimbursement less total and variable costs, respectively. Patients were compared based on clinical and demographic factors by univariate and multivariate analyses. RESULTS: Medicare patients undergoing THA generated negative average profits but substantial positive CMs. Lower profit and CM were associated with higher American Society of Anesthesiologists Physical Status Classification (P < .01, P = .03), older age (P < .01), and longer length of stay (P < .01, P = .03). No association was found with gender, body mass index, or race. CONCLUSION: If our results are generalizable, Medicare patients requiring THA are currently financially attractive, but institutions have a long-term incentive to shift resources to more profitable patients and service lines, which may eventually restrict access to care for this population. THA providers have a financial incentive to favor Medicare patients with younger age, lower American Society of Anesthesiologists Physical Status Classification, and those who can be expected to require relatively short admissions. The Center for Medicare and Medicaid Services must strive to accurately match reimbursement rates to provider costs to avoid inequitable payments to providers and financial incentives discouraging treatment of high-risk patients or other patient subpopulations.

What are the economic consequences of unplanned readmissions after TKA?

BACKGROUND: In 2009, the Center for Medicare & Medicaid Services (CMS) began penalizing hospitals with high rates of 30-day readmissions after hospitalizations for certain conditions. This policy will expand to include TKA in 2015. QUESTIONS/PURPOSES: What are the median profits and contribution margins of: (1) Medicare-reimbursed TKA, (2) 30-day TKA readmission, and (3) entire episode of care for readmitted TKA patients within 30 days compared to nonreadmitted patients? (4) Under new CMS guidelines, what financial penalty will the authors' institution face if its arthroplasty readmission rate exceeds the national average? METHODS: A retrospective review of 3218 primary TKAs performed during 2 years at a large urban academic hospital network was conducted using administrative and financial data. RESULTS: The median profit and contribution margins, respectively, were as follows: TKA episode, USD 5209 and USD 11,726; 30-day readmission, USD 608 and USD 3814; TKA visit with readmission, USD 2855 and USD 13,901; TKA visit without readmission, USD 5300 and USD 11,652. Readmission penalties could reach USD 6.21 million per year for the authors' institution. DISCUSSION: If our results are generalizable, unplanned TKA readmissions lead to diminished total profit. Although associated with a positive contribution margin, this is likely to be a short-term phenomenon as the new CMS policy will result in readmissions coming at a steep cost to referral centers.

Are there identifiable risk factors and causes associated with unplanned readmissions following total knee arthroplasty?

We conducted a retrospective review of 3218 primary total knee arthroplasties (TKA) performed over two years at an urban academic hospital network using clinical and administrative data. Increased length of stay (LOS) was associated with readmission (P < 0.001). Readmission was not associated with age (P = 0.100), gender (P = 0.608), body mass index (P = 0.329), or staged bilateral procedures (P = 0.420). The most common readmitting diagnoses were post-operative infection (22.5%), hematoma (10.1%), pulmonary embolus (7.9%) and deep vein thrombosis (5.6%). Of readmissions, 53.9% were for surgical reasons and 46.1% were for medical reasons. Certain interventions described in previous literature may be more successful in minimizing unplanned readmissions by focusing on patients with extended LOS, elevated infection risk and low socioeconomic status.

A comprehensive WSN-based approach to efficiently manage a Smart Grid.

The Smart Grid (SG) is conceived as the evolution of the current electrical grid representing a big leap in terms of efficiency, reliability and flexibility compared to today's electrical network. To achieve this goal, the Wireless Sensor Networks (WSNs) are considered by the scientific/engineering community to be one of the most suitable technologies to apply SG technology to due to their low-cost, collaborative and long-standing nature. However, the SG has posed significant challenges to utility operators-mainly very harsh radio propagation conditions and the lack of appropriate systems to empower WSN devices-making most of the commercial widespread solutions inadequate. In this context, and as a main contribution, we have designed a comprehensive ad-hoc WSN-based solution for the Smart Grid (SENSED-SG) that focuses on specific implementations of the MAC, the network and the application layers to attain maximum performance and to successfully deal with any arising hurdles. Our approach has been exhaustively evaluated by computer simulations and mathematical analysis, as well as validation within real test-beds deployed in controlled environments. In particular, these test-beds cover two of the main scenarios found in a SG; on one hand, an indoor electrical substation environment, implemented in a High Voltage AC/DC laboratory, and, on the other hand, an outdoor case, deployed in the Transmission and Distribution segment of a power grid. The results obtained show that SENSED-SG performs better and is more suitable for the Smart Grid than the popular ZigBee WSN approach.

Dynamic analysis of geomaterials using microwave sensing.

Precise characterization of geomaterials improves subsurface energy extraction and storage. Understanding geomaterial property, and the complexities between petrophysics and geomechanics, plays a key role in maintaining energy security and the transition to a net zero global carbon economy. Multiple sectors demand accurate and rapid characterization of geomaterial conditions, requiring the extraction of core plugs in the field for full-field characterization and analysis in the laboratory. We present a novel technique for the non-invasive characterization of geomaterials by using Frequency Modulated Continuous Wave (FMCW) radar in the K-band, representing a new application of microwave radar. We collect data through the delivery of FMCW wave interactions with geomaterials under static and dynamic conditions and show that FMCW can detect fluid presence, differentiate fluid type, indicate the presence of metallic inclusions and detect imminent failure in loaded sandstones by up to 15 s, allowing for greater control in loading up to a failure event. Such precursors have the potential to significantly enhance our understanding of, and ability to model, geomaterial dynamics. This low-cost sensing method is easily deployable, provides quicker and more accessible data than many state-of-the-art systems, and new insights into geomaterial behavior under dynamic conditions.