Citations

Abstract Introduction Idiopathic/isolated REM sleep behavior disorder (iRBD) is a prodromal alpha-synucleinopathy characterized by dream enactment behavior and REM sleep without atonia (RSWA). We sought to define quantitative RSWA diagnostic thresholds in the North American Prodromal Synucleinopathy (NAPS) Consortium cohort. We analyzed RSWA between iRBD patients across participating NAPS sleep centers, compared to normative controls, and hypothesized that previous diagnostic RSWA thresholds were overestimates. Methods All digital polysomnography files were converted to European Data Format and scored at a central laboratory (Mayo Clinic) which standardized display scoring montages, channel sensitivities, and filtering, and scripted computational analyses for visual scoring. RSWA was quantitatively analyzed in the submentalis (SM) and anterior tibialis (AT) muscles in iRBD (n=86) patients and controls (n=118) utilizing well validated visual (Mayo) and automated (RAI) methods. Parametric statistics were used to compare RSWA metrics, and RSWA thresholds were developed using receiver operating characteristic curves. Results RSWA was significantly higher for the RAI and all visual individual and combined muscle activity metrics in iRBD compared to controls (all p<0.001). Average SM phasic measures were: 14.2% (Mayo), 17.9% (McGill), 18.5% (UCLA), and 9.4% (Washington University). Average AT phasic measures at each site were: 26.7% (Mayo), 17.1% (McGill), 23.3% (UCLA), and 17.4% (Washington University). Average SM/AT ‘any’ measures at each site were: 45.4% (Mayo), 35.9% (McGill), 53.4% (UCLA), and 23.5% (Washington University). Overall cohort RBD diagnostic thresholds (AUC, specificity/sensitivity) were: SM phasic 4.9% (90.0, 82.2%/83.7%); AT phasic 7.6% (88.7%, 82.2%/81.4%) and combined SM/AT ‘any’ 13% (94.6, 83.9%/96.5%). Conclusion RSWA thresholds in the NAPS cohort were substantially lower than previously reported, suggesting previously overestimated diagnostic RSWA thresholds due to smaller, enriched patient samples and overfit statistical modeling. Confirmation of these findings in the complete NAPS cohort (n=300 iRBD patients across all 10 NAPS centers) is planned. Support (if any):

Abstract Background Persistent organ failure (POF) is the strongest determinant of mortality in acute pancreatitis (AP). There is a paucity of data regarding the impact of different POF attributes on mortality and the role of different characteristics of systemic inflammatory response syndrome (SIRS) in the risk of developing POF. Objective We aimed to assess the association of POF dynamic features with mortality and SIRS characteristics with POF. Methods We studied 1544 AP subjects prospectively enrolled at 22 international centers (APPRENTICE consortium). First, we estimated the association of onset, duration, and maximal score of SIRS with POF. Then, we evaluated the risk of mortality based on POF onset, duration, number, type, and sequence of organs affected. Analyses were adjusted for potential confounders. Results 58% had SIRS, 11% developed POF, and 2.5% died. Early SIRS, persistent SIRS, and maximal SIRS score ≥ 3 were independently associated with higher risk of POF ( p < 0.05). Mortality risk in POF was higher with two (33%, odds ratio [OR] = 10.8, 3.3–34.9) and three (48%, OR = 20.2, 5.9–68.6) organs failing, in comparison to single POF (4%). In subjects with multiple POF, mortality was higher when the cardiovascular and respiratory systems failed first or concurrently as compared to when the renal system failed first or concurrently with other organ ( p < 0.05). In multivariate regression model, the number and sequence of organs affected in POF were associated with mortality ( p < 0.05). Onset and duration of POF had no impact mortality. Conclusion In AP patients with POF, the risk of mortality is influenced by the number, type, and sequence of organs affected. These results are useful for future revisions of AP severity classification systems.

AbstractBackgroundAmong acute myocardial infarction patients with cardiogenic shock (AMICS), a number of key variables predict mortality, including cardiac arrest (CA) and shock classification as proposed by Society for Cardiovascular Angiography and Intervention (SCAI). Given this prognostic importance, we examined the frequency of reporting of high risk variables in published randomized controlled trials (RCTs) of AMICS patients.MethodsWe identified 15 RCTs enrolling 2,500 AMICS patients and then reviewed rates of CA, baseline neurologic status, right heart catheterization data, lactate levels, inotrope and vasopressor requirement, hypothermia, mechanical ventilation, left ventricular ejection fraction (LVEF), mechanical circulatory support, and specific cause of death based on the primary manuscript and Data in S1.ResultsA total of 2,500 AMICS patients have been enrolled in 15 clinical trials over 21 years with only four trials enrolling >80 patients. The reporting frequency and range for key prognostic factors was: neurologic status (0% reported), hypothermia (28% reported, prevalence 33–75%), specific cause of death (33% reported), cardiac index and wedge pressure (47% reported, range 1.6–2.3 L min−1 m−2 and 15–24 mmHg), lactate (60% reported, range 4–7.7 mmol/L), LVEF (73% reported, range 25–45%), CA (80% reported, prevalence 0–92%), MCS (80% reported, prevalence 13–100%), and mechanical ventilation (93% reported, prevalence 35–100%). This variability was reflected in the 30‐day mortality which ranged from 20–73%.ConclusionsIn a comprehensive review of seminal RCTs in AMICS, important predictors of outcome were frequently not reported. Future efforts to standardize CS trial data collection and reporting may allow for better assessment of novel therapies for AMICS.

Background: Artificial intelligence (AI) in healthcare delivery has become an important area of research due to the rapid progression of technology, which has allowed the growth of many processes historically reliant upon human input. AI has become particularly important in plastic surgery in a variety of settings. This article highlights current applications of AI in plastic surgery and discusses future implications. We further detail ethical issues that may arise in the implementation of AI in plastic surgery. Methods: We conducted a systematic literature review of all electronically available publications in the PubMed, Scopus, and Web of Science databases as of February 5, 2020. All returned publications regarding the application of AI in plastic surgery were considered for inclusion. Results: Of the 89 novel articles returned, 14 satisfied inclusion and exclusion criteria. Articles procured from the references of those of the database search and those pertaining to historical and ethical implications were summarized when relevant. Conclusions: Numerous applications of AI exist in plastic surgery. Big data, machine learning, deep learning, natural language processing, and facial recognition are examples of AI-based technology that plastic surgeons may utilize to advance their surgical practice. Like any evolving technology, however, the use of AI in healthcare raises important ethical issues, including patient autonomy and informed consent, confidentiality, and appropriate data use. Such considerations are significant, as high ethical standards are key to appropriate and longstanding implementation of AI.

AbstractAims and ObjectivesTo determine the level of convergent validity of the ‘6‐Clicks’ Basic Mobility and Daily Activity with the Bedside Mobility Assessment Tool (BMAT) in patients admitted to a tertiary care academic hospital.BackgroundAccurately measuring a patient's ability to mobilise during hospitalisation is necessary but can be challenging. Two instruments, the Activity Measure for Post‐Acute Care short‐form ‘6‐Clicks’ and the BMAT, are commonly used to determine patients’ mobility levels; however, these instruments have not been psychometrically evaluated together. Understanding the characteristics between these tools can support the process of shared decision making amongst healthcare providers.DesignRetrospective Cohort adhering to the STROBE statement.MethodsUsing 13,498 individual patient admissions from an electronic health record, the BMAT score measured closest in time to the ‘6‐Clicks’ Basic Mobility and Daily Activity evaluation was collected. Spearman rank correlations with 95% confidence intervals (CIs) were calculated to determine the level of convergent validity between the ‘6‐Clicks’ Basic Mobility and Daily Activity with the BMAT. Pairwise correlations were also calculated and stratified by admitting medical service.ResultsAll correlations for the ‘6‐Clicks’ Basic Mobility or Daily Activity summative scores and the BMAT mobility levels were statistically significant and moderately correlated. The weakest correlations were seen within the Orthopaedic admitting service group. Most correlations stratified by admitting service [CVD/Pulmonary, Medicine/Hospitalist, Other Surgery and Solid Organ Transplant] were moderate. The strongest correlations were seen within the Neuro/Stroke admitting service.ConclusionModerate levels of convergent validity exist between the ‘6‐Clicks’ and the BMAT in this sample. These findings demonstrate that the construct of patient mobility is not being assessed similarly between the two instruments.Relevance to Clinical PracticeThese findings suggest the continued use of both instruments to allow interdisciplinary assessment of patient mobility status during a hospital stay.