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Mckinney Kamp posted an update 6 months, 3 weeks ago
Postactivation depression was restored when dopaminergic medication and/or deep brain stimulation was applied. Comparisons between resting and active motor states revealed that the recovery curves were similar OFF meds/OFF stim owing to faster recovery in PD seen at rest. In contrast, the effect of the motor state was different ON meds/OFF stim and ON meds/ON stim (both P < 0.05), with a nonsignificant trend OFF meds/ON stim (P > 0.08). Selleck AZD1208 During a contraction, recovery curves were similar between all treatment conditions in PD and control.
Disrupted Hoffmann reflex recovery is restored to control levels in PD patients at rest when receiving medications and/or deep brain stimulation or when engaged in voluntary contraction.
Disrupted Hoffmann reflex recovery is restored to control levels in PD patients at rest when receiving medications and/or deep brain stimulation or when engaged in voluntary contraction.
Triphasic waves (TWs), a common EEG pattern, are considered a subtype of generalized periodic discharges. Most patients with TWs present with an altered level of consciousness, and the TW pattern is believed to represent thalamocortical dysfunction. However, the exact meaning and mechanism of TWs remain unclear. The objective of the current study was to evaluate the source of TWs using EEG source imaging and computerized tomography.
Twenty-eight patients with TWs were investigated. Source analysis was performed on the averaged TWs for each individual, and source maps were extracted. Normalization and automatic segmentation of gray matter were performed on computerized tomography scans before analysis. Finally, voxelwise correlation analyses were conducted between EEG source maps and gray matter volumes.
Source analyses showed that the anterior cingulate cortex was mainly involved in TWs (16/28 patients, 57%). Correlation analyses showed moderate positive and negative correlations between source locationion of the abnormal network responsible for TWs.
Comprehensive, high-value patient-centered care incorporates many facets of the health care system that are beyond the realm of traditional medical knowledge and/or clinical skills.
We describe a novel, learning program integrating systems-based practice curricula into competency-based interprofessional continuing education curriculum for health care professionals. The program incorporated experiential, team-based learning through the development of quality improvement projects. Presurveys and postsurveys assessed participant knowledge and skills. Mixed-level modeling analysis was used to examine the differences across all participants and each cohort.
Across all individuals in all cohorts, postsurvey scores significantly improved (pretest score 2.65) (P ≤ .001). Controlling for cohort year, postsurvey scores increased between cohorts 1 and 2 (B = 0.52; P = .01) and between cohorts 2 and 3 (B = 0.24; P = .15), although increased were nonsignificant. Cohort participants also participated in health systems improvement projects and leveraged improved patient outcomes.
This project signifies a unique approach to delivering systems-based curricula to interprofessional learners in the health care system. Participants became more engaged in systems change, influenced network-level QI initiatives and improvement projects, and positively influenced patient-centered outcomes. Health systems can model this program by partnering with academic organizations to scale and disseminate best practices.
This project signifies a unique approach to delivering systems-based curricula to interprofessional learners in the health care system. Participants became more engaged in systems change, influenced network-level QI initiatives and improvement projects, and positively influenced patient-centered outcomes. Health systems can model this program by partnering with academic organizations to scale and disseminate best practices.
Risk stratification of individual patients who are prone to infection would allow surgeons to monitor high-risk patients more closely and intervene early when needed. This could reduce infection-related consequences such as increased health-care costs. The purpose of this study was to develop a machine learning (ML)-derived risk-stratification tool using the SPRINT (Study to Prospectively Evaluate Reamed Intramedullary Nails in Patients with Tibial Fractures) and FLOW (Fluid Lavage of Open Wounds) trial databases to estimate the probability of infection in patients with operatively treated tibial shaft fractures (TSFs).
Patients with unilateral TSFs from the SPRINT and FLOW trials were randomly split into derivation (80%) and validation (20%) cohorts. Random forest algorithms were used to select features that are relevant to predicting infection. These features were included for algorithm training. Five ML algorithms were trained in recognizing patterns associated with infection. The performance of each Md 0.079, respectively, in the validation cohort.
We developed an ML prediction model that can estimate the probability of infection for individual patients with TSFs based on patient and fracture characteristics that are readily available at hospital admission.
Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.Using data from the National Ambulatory Medical Care Survey, we examined team composition in office-based practices and compared their relative quality of care. We found that, compared with physician-only teams, patients seen by physician and nurse practitioner/nurse midwife teams and those seen by physician and nurse teams were more likely to receive statins for hyperlipidemia and blood pressure screening, respectively. We also found that patients seen by physician and physician assistant teams were less likely to receive recommended care for all 4 quality indicators, and patients seen by any interprofessional team were less likely to receive recommended depression treatment than physician-only teams.
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