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hospitalized patients, methods to optimize use need to be prioritized to provide optimal care. Because the survey provides a cross-sectional assessment, follow-up studies can determine the long-term impact of the pandemic on cEEG utilization.

Postactivation depression of the Hoffmann reflex is reduced in Parkinson's disease (PD), but how the recovery is influenced by the state of the muscle is unknown. The present pilot study examined postactivation depression in PD at rest and during a voluntary contraction while patients were off treatment and while receiving medications and/or deep brain stimulation.

The authors recruited nine patients with PD treated with implanted deep brain stimulation and examined postactivation depression under four treatment conditions. Paired pulses were delivered 25 to 300 ms apart, and soleus Hoffmann reflex recovery was tested at rest and during voluntary plantar flexion. Trials were matched for background muscle activity and compared with 10 age-matched controls.

Patients with Parkinson disease who were OFF medications (OFF meds) and OFF stimulation (OFF stim) at rest showed less postactivation depression at the 300 ms interpulse interval (86.1% ± 21.0%) relative to control subjects (36.4% ± 6.1%; P < 0.05). 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. buy SCH900353 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). 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. link2 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.Using the Veterans Health Administration's 2018 national provider and staff survey, this study describes the practice patterns of 1453 primary care providers for specialty care consults, program referrals, secure messaging, and telephone visits; and examines whether the practice patterns are associated with provider burnout in primary care teamlets. About 51% of providers experienced moderate to severe burnout and 22% had severe burnout. Providers who embraced all 4 practice approaches had lower odds of severe burnout than providers endorsing none of the approaches (odds ratio range, 0.35-0.39). Associations were weaker for providers with moderate to severe burnout.An eVisit is a form of asynchronous telehealth whereby the patient submits an online request for medical advice and receives a written response from a health care provider. While thought to be an efficient way to resolve low-acuity medical issues, there is limited information on whether eVisits lead the avoidance of in-person care. link3 We reviewed 8627 eVisits that occurred at our institution from July 2017 to March 2020 and found that 23.1% of eVisits required follow-up medical care within 14 days (22.6% with primary care physician, 0.3% with emergency department, 0.2% both). Our results indicate that eVisits are a feasible alternative to in-person care for low-complexity medical issues.

We used the Agence nationale de Recherches sur le sida et les hépatites virales (ANRS)-IPERGAY trial to qualitatively and quantitatively measure drug use among men who have sex with men under preexposure prophylaxis using 2 different methods, to better understand and collectively respond to risky practices.

We included 69 volunteers of the ANRS-IPERGAY trial. We measured drug use by 2 methods (1) drug detection by hair analysis and (2) reported drug use by self-reported drug consumption.

New psychoactive substances (NPS) and conventional drugs were detected in 53 of the 69 (77%) volunteers by hair analysis and in 39 of the 69 (57%) volunteers by questionnaires. On the 219 hair segments analyzed, the most commonly used drugs were cocaine in 47 of the 69 (68%), 3,4-methylenedioxymethamphetamine/ecstasy in 31 of the 69 (45%), and NPS in 27 of the 69 (39%). On the 1061 collected questionnaires, the most commonly used drugs were cocaine in 31 of the 69 (45%), 3,4-methylenedioxymethamphetamine/ecstasy in 29 osting to understand uses and to be able to collectively respond to risky practices with adapted messages.

The diagnosis of paradoxical tuberculosis-associated immune reconstitution inflammatory syndrome (TB-IRIS) relies on characteristic clinical features synthesized as the International Network for the Study of HIV-associated IRIS (INSHI) case definition. There is no confirmatory laboratory test.

Site B HIV-TB clinic in Khayelitsha, Cape Town, South Africa.

Using data of participants with HIV-associated tuberculosis starting antiretroviral treatment from a prospective trial evaluating prednisone for TB-IRIS prevention, we applied latent class analysis to model a gold standard for TB-IRIS. The model-predicted probability of TB-IRIS for each participant was used to assess the performance of the INSHI case definition and compare its diagnostic accuracy with several adapted case definitions.

Data for this analysis were complete for 217 participants; 41% developed TB-IRIS. Our latent class model included the following parameters respiratory symptoms; night sweats; INSHI major criteria 1, 2, and 4; maximum C-reactive protein >90 mg/L; maximum heart rate >120/min; maximum temperature >37.7°C; and preantiretroviral therapy CD4 count <50 cells/µL. The model estimated a TB-IRIS incidence of 43% and had optimal goodness of fit (χ2 = 337, P = 1.0). The INSHI case definition displayed a sensitivity of 0.77 and a specificity of 0.86. Replacing all the minor INSHI criteria with objectives measures (C-reactive protein elevation, fever, and/or tachycardia) resulted in a definition with better diagnostic accuracy, with a sensitivity of 0.89 and a specificity of 0.88.

The INSHI case definition identifies TB-IRIS with reasonable accuracy. Amending the case definition by replacing INSHI minor criteria with objective variables improved sensitivity without loss of specificity.

The INSHI case definition identifies TB-IRIS with reasonable accuracy. Amending the case definition by replacing INSHI minor criteria with objective variables improved sensitivity without loss of specificity.