Interpretable video-based tracking and quantification of parkinsonism clinical motor states.

Quantification of motor symptom progression in Parkinson's disease (PD) patients is crucial for assessing disease progression and for optimizing therapeutic interventions, such as dopaminergic medications and deep brain stimulation. Cumulative and heuristic clinical experience has identified various clinical signs associated with PD severity, but these are neither objectively quantifiable nor robustly validated. Video-based objective symptom quantification enabled by machine learning (ML) introduces a potential solution. However, video-based diagnostic tools often have implementation challenges due to expensive and inaccessible technology, and typical "black-box" ML implementations are not tailored to be clinically interpretable. Here, we address these needs by releasing a comprehensive kinematic dataset and developing an interpretable video-based framework that predicts high versus low PD motor symptom severity according to MDS-UPDRS Part III metrics. This data driven approach validated and robustly quantified canonical movement features and identified new clinical insights, not previously appreciated as related to clinical severity, including pinkie finger movements and lower limb and axial features of gait. Our framework is enabled by retrospective, single-view, seconds-long videos recorded on consumer-grade devices such as smartphones, tablets, and digital cameras, thereby eliminating the requirement for specialized equipment. Following interpretable ML principles, our framework enforces robustness and interpretability by integrating (1) automatic, data-driven kinematic metric evaluation guided by pre-defined digital features of movement, (2) combination of bi-domain (body and hand) kinematic features, and (3) sparsity-inducing and stability-driven ML analysis with simple-to-interpret models. These elements ensure that the proposed framework quantifies clinically meaningful motor features useful for both ML predictions and clinical analysis.

Predictive models for occurrence of expansive intracranial hematomas and surgical evacuation outcomes in traumatic brain injury patients in Uganda: A prospective cohort study.

Background: Hematoma expansion is a common manifestation of acute intracranial hemorrhage (ICH) which is associated with poor outcomes and functional status. Objective: We determined the prevalence of expansive intracranial hematomas (EIH) and assessed the predictive model for EIH occurrence and surgical evacuation outcomes in patients with traumatic brain injury (TBI) in Uganda. Methods: We recruited adult patients with TBI with intracranial hematomas in a prospective cohort study. Data analysis using logistic regression to identify relevant risk factors, assess the interactions between variables, and developing a predictive model for EIH occurrence and surgical evacuation outcomes in TBI patients was performed. The predictive accuracies of these algorithms were compared using the area under the receiver operating characteristic curve (AUC). A p-values of < 0.05 at a 95% Confidence interval (CI) was considered significant. Results: A total of 324 study participants with intracranial hemorrhage were followed up for 6 months after surgery. About 59.3% (192/324) had expansive intracranial hemorrhage. The study participants with expansive intracranial hemorrhage had poor quality of life at both 3 and 6-months with p < 0.010 respectively. Among the 5 machine learning algorithms, the random forest performed the best in predicting EIH in both the training cohort (AUC = 0.833) and the validation cohort (AUC = 0.734). The top five features in the random forest algorithm-based model were subdural hematoma, diffuse axonal injury, systolic and diastolic blood pressure, association between depressed fracture and subdural hematoma. Other models demonstrated good discrimination with AUC for intraoperative complication (0.675) and poor discrimination for mortality (0.366) after neurosurgical evacuation in TBI patients. Conclusion: Expansive intracranial hemorrhage is common among patients with traumatic brain injury in Uganda. Early identification of patients with subdural hematoma, diffuse axonal injury, systolic and diastolic blood pressure, association between depressed fracture and subdural hematoma, were crucial in predicting EIH and intraoperative complications.

Burden, risk factors, neurosurgical evacuation outcomes, and predictors of mortality among traumatic brain injury patients with expansive intracranial hematomas in Uganda: a mixed methods study design.

BACKGROUND: Expansive intracranial hematomas (EIH) following traumatic brain injury (TBI) continue to be a public health problem in Uganda. Data is limited regarding the neurosurgical outcomes of TBI patients. This study investigated the neurosurgical outcomes and associated risk factors of EIH among TBI patients at Mulago National Referral Hospital (MNRH). METHODS: A total of 324 subjects were enrolled using a prospective cohort study. Socio-demographic, risk factors and complications were collected using a study questionnaire. Study participants were followed up for 180 days. Univariate, multivariable, Cox regression analyses, Kaplan Meir survival curves, and log rank tests were sequentially conducted. P-values of < 0.05 at 95% Confidence interval (CI) were considered to be statistically significant. RESULTS: Of the 324 patients with intracranial hematomas, 80.6% were male. The mean age of the study participants was 37.5 ± 17.4 years. Prevalence of EIH was 59.3% (0.59 (95% CI: 0.54 to 0.65)). Participants who were aged 39 years and above; PR = 1.54 (95% CI: 1.20 to 1.97; P = 0.001), and those who smoke PR = 1.21 (95% CI: 1.00 to 1.47; P = 0.048), and presence of swirl sign PR = 2.26 (95% CI: 1.29 to 3.95; P = 0.004) were found to be at higher risk for EIH. Kaplan Meier survival curve indicated that mortality at the 16-month follow-up was 53.4% (95% CI: 28.1 to 85.0). Multivariate Cox regression indicated that the predictors of mortality were old age, MAP above 95 mmHg, low GCS, complications such as infection, spasticity, wound dehiscence, CSF leaks, having GOS < 3, QoLIBRI < 50, SDH, contusion, and EIH. CONCLUSION: EIH is common in Uganda following RTA with an occurrence of 59.3% and a 16-month higher mortality rate. An increased age above 39 years, smoking, having severe systemic disease, and the presence of swirl sign are independent risk factors. Old age, MAP above 95 mmHg, low GCS, complications such as infection, spasticity, wound dehiscence, CSF leaks, having a GOS < 3, QoLIBRI < 50, ASDH, and contusion are predictors of mortality. These findings imply that all patients with intracranial hematomas (IH) need to be monitored closely and a repeat CT scan to be done within a specific period following their initial CT scan. We recommend the development of a protocol for specific surgical and medical interventions that can be implemented for patients at moderate and severe risk for EIH.

One-Pot Synthesis of Substituted 2-Amino Isonicotinic Acids: Reminiscent of the Guareschi-Thorpe Condensation.

This work describes a concise manner to make a wide variety of mono- or disubstituted 2-amino isonicotinic acids via the corresponding 2,4-dioxo-carboxylic acid ethyl esters and ethyl 3-amino-3-iminopropionate hydrochloride. The reaction likely proceeds through an in situ decarboxylation process and is reminiscent of the Guareschi-Thorpe Condensation.

In vitro activity of omadacycline against pathogens isolated from Mainland China during 2017-2018.

Antibiotic resistance of bacterial pathogens isolated in China is a major concern. Omadacycline is a novel tetracycline derivative that has been approved for use in skin infections and community-acquired pneumonia. This study was conducted to determine the in vitro activity of omadacycline against a large collection of patient isolate medical centers across Mainland China. A total of 1041 recent clinical isolates are obtained from patients hospitalized in 29 provinces and municipalities across China. The in vitro activity of omadacycline and comparator agents was assessed using the microbroth dilution methodology. Omadacycline was active against methicillin-susceptible and -resistant Staphylococcus aureus with MIC90 values of 0.25 and 1 mg/L, respectively. All isolates of Enterococcus faecalis and Enterococcus faecium, including vancomycin-resistant isolates, were inhibited by ≤ 0.25 mg/L of omadacycline. It was active against Streptococcus pneumoniae irrespective of susceptibility to penicillin or macrolides (MIC90 =0.12 mg/L). The minimum inhibitory concentration (MIC) distribution of omadacycline was nearly identical against (extended-spectrum beta-lactamases) ESBL-positive, ESBL-negative, and carbapenemase-producing Escherichia coli (MIC90 = 4 mg/L). Omadacycline also showed good activity against Acinetobacter baumannii, inhibiting all isolates at ≤ 8 mg/L. Against Hemophilus influenzae and Moraxella catarrhalis, the MICs of omadacycline were low and not influenced by the presence of ß-lactamase. Overall, the activity of omadacycline was very good against isolates commonly associated with skin infections and pneumonia, and the susceptibility of Chinese isolates was similar to that reported for these pathogens from large surveillance studies outside China. This suggests that omadacycline could be an option for treatment of these infections in Chinese patients.