Background. Accurate prediction of clinical impairment in upper-extremity motor function following therapy in chronic stroke patients is a difficult task for clinicians but is key in prescribing appropriate therapeutic strategies. Machine learning is a highly promising avenue with which to improve prediction accuracy in clinical practice. Objectives. The objective was to evaluate the performance of 5 machine learning methods in predicting postintervention upper-extremity motor impairment in chronic stroke patients using demographic, clinical, neurophysiological, and imaging input variables. Methods. A total of 102 patients (female: 31%, age 61 ± 11 years) were included. The upper-extremity Fugl-Meyer Assessment (UE-FMA) was used to assess motor impairment of the upper limb before and after intervention. Elastic net (EN), support vector machines, artificial neural networks, classification and regression trees, and random forest were used to predict postintervention UE-FMA. The performances of methods were compared using cross-validated R2. Results. EN performed significantly better than other methods in predicting postintervention UE-FMA using demographic and baseline clinical data (median [Formula: see text] P < .05). Preintervention UE-FMA and the difference in motor threshold (MT) between the affected and unaffected hemispheres were the strongest predictors. The difference in MT had greater importance than the absence or presence of a motor-evoked potential (MEP) in the affected hemisphere. Conclusion. Machine learning methods may enable clinicians to accurately predict a chronic stroke patient’s postintervention UE-FMA. Interhemispheric difference in the MT is an important predictor of chronic stroke patients’ response to therapy and, therefore, could be included in prospective studies.
We report a case of a 59-year-old man with idiopathic ventricular fibrillation storm. Ventricular fibrillation was pause-dependent and triggered by an early-coupled right ventricular premature complex. The characteristic premature beat was mapped and successfully ablated from Purkinje fibers of the moderator band.
Merkel cell carcinoma (MCC) is a rare and aggressive epidermal cancer. We conducted a retrospective study and literature review to investigate the impact that radiation therapy has on local, regional, and distant control aspart of the oncologic managementofMCC of the headand neck and tofurther elucidate the role of radiation therapy with regard toregional controlfor theclinically uninvolved neck.
Introduction
Contact force (CF) guided ablation of paroxysmal atrial fibrillation (PAF) with stable catheter‐tissue contact optimizes clinical success and may increase an operator's ability to achieve pulmonary vein isolation (PVI) in a single encirclement. First pass PVI reduces procedure time but the relationship with long term clinical success is not well understood. This study evaluated patient characteristics and procedural details as predictors of 1‐year clinical success after PAF ablation, including first pass isolation.
Methods
Consecutive de novo PAF ablations were performed with a porous tip CF catheter in 2017 and 2018. All ablations used wide‐area circumferential ablation, with first pass isolation captured separately for the left and right pulmonary veins (PVs). CF was held between 10 and 20 g and the catheter was moved every 10–20 s. Radiofrequency energy was set at 40–45 W throughout the atrium. Patient characteristics and procedural details were tested for association with clinical success, defined as freedom from recurrent atrial tachyarrhythmia through 1 year.
Results
A total of 404 patients were included in the study. Clinical success at 1 year was 86.6%. Achieving first pass isolation on at least one ipsilateral PV pair was the most significant predictor of clinical success (p = .0126). After controlling for first pass isolation, only recurrence within the 90‐day blanking period was independently predictive (p = .0015). First pass isolation was not associated with early recurrence (p = .2454).
Conclusion
In a real‐world setting, first pass isolation was highly predictive of 12‐month clinical success after CF‐guided ablation in a PAF population.
Background and Purpose
The potential for adaptive plasticity in the post-stroke brain is difficult to estimate, as is the demonstration of central nervous system (CNS) target engagement of drugs that show promise in facilitating stroke recovery. We set out to determine if paired associative stimulation (PAS) can be used (a) as an assay of CNS plasticity in patients with chronic stroke, and (b) to demonstrate CNS engagement by memantine, a drug which has potential plasticity-modulating effects for use in motor recovery following stroke.
Methods
We examined the effect of PAS in fourteen participants with chronic hemiparetic stroke at five time-points in a within-subjects repeated measures design study: baseline off-drug, and following a week of orally administered memantine at doses of 5, 10, 15, and 20 mg, comprising a total of seventy sessions. Each week, MEP amplitude pre and post-PAS was assessed in the contralesional hemisphere as a marker of enhanced or diminished plasticity. Strength and dexterity were recorded each week to monitor motor-specific clinical status across the study period.
Results
We found that MEP amplitude was significantly larger after PAS in baseline sessions off-drug, and responsiveness to PAS in these sessions was associated with increased clinical severity. There was no observed increase in MEP amplitude after PAS with memantine at any dose. Motor threshold (MT), strength, and dexterity remained unchanged during the study.
Conclusion
Paired associative stimulation successfully induced corticospinal excitability enhancement in chronic stroke subjects at the group level. However, this response did not occur in all participants, and was associated with increased clinical severity. This could be an important way to stratify patients for future PAS-drug studies. PAS was suppressed by memantine at all doses, regardless of responsiveness to PAS off-drug, indicating CNS engagement.
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