A systematic review and meta-analysis of unplanned hospital visits and re-admissions following radical prostatectomy for prostate cancer.

INTRODUCTION: Unplanned visits (UPV) - re-admissions and emergency room (ER) visits - are markers of healthcare system quality. Radical prostatectomy (RP) is a commonly performed cancer procedure, where variation in UPV represents a gap in care for prostate cancer patients. Here, we systematically synthesize the rates, reasons, predictors, and interventions for UPV after RP to inform evidence-based quality improvement (QI) initiatives. METHODS: A systematic review was performed for studies from 2000-2020 using keywords: "re-admission," "emergency room/department," "unplanned visit," and "prostatectomy." Studies that focused on UPV following RP and that reported rates, reasons, predictors, or interventions, were included. Data was extracted via a standardized form. Meta-analysis was completed. RESULTS: Sixty studies, with 406 107 RP patients, were eligible; 16 028 UPV events (approximately 5%) were analyzed from 317 050 RP patients. UPV rates after RP varied between studies (ER visit range 6-24%; re-admissions range 0-56%). The 30-day and 90-day ER visit rates were 12% and 14%, respectively; the 30-day and 90-day re-admission rates were 4% and 9%, respectively. A total of 55% of all re-admissions after RP are directly due to postoperative genitourinary (GU)-related complications, such as strictures, obstructions, fistula, bladder-related, incontinence, urine leak, renal problems, and other unspecified urinary complications. The next most common re-admission reasons were anastomosis-related, infection-related, cardiovascular/pulmonary events, and wound-related issues. Thirty-four percent of all ER visits after RP are directly due to urine-related issues, such as retention, urinoma, obstruction, leak, and catheter problems. The next most common ER visit reasons were abdominal/gastrointestinal issues, infection-related, venous thromboembolic events, and wound-related issues. Predictors for increased re-admission included: open RP, lymph node dissection, Charlson comorbidity index ≥2, low surgeon/hospital case volume, and socioeconomic determinants of health. Of the 10 interventions evaluated, a 3.4% average reduction in UPV rate was observed, highlighting an approximate two-fold decrease. Meta-analysis demonstrated a significant benefit of interventions over controls, with odds ratio 0.62 (95% confidence interval 0.46-0.84). Interventions that used multidisciplinary, nurse-centered, programs, with patient self-care/empowerment were more beneficial than algorithmic patient care pathways and preoperative patient education. CONCLUSIONS: Twenty years of international, retrospective experience suggests UPV after RP are often related to GU complications and infection- or wound-related factors. QI interventions to reduce UPV should target these factors. While many re-admissions after RP appear to be unavoidable, ER visits have more opportunity for volume reduction by QI. The interventions evaluated herein have the potential to reduce UPV after RP.

EEG source localization: Sensor density and head surface coverage.

BACKGROUND: The accuracy of EEG source localization depends on a sufficient sampling of the surface potential field, an accurate conducting volume estimation (head model), and a suitable and well-understood inverse technique. The goal of the present study is to examine the effect of sampling density and coverage on the ability to accurately localize sources, using common linear inverse weight techniques, at different depths. Several inverse methods are examined, using the popular head conductivity. NEW METHOD: Simulation studies were employed to examine the effect of spatial sampling of the potential field at the head surface, in terms of sensor density and coverage of the inferior and superior head regions. In addition, the effects of sensor density and coverage are investigated in the source localization of epileptiform EEG. RESULTS: Greater sensor density improves source localization accuracy. Moreover, across all sampling density and inverse methods, adding samples on the inferior surface improves the accuracy of source estimates at all depths. COMPARISON WITH EXISTING METHODS: More accurate source localization of EEG data can be achieved with high spatial sampling of the head surface electrodes. CONCLUSIONS: The most accurate source localization is obtained when the voltage surface is densely sampled over both the superior and inferior surfaces.

Localizing movement-related primary sensorimotor cortices with multi-band EEG frequency changes and functional MRI.

Electroencephalographic (EEG) oscillations in multiple frequency bands can be observed during functional activity of the cerebral cortex. An important question is whether activity of focal areas of cortex, such as during finger movements, is tracked by focal oscillatory EEG changes. Although a number of studies have compared EEG changes to functional MRI hemodynamic responses, we can find no previous research that relates the fMRI hemodynamic activity to localization of the multiple EEG frequency changes observed in motor tasks. In the present study, five participants performed similar thumb and finger movement tasks in parallel EEG and functional MRI studies. We examined changes in five frequency bands (from 5-120 Hz) and localized them using 256 dense-array EEG (dEEG) recordings and high-resolution individual head models. These localizations were compared with fMRI localizations in the same participants. Results showed that beta-band (14-30 Hz) desynchronizations (power decreases) were the most robust effects, appearing in all individuals, consistently localized to the hand region of the primary motor cortex, and consistently aligned with fMRI localizations.

Methods for examining electrophysiological coherence in epileptic networks.

Epilepsy may reflect a focal abnormality of cerebral tissue, but the generation of seizures typically involves propagation of abnormal activity through cerebral networks. We examined epileptiform discharges (spikes) with dense array electroencephalography (dEEG) in five patients to search for the possible engagement of pathological networks. Source analysis was conducted with individual electrical head models for each patient, including sensor position measurement for registration with MRI with geodesic photogrammetry; tissue segmentation and skull conductivity modeling with an atlas skull warped to each patient's MRI; cortical surface extraction and tessellation into 1 cm(2) equivalent dipole patches; inverse source estimation with either minimum norm or cortical surface Laplacian constraints; and spectral coherence computed among equivalent dipoles aggregated within Brodmann areas with 1 Hz resolution from 1 to 70 Hz. These analyses revealed characteristic source coherence patterns in each patient during the pre-spike, spike, and post-spike intervals. For one patient with both spikes and seizure onset localized to a single temporal lobe, we observed a cluster of apparently abnormal coherences over the involved temporal lobe. For the other patients, there were apparently characteristic coherence patterns associated with the discharges, and in some cases these appeared to reflect abnormal temporal lobe synchronization, but the coherence patterns for these patients were not easily related to an unequivocal epileptogenic zone. In contrast, simple localization of the site of onset of the spike discharge, and/or the site of onset of the seizure, with non-invasive 256 dEEG was useful in predicting the characteristic site of seizure onset for those cases that were verified by intracranial EEG and/or by surgical outcome.