EEG with co-registered electrocardiography was recorded during at least two interictal epileptiform EEG discharges in each of 11 patients who later suffered from sudden unexpected death in epilepsy (SUDEP), and from another 11 age and sex matched patients, also with uncontrolled tonic-clonic seizures, drawn from the same centre who were still alive at the time of investigation (non-SUDEPs). A corrected QT interval for rate (QTc) was obtained and a mean value calculated for the period immediately prior to discharge, during discharge and immediately post discharge. Mean QTc was also obtained interictally without discharge. There was a significant (P = 0.01) increase in the mean QTc during discharge compared to that measured interictally without discharge for the whole population of SUDEPs and non-SUDEPs, and this was maintained for the SUDEPs alone (P = 0.02) but did not hold for the non-SUDEP group alone. Although reaching statistical significance, increases in mean QTc in SUDEP patients only exceeded currently accepted upper limits in one case, and then only marginally. The clinical significance of these findings merits further investigation.

OBJECTIVEPostoperative ileus (POI) is associated with abdominal pain, nausea, vomiting, and delayed mobilization that in turn lead to diminished patient satisfaction, increased hospital length of stay (LOS), and increased healthcare costs. In this study, the authors developed a risk assessment scale to predict the likelihood of developing POI following spinal surgery.METHODSThe authors undertook a retrospective review of a prospectively maintained registry of consecutive patients who underwent arthrodesis/fusion surgeries between May 2013 and December 2017. They extracted clinical information, including cumulative intraoperative and postoperative opioid doses using standardized converted morphine milligram equivalent (MME) values. Univariate and multivariate analyses were performed and several categorical and continuous variables were evaluated in a binary logistic regression model built with backward elimination to assess for independent predictors. A points-based prediction model was developed and validated to determine the risk of POI.RESULTSA total of 334 patients who underwent spinal fusion surgeries were included. Fifty-six patients (16.8%) developed POI, more frequently in those who underwent long-segment surgeries compared to short-segment surgeries (33.3% vs 10.4%; p < 0.001). POI was associated with an increased LOS when compared with patients who did not develop POI (8.0 ± 4.5 days vs 4.4 ± 2.4 days; p < 0.01). The incidences of liver disease (16% vs 3.7%; p = 0.01) and substance abuse history (12.0% vs 3.2%; p = 0.04) were higher in POI patients than non-POI patients undergoing short-segment surgeries. While the incidences of preoperative opioid intake (p = 0.23) and cumulative 24-hour (87.7 MME vs 73.2 MME; p = 0.08) and 72-hour (225.6 MME vs 221.4 MME; p = 0.87) postoperative opioid administration were not different, remifentanil (3059.3 µg vs 1821.5 µg; p < 0.01) and overall intraoperative opioid (326.7 MME vs 201.7 MME; p < 0.01) dosing were increased in the POI group. The authors derived a multivariate model based on the 5 most significant factors predictive of POI (number of surgical levels, intraoperative MME, liver disease, age, and history of substance abuse) and calculated relative POI risks using a derived 32-point system.CONCLUSIONSIntraoperative opioid administration, incorporated in a comprehensive risk assessment scale, represents an early and potentially modifiable predictor of POI. These data indicate that potential preventive strategies, implemented as part of enhanced recovery after surgery protocols, could be instituted in the preoperative phase of care to reduce POI incidence.

OBJECTIVE Despite the increasing incidence of spinal epidural abscess (SEA), the baseline parameters potentially predictive of treatment failure remain poorly characterized. In this study, the authors identify the relevant baseline parameters that predict multimodal treatment failure in patients with either intravenous drug use (IVDU)–associated SEA or non-IVDU–associated SEA. METHODS The authors reviewed the electronic medical records of a large institutional series of consecutive patients with diagnosed SEA between January 2011 and December 2017 to characterize epidemiological trends as well as the complement of baseline measures that are predictive of failure after multimodal treatment in patients with and without concomitant IVDU. The independent impact of clinical and imaging factors in detecting treatment failure was assessed by performing stepwise binary logistic regression analysis. RESULTS A total of 324 consecutive patients with diagnosed SEA were identified. Overall, 226 patients (69.8%) had SEA related to other causes and 98 (30.2%) had a history of recent IVDU. While non-IVDU SEA admission rates remained constant, year-over-year admissions of patients with IVDU SEA nearly tripled. At baseline, patients with IVDU SEA were distinct in many respects including younger age, greater unemployment and disability, less frequent diabetes mellitus (DM), and more frequent methicillin-resistant Staphylococcus aureus infection. However, differences in length of stay, loss to follow-up, and treatment failure did not reach statistical significance between the groups. The authors constructed independent multivariate logistic regression models for treatment failure based on identified parameters in the two cohorts. For the non-IVDU cohort, the authors identified four variables as independent factors: DM, hepatitis B/C, osteomyelitis, and compression deformity severity. In contrast, for patients with IVDU, the authors identified three variables: albumin, endocarditis, and endplate destruction. Receiver operating characteristic and area under the curve (AUC) analyses were undertaken for the multivariate models predicting the likelihood of treatment failure in the two cohorts (AUC = 0.88 and 0.89, respectively), demonstrating that the derived models could adequately predict the risk of multimodal treatment failure. Treatment failure risk factor point scales were derived for the identified variables separately for both cohorts. CONCLUSIONS Patients with IVDU SEA represent a unique population with a distinct set of baseline parameters that predict treatment failure. Identification of relevant prognosticating factors will allow for the design of tailored treatment and follow-up regimens.

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