Everything old is new again. revisiting hypophysectomy for the treatment of refractory cancer-related pain: a systematic review.

Cancer-related pain is a common and debilitating condition that can significantly affect the quality of life of patients. Opioids, NSAIDs, and antidepressants are among the first-line therapies, but their efficacy is limited or their use can be restricted due to serious side effects. Neuromodulation and lesioning techniques have also proven to be a valuable instrument for managing refractory pain. For patients who have exhausted all standard treatment options, hypophysectomy may be an effective alternative treatment. We conducted a comprehensive systematic review of the available literature on PubMed and Scielo databases on using hypophysectomy to treat refractory cancer-related pain. Data extraction from included studies included study design, treatment model, number of treated patients, sex, age, Karnofsky Performance Status (KPS) score, primary cancer site, lead time from diagnosis to treatment, alcohol injection volume, treatment data, and clinical outcomes. Statistical analysis was reported using counts (N, %) and means (range). The study included data from 735 patients from 24 papers treated with hypophysectomy for refractory cancer-related pain. 329 cancer-related pain patients were treated with NALP, 216 with TSS, 66 with RF, 55 with Y90 brachytherapy, 51 with Gamma Knife radiosurgery (GK), and 18 with cryoablation. The median age was 58.5 years. The average follow-up time was 8.97 months. Good pain relief was observed in 557 out of 735 patients, with complete pain relief in 108 out of 268 patients. Pain improvement onset was observed 24 h after TSS, a few days after NALP or cryoablation, and a few days to 4 weeks after GK. Complications varied among treatment modalities, with diabetes insipidus (DI) being the most common complication. Although mostly forgotten in modern neurosurgical practice, hypophysectomy is an attractive option for treating refractory cancer-related pain after failure of traditional therapies. Radiosurgery is a promising treatment modality due to its high success rate and reduced risk of complications.

Resting-State EEG Signature of Early Consciousness Recovery in Comatose Patients with Traumatic Brain Injury.

BACKGROUND: Resting-state electroencephalography (rsEEG) is usually obtained to assess seizures in comatose patients with traumatic brain injury (TBI). We aim to investigate rsEEG measures and their prediction of early recovery of consciousness in patients with TBI. METHODS: This is a retrospective study of comatose patients with TBI who were admitted to a trauma center (October 2013 to January 2022). Demographics, basic clinical data, imaging characteristics, and EEGs were collected. We calculated the following using 10-min rsEEGs: power spectral density, permutation entropy (complexity measure), weighted symbolic mutual information (wSMI, global information sharing measure), Kolmogorov complexity (Kolcom, complexity measure), and heart-evoked potentials (the averaged EEG signal relative to the corresponding QRS complex on electrocardiography). We evaluated the prediction of consciousness recovery before hospital discharge using clinical, imaging, and rsEEG data via a support vector machine. RESULTS: We studied 113 of 134 (84%) patients with rsEEGs. A total of 73 (65%) patients recovered consciousness before discharge. Patients who recovered consciousness were younger (40 vs. 50 years, p = 0.01). Patients who recovered also had higher Kolcom (U = 1688, p = 0.01), increased beta power (U = 1,652 p = 0.003) with higher variability across channels (U = 1534, p = 0.034) and epochs (U = 1711, p = 0.004), lower delta power (U = 981, p = 0.04), and higher connectivity across time and channels as measured by wSMI in the theta band (U = 1636, p = 0.026; U = 1639, p = 0.024) than those who did not recover. The area under the receiver operating characteristic curve for rsEEG was higher than that for clinical data (using age, motor response, pupil reactivity) and higher than that for the Marshall computed tomography classification (0.69 vs. 0.66 vs. 0.56, respectively; p < 0.001). CONCLUSIONS: We describe the rsEEG signature in recovery of consciousness prior to discharge in comatose patients with TBI. rsEEG measures performed modestly better than the clinical and imaging data in predicting recovery.

Resting-State EEG Signature of Early Consciousness Recovery in Comatose Traumatic Brain Injury Patients.

Background Resting-state electroencephalogram (rsEEG) is usually obtained to assess seizures in comatose patients with traumatic brain injury (TBI) patients. We aim to investigate rsEEG measures and their prediction of early recovery of consciousness in comatose TBI patients. Methods This is a retrospective study of comatose TBI patients who were admitted to a level-1 trauma center (10/2013-1/2022). Demographics, basic clinical data, imaging characteristics, and EEG data were collected. We calculated using 10-minute rsEEGs: power spectral density (PSD), permutation entropy (PE - complexity measure), weighted symbolic-mutual-information (wSMI - global information sharing measure), Kolmogorov complexity (Kolcom - complexity measure), and heart-evoked potentials (HEP - the averaged EEG signal relative to the corresponding QRS complex on electrocardiogram). We evaluated the prediction of consciousness recovery before hospital discharge using clinical, imaging, rsEEG data via Support Vector Machine with a linear kernel (SVM). Results We studied 113 (out of 134, 84%) patients with rsEEGs. A total of 73 (65%) patients recovered consciousness before discharge. Patients who recovered consciousness were younger (40 vs. 50, p .01). Patients who recovered consciousness had higher Kolcom (U = 1688, p = 0.01,), increased beta power (U = 1652 p = 0.003), with higher variability across channels ( U = 1534, p = 0.034), and epochs (U = 1711, p = 0.004), lower delta power (U = 981, p = 0.04) and showed higher connectivity across time and channels as measured by wSMI in the theta band (U = 1636, p = .026, U = 1639, p = 0.024) than those who didn't recover. The ROC-AUC improved from 0.66 (using age, motor response, pupils' reactivity, and CT Marshall classification) to 0.69 (p < 0.001) when adding rsEEG measures. Conclusion We describe the rsEEG EEG signature in recovery of consciousness prior to discharge in comatose TBI patients. Resting-state EEG measures improved prediction beyond the clinical and imaging data.