Citations

Study Design: Analysis of prospectively collected data. Objective: To assess if systemic illness severity affects cervical spondylotic myelopathy (CSM) surgery outcomes. Summary of Background Data: It remains unclear if CSM patients with poor physical status/severe systemic illness benefit as much from surgery as those in good condition. Methods: Using the Quality Outcomes Database CSM cohort and the American Association of Anesthesiology (ASA) grade as a surrogate for illness burden, we compared patients with (ASA 3–4) and without (ASA 1–2) severe systemic illness, including rates of readmission and 24-month minimal clinically important differences (MCID) achievement for patient-reported outcomes (PROs)—numerical rating score (NRS) arm and neck pain, neck pain-related disability (NDI), and quality of life (EQ-5D). Results: Of 1141 CSM patients, 1062 had ASA grades recorded. Of these 1062 patients, 70.2% had a 2-year follow-up for mJOA, and 81%–84% had a follow-up for NRS arm and neck, NDI, and EQ-5D. Five hundred twenty-one patients (49.1%) had mild (ASA 1–2) and 541 (50.9%) had severe systemic illness (ASA 3–4). The severe disease cohort was older (63.3±11.0 vs. 57.4±11.7), had higher BMI (31.4±7.0 vs. 28.9±5.6), had more comorbidities (diabetes, coronary artery disease, depression), and had less independent ambulation (71.3% vs. 90.6%) ( P <0.05). At baseline, severe disease patients had worse NRS arm (5.2±3.5 vs. 4.7±3.4) and neck (5.5±3.2 vs. 5.1±3.3) pain, NDI (40.5±20.1 vs. 36.8±21.0), and EQ-5D (0.53±0.22 vs. 0.59±0.22) scores ( P <0.05). Perioperatively, the severe disease cohort had longer hospitalizations (2.4±2.6 vs. 1.7±2.0 days) and increased nonhome discharges (17% vs. 5%) ( P <0.05). The severe disease cohort had higher 90-day readmissions (7.6% vs. 2.5%), including surgery-related (3.7% vs. 1.5%) and non–surgery-related reasons (3.9% vs. 1.0%) ( P <0.05). On multivariate analysis, increased ASA grade was significantly associated with 90-day readmissions (OR: 2.55 per 1-grade increase, 95% CI: 1.38–4.83). However, both severe and mild disease cohorts had similarly high rates of achieving 2-year MCID for mJOA (67.5% vs. 66.0%), NRS arm (72.0% vs. 74.1%), neck (69.5% vs. 69.4%) pain, NDI (63.1% vs. 68.1%), and EQ-5D (67.9% vs. 66.9%) ( P >0.05). Conclusion: Patients with severe systemic illness (higher ASA) have worse baseline PROs and higher 90-day readmissions. However, they achieve similar MCID rates for mJOA and all measured PROs 2 years postoperatively.

Abstract Purpose/Background Clozapine was approved in the United States (US) using 1989 regulations and knowledge. After 30 years, many sections of the US package insert (PI) are outdated. Methods We comprehensively reviewed the literature to propose PI updates. We present the information in 2 articles. In Part I, we focus on basic pharmacology based on 407 relevant articles. Part II focuses on clinical aspects and pharmacovigilance. Findings/Results Based on more recent expectations of Food and Drug Administration regulations, we reviewed clozapine basic pharmacology including the following: 1) clearance, 2) pharmacokinetics and pharmacodynamics, and 3) monitoring tools. We identified 9 major problems in the basic pharmacological sections of the PI including the following: 1) in vivo studies indicate that clozapine is dependent on CYP1A2 for its metabolism, 2) the minor role of CYP2D6 in clozapine metabolism requires removing the PI recommendation to lower clozapine doses in CYP2D6 poor metabolizers, 3) in nontoxic concentrations CYP3A4 has a minor role in clozapine metabolism and potent CYP3A4 inhibitors lack clinically relevant effects, 4) several drug-drug interactions need to be updated based on recent literature, 5) systemic inflammation may decrease clozapine metabolism and increase the risk of clozapine intoxication, 6) obesity may decrease clozapine metabolism, 7) patients of Asian and Indigenous American ancestry need lower clozapine doses, 8) personalized titration and c-reactive protein monitoring should be considered until prospective studies are available, and 9) the half-life section needs to be modified to acknowledge that single dosing at night is frequent in the US. Implications/Conclusions An improvement in the US clozapine PI may lead to improvement in PIs worldwide.

Abstract Purpose/Background This is the second part of a 2-part article that proposes improving the United States (US) clozapine package insert. Part II focuses on fatal outcomes and the 5 boxed warnings, 4 specifically for clozapine: severe neutropenia, seizure, orthostatic hypotension and myocarditis, and 1 for all antipsychotics (elderly with dementia). Methods US reports to the World Health Organization's global pharmacovigilance database were analyzed from clozapine's introduction to January 15, 2023. Findings/Results The US was the top reporter worldwide for clozapine with 56,003 reports and 9587 associated fatal outcomes. The 4 clozapine boxed warnings were associated with 534 fatal outcomes (218 with severe neutropenia, 131 with seizures, 125 with orthostasis, 36 with myocarditis, 24 with cardiomyopathy, and 0 with mitral valve prolapse). With no boxed warnings, pneumonia was associated with 674 fatal outcomes and increased white blood cell count (a sign of infection) with 596 fatal outcomes. After considering overlaps, pneumonia and increases in white blood cell count explained 900 fatalities, or 9.4% of 9587 fatal outcomes. The Food and Drug Administration continues to focus on severe neutropenia which was associated with only 218 or 2.3% of fatal outcomes, whereas 97.7% of fatal outcomes reported in US clozapine-treated patients had another cause. Implications/Conclusions To help prevent future deaths in clozapine-treated patients, the clozapine package insert should focus on fatal outcomes during infections. Part II offers detailed solutions regarding current boxed warnings and lack of a warning for pneumonia and other infections. The Supplementary Material includes letters of support from 124 non-US clozapine experts from 44 countries/regions who support Parts I and II.

OBJECTIVE In this study, the authors aimed to establish a supervised machine learning (ML) model based on multiple tree-based algorithms to predict long-term biochemical outcomes and intervention-free survival (IFS) after endonasal transsphenoidal surgery (ETS) in patients with Cushing’s disease (CD). METHODS The medical records of patients who underwent ETS for CD between 2013 and 2023 were reviewed. Data were collected on the patient’s baseline characteristics, intervention details, histopathology, surgical outcomes, and postoperative endocrine functions. The study’s primary outcome was IFS, and the therapeutic outcomes were labeled as "under control" or "treatment failure," depending on whether additional therapeutic interventions after primary ETS were required. The decision tree and random forest classifiers were trained and tested to predict long-term IFS based on unseen data, using an 80/20 cohort split. RESULTS Data from 150 patients, with a median follow-up period of 56 months, were extracted. In the cohort, 42 (28%) patients required additional intervention for persistent or recurrent CD. Consequently, the IFS rates following ETS alone were 83% at 3 years and 78% at 5 years. Multivariable Cox proportional hazards analysis demonstrated that a smaller tumor diameter that could be detected by MRI (hazard ratio 0.95, 95% CI 0.90–0.99; p = 0.047) was significantly associated with greater IFS. However, the lack of tumor detection on MRI was a poor predictor. The ML-based model using a decision tree model displayed 91% accuracy (95% CI 0.70–0.94, sensitivity 87.0%, specificity 89.0%) in predicting IFS in the unseen test dataset. Random forest analysis revealed that tumor size (mean minimal depth 1.67), Knosp grade (1.75), patient age (1.80), and BMI (1.99) were the four most significant predictors of long-term IFS. CONCLUSIONS The ML algorithm could predict long-term postoperative endocrinological remission in CD with high accuracy, indicating that prognosis may vary not only with previously reported factors such as tumor size, Knosp grade, gross-total resection, and patient age but also with BMI. The decision tree flowchart could potentially stratify patients with CD before ETS, allowing for the selection of personalized treatment options and thereby assisting in determining treatment plans for these patients. This ML model may lead to a deeper understanding of the complex mechanisms of CD by uncovering patterns embedded within the data.