Background: Estimating operative time with low accuracy and precision leads to suboptimal scheduling of available operating rooms (ORs) and waste of healthcare resources. We aimed to develop a predictive machine learning (ML) model for operative time using our institutional data to improve the scheduling of neurosurgical ORs, minimize waste, and maximize resource utilization. Methods: We developed a predictive model using our institution’s multicenter registry, which included diverse neurosurgical cases across three tertiary hospitals. We applied multiple ML techniques, including linear regression, support vector regression, deep neural networks, and extreme gradient boosting regression (XGBR). The best model was combined with the first fit decreasing bin-packing algorithm to create a practical OR scheduling system based on prior data. Results: The XGBR model exhibited the best performance, with lower mean absolute errors (MAEs) (root mean squared error: 52.24, MAE: 37.25) and higher R2 (0.76) values than other models. Implementing this model in a simulated OR scheduling scenario using institutional data, we successfully scheduled 30 random procedures with minimal residual time, such that the model ran out of procedures for the week with 86 and 171 min remaining in the cranial and spinal ORs, respectively, demonstrating potential efficiency gains. The cranial procedures were scheduled over 4 days and spinal procedures over 6 days, optimizing available OR time. Conclusion: Integrating ML models into operative time prediction can significantly improve the accuracy and efficiency of surgical schedules. This approach minimizes wasted OR time and enhances resource allocation, potentially improving patient outcomes and satisfaction by reducing waiting times.
Spoken Language Alterations can Predict Phenoconversion in Isolated Rapid Eye Movement Sleep Behavior Disorder: A Multicenter Study
ObjectiveThis study assessed the relationship between speech and language impairment and outcome in a multicenter cohort of isolated/idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD).MethodsPatients with iRBD from 7 centers speaking Czech, English, German, French, and Italian languages underwent a detailed speech assessment at baseline. Story‐tale narratives were transcribed and linguistically annotated using fully automated methods based on automatic speech recognition and natural language processing algorithms, leading to the 3 distinctive linguistic and 2 acoustic patterns of language deterioration and associated composite indexes of their overall severity. Patients were then prospectively followed and received assessments for parkinsonism or dementia during follow‐up. The Cox proportional hazard was performed to evaluate the predictive value of language patterns for phenoconversion over a follow‐up period of 5 years.ResultsOf 180 patients free of parkinsonism or dementia, 156 provided follow‐up information. After a mean follow‐up of 2.7 years, 42 (26.9%) patients developed neurodegenerative disease. Patients with higher severity of linguistic abnormalities (hazard ratio [HR = 2.35]) and acoustic abnormalities (HR = 1.92) were more likely to develop a defined neurodegenerative disease, with converters having lower content richness (HR = 1.74), slower articulation rate (HR = 1.58), and prolonged pauses (HR = 1.46). Dementia‐first (n = 16) and parkinsonism‐first with mild cognitive impairment (n = 9) converters had higher severity of linguistic abnormalities than parkinsonism‐first with normal cognition converters (n = 17).InterpretationAutomated language analysis might provide a predictor of phenoconversion from iRBD into synucleinopathy subtypes with cognitive impairment, and thus can be used to stratify patients for neuroprotective trials. ANN NEUROL 2024;95:530–543
Contemporary diagnostic visual and automated polysomnographic REM sleep without atonia thresholds in isolated REM sleep behavior disorder
Abstract Study Objectives Post-traumatic stress disorder (PTSD) and rapid eye movement (REM) sleep behavior disorder (RBD) share some common features including prominent nightmares and sleep disturbances. We aimed to comparatively analyze REM sleep without atonia (RSWA) between patients with chronic PTSD with and without dream enactment behavior (DEB), isolated RBD (iRBD), and controls. Methods In this retrospective study, we comparatively analyzed 18 PTSD with DEB (PTSD+DEB), 18 PTSD without DEB, 15 iRBD, and 51 controls matched for age and sex. We reviewed medical records to determine PTSD clinical features and quantitatively analyzed RSWA. We used nonparametric analyses to compare clinical and polysomnographic features. Results PTSD patients, both with and without DEB, had significantly higher RSWA than controls (all p < .025, excepting submentalis phasic duration in PTSD+DEB). Most RSWA measures were also higher in PTSD+DEB than in PTSD without DEB patients (all p < .025). Conclusions PTSD patients have higher RSWA than controls, whether DEB is present or not, indicating that REM sleep atonia control is abnormal in chronic PTSD. Further prospective studies are needed to determine whether neurodegenerative risk and disease markers similar to RBD might occur in PTSD patients.
Objective sleep profile in LGI1/CASPR2 autoimmunity
AbstractStudy ObjectivesRapid eye movement (REM) sleep behavior disorder (RBD) and other sleep disturbances are frequent in leucine-rich, glioma inactivated protein 1-IgG (LGI1) and contactin-associated protein 2-IgG (CASPR2) autoimmunity, yet polysomnographic analyses of these disorders remain limited. We aimed to characterize clinical presentations and analyze polysomnographic manifestations, especially quantitative REM sleep without atonia (RSWA) in LGI1/CASPR2-IgG seropositive (LGI/CASPR2+) patients.MethodsWe retrospectively analyzed clinical and polysomnographic features and quantitative RSWA between LGI1+/CASPR2+ patients and age-sex matched controls. Groups were compared with Wilcoxon rank-sum and chi-square tests. Combined submentalis and anterior tibialis (SM + AT) RSWA was the primary outcome.ResultsAmong 11 (LGI1+, n = 9; CASPR2+, n = 2) patients, Morvan syndrome sleep features were present in seven (63.6%) LGI1+/CASPR2+ patients, with simultaneous insomnia and dream enactment behavior (DEB) in three (27.3%), and the most common presenting sleep disturbances were DEB (n = 5), insomnia (n = 5), and sleep apnea (n = 8; median apnea-hypopnea index = 15/hour). Median Epworth Sleepiness Scale was nine (range 3–24; n = 10), with hypersomnia in four (36.4%). LGI1+/CASPR2+ patients had increased N1 sleep (p = .02), decreased REM sleep (p = .001), and higher levels of SM + AT any RSWA (p < .001). Eight of nine (89%) LGI1+ exceeded RBD RSWA thresholds (DEB, n = 5; isolated RSWA, n = 3). RSWA was greater in AT than SM. All 10 LGI1+/CASPR2+ patients treated with immunotherapy benefitted, and 5/10 had improved sleep disturbances.ConclusionsLGI1/CASPR2-IgG autoimmunity is associated with prominent dream enactment, insomnia, RSWA, sleep apnea, and shallower sleep. Polysomnography provides objective disease markers in LGI1+/CASPR2+ autoimmunity and immunotherapy may benefit associated sleep disturbances.
Speech Biomarkers in Rapid Eye Movement Sleep Behavior Disorder and Parkinson Disease
ObjectiveThis multilanguage study used simple speech recording and high‐end pattern analysis to provide sensitive and reliable noninvasive biomarkers of prodromal versus manifest α‐synucleinopathy in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and early‐stage Parkinson disease (PD).MethodsWe performed a multicenter study across the Czech, English, German, French, and Italian languages at 7 centers in Europe and North America. A total of 448 participants (337 males), including 150 with iRBD (mean duration of iRBD across language groups 0.5–3.4 years), 149 with PD (mean duration of disease across language groups 1.7–2.5 years), and 149 healthy controls were recorded; 350 of the participants completed the 12‐month follow‐up. We developed a fully automated acoustic quantitative assessment approach for the 7 distinctive patterns of hypokinetic dysarthria.ResultsNo differences in language that impacted clinical parkinsonian phenotypes were found. Compared with the controls, we found significant abnormalities of an overall acoustic speech severity measure via composite dysarthria index for both iRBD (p = 0.002) and PD (p < 0.001). However, only PD (p < 0.001) was perceptually distinct in a blinded subjective analysis. We found significant group differences between PD and controls for monopitch (p < 0.001), prolonged pauses (p < 0.001), and imprecise consonants (p = 0.03); only monopitch was able to differentiate iRBD patients from controls (p = 0.004). At the 12‐month follow‐up, a slight progression of overall acoustic speech impairment was noted for the iRBD (p = 0.04) and PD (p = 0.03) groups.InterpretationAutomated speech analysis might provide a useful additional biomarker of parkinsonism for the assessment of disease progression and therapeutic interventions. ANN NEUROL 2021;90:62–75
Multisite validation of a simple electronic health record algorithm for identifying diagnosed obstructive sleep apnea
Accurate antemortem diagnosis of parkinsonism is primarily based on clinical evaluation with limited biomarkers. We evaluated the diagnostic utility of quantitative rapid eye movement (REM) sleep without atonia analysis in the submentalis and anterior tibialis muscles in parkinsonian patients (53 synucleinopathy, 24 tauopathy). Receiver operating characteristic curves determined REM sleep without atonia cutoffs distinguishing synucleinopathies from tauopathies. Elevated submentalis muscle activity was highly sensitive (70–77%) and specific (95–100%) in distinguishing synucleinopathy from tauopathy. In contrast, anterior tibialis synucleinopathy discrimination was poor. Our results suggest that elevated submentalis REM sleep without atonia appears to be a potentially useful biomarker for presumed synucleinopathy etiologies in parkinsonism. ANN NEUROL 2019;86:969–974
Normative and isolated rapid eye movement sleep without atonia in adults without REM sleep behavior disorder
Abstract Study Objectives Values for normative REM sleep without atonia (RSWA) remain unclear. Older age and male sex are associated with greater RSWA, and isolated elevated RSWA has been reported. We aimed to describe normative RSWA and characterize isolated RSWA frequency in adults without REM sleep behavior disorder (RBD). Methods We visually quantified phasic, “any,” and tonic RSWA in the submentalis (SM) and anterior tibialis (AT) muscles, and the automated Ferri REM Atonia Index during polysomnography in adults without RBD aged 21–88. We calculated RSWA percentiles across age and sex deciles and compared RSWA in older (≥ 65) versus younger (<65) men and women. Isolated RSWA (exceeding diagnostic RBD cutoffs, or >95th percentile) frequency was also determined. Results Overall, 95th percentile RSWA percentages were SM phasic, any, tonic = 8.6%, 9.1%, 0.99%; AT phasic and “any” = 17.0%; combined SM/AT phasic, “any” = 22.3%, 25.5%; and RAI = 0.85. Most phasic RSWA burst durations were ≤1.0 s (85th percentiles: SM = 1.07, AT = 0.86 seconds). Older men had significantly higher AT RSWA than older women and younger patients (all p < 0.04). Twenty-nine (25%, 18 men) had RSWA exceeding the cohort 95th percentile, while 17 (14%, 12 men) fulfilled diagnostic cutoffs for phasic or automated RBD RSWA thresholds. Conclusions RSWA levels are highest in older men, mirroring the demographic characteristics of RBD, suggesting that older men frequently have altered REM sleep atonia control. These data establish normative adult RSWA values and thresholds for determination of isolated RSWA elevation, potentially aiding RBD diagnosis and discussions concerning incidental RSWA in clinical sleep medicine practice.