Application of Robotic Stereotactic Assistance (ROSA) for spontaneous intracerebral hematoma aspiration and thrombolytic catheter placement.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) accounts for up to 20% of all strokes and results in 40% mortality at 30 days. Although conservative medical management is still the standard treatment for ICH patients with small hematoma, patients with residual hematoma ≤15 mL after surgery are associated with better functional outcomes and survival rates. This study reported our clinical experience with using Robotic Stereotactic Assistance (ROSA) as a safe and effective approach for stereotactic ICH aspiration and intra-clot catheter placement. METHODS: A retrospective analysis was conducted of patients with spontaneous ICH who underwent ROSA-guided ICH aspiration surgery. ROSA-guided ICH surgical techniques, an aspiration and intra-clot catheter placement protocol, and a specific operative workflow (pre-operative protocol, intraoperative procedure and postoperative management) were employed to aspirate ICH using the ROSA One Brain, and appropriate follow-up care was provided. RESULTS: From September 14, 2021 to May 4, 2022, a total of 7 patients were included in the study. Based on our workflow design, ROSA-guided stereotactic ICH aspiration effectively aspirated more than 50% of hematoma volume (or more than 30 mL for massive hematomas), thereby reducing the residual hematoma to less than 15 mL. The mean operative time of entire surgical procedure was 1.3 ± 0.3 h, with very little perioperative blood loss and no perioperative complications. No patients required catheter replacement and all patients' functional status improved. CONCLUSIONS: Within our clinical practice ROSA-guided ICH aspiration, using our established protocol and workflow, was safe and effective for reducing hematoma volume, with positive functional outcomes.

The impact of comorbidities on prolonged mechanical ventilation in patients with chronic obstructive pulmonary disease.

BACKGROUND: In patients with chronic obstructive pulmonary disease (COPD) and acute respiratory failure, approximately 10% of them are considered to be at high risk for prolonged mechanical ventilation (PMV, > 21 days). PMV have been identified as independent predictors of unfavorable outcomes. Our previous study revealed that patients aged 70 years older and COPD severity were at a significantly higher risk for PMV. We aimed to analyze the impact of comorbidities and their associated risks in patients with COPD who require PMV. METHODS: The data used in this study was collected from Kaohsiung Medical University Hospital Research Database. The COPD subjects were the patients first diagnosed COPD (index date) between January 1, 2012 and December 31, 2020. The exclusion criteria were the patients with age less than 40 years, PMV before the index date or incomplete records. COPD and non-COPD patients, matched controls were used by applying the propensity score matching method. RESULTS: There are 3,744 eligible patients with COPD in the study group. The study group had a rate of 1.6% (60 cases) patients with PMV. The adjusted HR of PMV was 2.21 (95% CI 1.44-3.40; P < 0.001) in the COPD patients than in non-COPD patients. Increased risks of PMV were found significantly for patients with diabetes mellitus (aHR 4.66; P < 0.001), hypertension (aHR 3.20; P = 0.004), dyslipidemia (aHR 3.02; P = 0.015), congestive heart failure (aHR 6.44; P < 0.001), coronary artery disease (aHR 3.11; P = 0.014), stroke (aHR 6.37; P < 0.001), chronic kidney disease (aHR 5.81 P < 0.001) and Dementia (aHR 5.78; P < 0.001). CONCLUSIONS: Age, gender, and comorbidities were identified as significantly higher risk factors for PMV occurrence in the COPD patients compared to the non-COPD patients. Beyond age, comorbidities also play a crucial role in PMV in COPD.

Predictors of extubation failure and prolonged mechanical ventilation among patients with intracerebral hemorrhage after surgery.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is a condition associated with high mortality and morbidity. Survivors may require prolonged intubation with mechanical ventilation (MV). The aim of this study was to analyze the predictors of extubation failure and prolonged MV in patients who undergo surgical evacuation. METHODS: This retrospective study was conducted on adult patients with ICH who underwent MV for at least 48 h and survived > 14 days after surgery. The demographics, clinical characteristics, laboratory tests, and Glasgow Coma Scale score were analyzed. RESULTS: A total of 134 patients with ICH were included in the study. The average age of the patients was 60.34 ± 15.59 years, and 79.9% (n = 107) were extubated after satisfying the weaning parameters. Extubation failure occurred in 11.2% (n = 12) and prolonged MV in 48.5% (n = 65) patients. Multivariable regression analysis revealed that a white blood cell count > 10,000/mm3 at the time of extubation was an independent predictor of reintubation. Meanwhile, age and initial Glasgow Coma Scale scores were predictors of prolonged MV. CONCLUSIONS: This study provided the first comprehensive characterization and analysis of the predictors of extubation failure and prolonged MV in patients with ICH after surgery. Knowledge of potential predictors is essential to improve the strategies for early initiation of adequate treatment and prognosis assessment in the early stages of the disease.

The impact of nontuberculous mycobacterial lung disease in critically ill patients: Significance for survival and ventilator use.

BACKGROUND: This study investigates the impact of nontuberculous mycobacterial lung disease (NTM-LD) on mortality and mechanical ventilation use in critically ill patients. METHODS: We enrolled patients with NTM-LD or tuberculosis (TB) in intensive care units (ICU) and analysed their association with 30-day mortality and with mechanical ventilator-free survival (VFS) at 30 days after ICU admission. RESULTS: A total of 5996 ICU-admitted patients were included, of which 541 (9.0 %) had TB and 173 (2.9 %) had NTM-LD. The overall 30-day mortality was 22.2 %. The patients with NTM-LD had an adjusted hazard ratio (aHR) of 1.49 (95 % CI, 1.06-2.05), and TB patients had an aHR of 2.33 (95 % CI, 1.68-3.24), compared to ICU patients with negative sputum mycobacterial culture by multivariable Cox proportional hazard (PH) regression. The aHR of age<65 years, obesity, idiopathic pulmonary fibrosis, end-stage kidney disease, active cancer and autoimmune disease and diagnosis of respiratory failure were also significantly positively associated with ICU 30-day mortality. In multivariable Cox PH regression for VFS at 30 days in patients requiring invasive mechanical ventilation, NTM-LD was negatively associated with VFS (aHR 0.71, 95 % CI: 0.56-0.92, p = 0.009), while TB showed no significant association. The diagnosis of respiratory failure itself predicted unfavourable outcome for 30-day mortality and a negative impact on VFS at 30 days. CONCLUSIONS: NTM-LD and TB were not uncommon in ICU and both were correlated with increasing 30-day mortality in ICU patients. NTM-LD was associated with a poorer outcome in terms of VFS at 30 days.

Traumatic brain injury-induced disruption of the circadian clock.

Disturbances in the circadian rhythm have been reported in patients following traumatic brain injury (TBI). However, the rhythmic expression of circadian genes in peripheral blood leukocytes (PBL) following TBI has not yet been studied. The messenger ribonucleic acid (mRNA) expression of period 1 (Per1), Per2, Per3, cryptochrome 1 (Cry1), Cry2, brain and muscle aryl hydrocarbon receptor nuclear translocator-like 1 (Bmal1), and circadian locomotor output cycles kaput (Clock) was quantified in PBLs from sham-operated rats and rats with acute subdural hematoma (ASDH) over a 48-h period. The rectal temperature of the animals was measured every 4 h over 2 days. The mesor, rhythm, amplitude, and acrophase were estimated using cosinor analysis. Cosinor analysis revealed that Per2, Cry1, and Bmal1 mRNAs were rhythmically expressed in the PBLs of sham-operated rats. In contrast, fluctuations in rhythmic expression were not observed following ASDH. The rectal temperature of sham-operated rats also exhibited rhythmicity. ASDH rats had a disrupted rectal temperature rhythm, a diminished amplitude, and an acrophase shift. TBI with ASDH results in dysregulated expression of some circadian genes and changes in body temperature rhythm. Further research is required to understand the pathophysiology of altered circadian networks following TBI. KEY MESSAGES: First to investigate the mRNA expression of circadian genes in PBLs of ASDH rats. ASDH rats had disrupted rhythmicity of Per2, Cry1, and Bmal1 mRNA expression. Cosinor analysis showed that ASDH rats had a disrupted rectal temperature rhythm.

Unrecognised entrapment of a herniated bladder at the pubic symphysis following reduction and external fixation of an unstable pelvic fracture.

Bladder injury is frequently associated with complex pelvic fractures with men being the predominant population to sustain such injuries. Entrapment of the bladder through the site of pelvic fracture is a rare clinical entity. We report a case of an entrapped bladder post closed reduction and external fixation of an unstable anteroposterior compression type 3 (APC-3) fracture. This report highlights the diagnostic difficulty with identifying an entrapped bladder and the patient's functional outcome after 1 year of follow-up.

Deep learning with test-time augmentation for radial endobronchial ultrasound image differentiation: a multicentre verification study.

PURPOSE: Despite the importance of radial endobronchial ultrasound (rEBUS) in transbronchial biopsy, researchers have yet to apply artificial intelligence to the analysis of rEBUS images. MATERIALS AND METHODS: This study developed a convolutional neural network (CNN) to differentiate between malignant and benign tumours in rEBUS images. This study retrospectively collected rEBUS images from medical centres in Taiwan, including 769 from National Taiwan University Hospital Hsin-Chu Branch, Hsinchu Hospital for model training (615 images) and internal validation (154 images) as well as 300 from National Taiwan University Hospital (NTUH-TPE) and 92 images were obtained from National Taiwan University Hospital Hsin-Chu Branch, Biomedical Park Hospital (NTUH-BIO) for external validation. Further assessments of the model were performed using image augmentation in the training phase and test-time augmentation (TTA). RESULTS: Using the internal validation dataset, the results were as follows: area under the curve (AUC) (0.88 (95% CI 0.83 to 0.92)), sensitivity (0.80 (95% CI 0.73 to 0.88)), specificity (0.75 (95% CI 0.66 to 0.83)). Using the NTUH-TPE external validation dataset, the results were as follows: AUC (0.76 (95% CI 0.71 to 0.80)), sensitivity (0.58 (95% CI 0.50 to 0.65)), specificity (0.92 (95% CI 0.88 to 0.97)). Using the NTUH-BIO external validation dataset, the results were as follows: AUC (0.72 (95% CI 0.64 to 0.82)), sensitivity (0.71 (95% CI 0.55 to 0.86)), specificity (0.76 (95% CI 0.64 to 0.87)). After fine-tuning, the AUC values for the external validation cohorts were as follows: NTUH-TPE (0.78) and NTUH-BIO (0.82). Our findings also demonstrated the feasibility of the model in differentiating between lung cancer subtypes, as indicated by the following AUC values: adenocarcinoma (0.70; 95% CI 0.64 to 0.76), squamous cell carcinoma (0.64; 95% CI 0.54 to 0.74) and small cell lung cancer (0.52; 95% CI 0.32 to 0.72). CONCLUSIONS: Our results demonstrate the feasibility of the proposed CNN-based algorithm in differentiating between malignant and benign lesions in rEBUS images.

Application of Pupillometry in Neurocritical Patients.

Pupillary light reflex (PLR) assessment is a crucial examination for evaluating brainstem function, particularly in patients with acute brain injury and neurosurgical conditions. The PLR is controlled by neural pathways modulated by both the sympathetic and parasympathetic nervous systems. Altered PLR is a strong predictor of adverse outcomes after traumatic and ischemic brain injuries. However, the assessment of PLR needs to take many factors into account since it can be modulated by various medications, alcohol consumption, and neurodegenerative diseases. The development of devices capable of measuring pupil size and assessing PLR quantitatively has revolutionized the non-invasive neurological examination. Automated pupillometry, which is more accurate and precise, is widely used in diverse clinical situations. This review presents our current understanding of the anatomical and physiological basis of the PLR and the application of automated pupillometry in managing neurocritical patients. We also discuss new technologies that are being developed, such as smartphone-based pupillometry devices, which are particularly beneficial in low-resource settings.

Systemic Inflammation after Aneurysmal Subarachnoid Hemorrhage.

Aneurysmal subarachnoid hemorrhage (aSAH) is one of the most severe neurological disorders, with a high mortality rate and severe disabling functional sequelae. Systemic inflammation following hemorrhagic stroke may play an important role in mediating intracranial and extracranial tissue damage. Previous studies showed that various systemic inflammatory biomarkers might be useful in predicting clinical outcomes. Anti-inflammatory treatment might be a promising therapeutic approach for improving the prognosis of patients with aSAH. This review summarizes the complicated interactions between the nervous system and the immune system.

Association between microcirculation in spontaneous breathing trial and extubation success.

PURPOSE: This study assessed the association between changes in sublingual microcirculation after a spontaneous breathing trial (SBT) and successful extubation. MATERIALS AND METHODS: Sublingual microcirculation was assessed using an incident dark-field video microscope before and after each SBT and before extubation. Microcirculatory parameters before the SBT, at the end of the SBT, and before extubation were compared between the successful and failed extubation groups. RESULTS: Forty-seven patients were enrolled and analysed in this study (34 patients in the successful extubation group and 13 patients in the failed extubation group). At the end of the SBT, the weaning parameters did not differ between the two groups. However, the total small vessel density (21.2 [20.4-23.7] versus 24.9 [22.6-26.5] mm/mm2), perfused small vessel density (20.6 [18.5-21.8] versus 23.1 [20.9-25] mm/mm2), proportion of perfused small vessels (91 [87-96] versus 95 [93-98] %), and microvascular flow index (2.8 [2.7-2.9] versus 2.9 [2.9-3]) were significantly lower in the failed extubation group than in the successful extubation group. The weaning and microcirculatory parameters did not differ significantly between the two groups before the SBT. CONCLUSIONS: More patients are required to investigate the difference between baseline microcirculation before a successful SBT and the change in microcirculation at the end of the SBT between the successful and failed extubation groups. Better sublingual microcirculatory parameters at the end of SBT and before extubation are associated with successful extubation.

A deep learning model using chest X-ray for identifying TB and NTM-LD patients: a cross-sectional study.

BACKGROUND: Timely differentiating between pulmonary tuberculosis (TB) and nontuberculous mycobacterial lung disease (NTM-LD), which are radiographically similar, is important because infectiousness and treatment differ. This study aimed to evaluate whether artificial intelligence could distinguish between TB or NTM-LD patients by chest X-rays (CXRs) from suspects of mycobacterial lung disease. METHODS: A total of 1500 CXRs, including 500 each from patients with pulmonary TB, NTM-LD, and patients with clinical suspicion but negative mycobacterial culture (Imitator) from two hospitals, were retrospectively collected and evaluated in this study. We developed a deep neural network (DNN) and evaluated model performance using the area under the receiver operating characteristic curves (AUC) in both internal and external test sets. Furthermore, we conducted a reader study and tested our model under three scenarios of different mycobacteria prevalence. RESULTS: Among the internal and external test sets, the AUCs of our DNN model were 0.83 ± 0.005 and 0.76 ± 0.006 for pulmonary TB, 0.86 ± 0.006 and 0.64 ± 0.017 for NTM-LD, and 0.77 ± 0.007 and 0.74 ± 0.005 for Imitator. The DNN model showed higher performance on the internal test set in classification accuracy (66.5 ± 2.5%) than senior (50.8 ± 3.0%, p < 0.001) and junior pulmonologists (47.5 ± 2.8%, p < 0.001). Among different prevalence scenarios, the DNN model has stable performance in terms of AUC to detect TB and mycobacterial lung disease. CONCLUSION: DNN model had satisfactory performance and a higher accuracy than pulmonologists on classifying patients with presumptive mycobacterial lung diseases. DNN model could be a complementary first-line screening tool.

Early prediction of delirium upon intensive care unit admission: Model development, validation, and deployment.

STUDY OBJECTIVE: To develop, validate, and deploy models for predicting delirium in critically ill adult patients as early as upon intensive care unit (ICU) admission. DESIGN: Retrospective cohort study. SETTING: Single university teaching hospital in Taipei, Taiwan. PATIENTS: 6238 critically ill patients from August 2020 to August 2021. MEASUREMENTS: Data were extracted, pre-processed, and split into training and testing datasets based on the time period. Eligible variables included demographic characteristics, Glasgow Coma Scale, vital signs parameters, treatments, and laboratory data. The predicted outcome was delirium, defined as any positive result (a score ≥ 4) of the Intensive Care Delirium Screening Checklist that was assessed by primary care nurses in each 8-h shift within 48 h after ICU admission. We trained models to predict delirium upon ICU admission (ADM) and at 24 h (24H) after ICU admission by using logistic regression (LR), gradient boosted trees (GBT), and deep learning (DL) algorithms and compared the models' performance. MAIN RESULTS: Eight features were extracted from the eligible features to train the ADM models, including age, body mass index, medical history of dementia, postoperative intensive monitoring, elective surgery, pre-ICU hospital stays, and GCS score and initial respiratory rate upon ICU admission. In the ADM testing dataset, the incidence of ICU delirium occurred within 24 h and 48 h was 32.9% and 36.2%, respectively. The area under the receiver operating characteristic curve (AUROC) (0.858, 95% CI 0.835-0.879) and area under the precision-recall curve (AUPRC) (0.814, 95% CI 0.780-0.844) for the ADM GBT model were the highest. The Brier scores of the ADM LR, GBT, and DL models were 0.149, 0.140, and 0.145, respectively. The AUROC (0.931, 95% CI 0.911-0.949) was the highest for the 24H DL model and the AUPRC (0.842, 95% CI 0.792-0.886) was the highest for the 24H LR model. CONCLUSION: Our early prediction models based on data obtained upon ICU admission could achieve good performance in predicting delirium occurred within 48 h after ICU admission. Our 24-h models can improve delirium prediction for patients discharged >1 day after ICU admission.

Impact of Nutritional Status on Outcomes of Stroke Survivors: A Post Hoc Analysis of the NHANES.

Stroke, a neurological emergency, is a leading cause of death and disability in adults worldwide. In acute or rehabilitative stages, stroke survivors sustain variable neurological recovery with long-term disabilities. The influence of post-stroke nutritional status on long-term survival has not been confirmed. Using the United States National Health and Nutrition Examination Survey data (2001−2010), we conducted a matched-cohort analysis (929 and 1858 participants in stroke and non-stroke groups, respectively) to investigate the influence of nutritional elements on post-stroke survival. With significantly lower nutrient consumption, the mortality risk was 2.2 times higher in stroke patients compared to non-stroke patients (Kaplan−Meier method with Cox proportional hazards model: adjusted hazard ratio, 2.208; 95% confidence interval: 1.887−2.583; p < 0.001). For several nutritional elements, the lower consumption group had significantly shorter survival than the higher consumption stroke subgroup; moreover, stroke patients with the highest 25% nutritional intake for each nutritional element, except moisture and total fat, had significantly shorter survival than non-stroke patients with the lowest 25% nutrition. Malnutrition is highly prevalent in stroke patients and is associated with high mortality rates. The dynamic change in energy requirements throughout the disease course necessitates dietary adjustment to ensure adequate nutritional intake.

Training a Deep Contextualized Language Model for International Classification of Diseases, 10th Revision Classification via Federated Learning: Model Development and Validation Study.

BACKGROUND: The automatic coding of clinical text documents by using the International Classification of Diseases, 10th Revision (ICD-10) can be performed for statistical analyses and reimbursements. With the development of natural language processing models, new transformer architectures with attention mechanisms have outperformed previous models. Although multicenter training may increase a model's performance and external validity, the privacy of clinical documents should be protected. We used federated learning to train a model with multicenter data, without sharing data per se. OBJECTIVE: This study aims to train a classification model via federated learning for ICD-10 multilabel classification. METHODS: Text data from discharge notes in electronic medical records were collected from the following three medical centers: Far Eastern Memorial Hospital, National Taiwan University Hospital, and Taipei Veterans General Hospital. After comparing the performance of different variants of bidirectional encoder representations from transformers (BERT), PubMedBERT was chosen for the word embeddings. With regard to preprocessing, the nonalphanumeric characters were retained because the model's performance decreased after the removal of these characters. To explain the outputs of our model, we added a label attention mechanism to the model architecture. The model was trained with data from each of the three hospitals separately and via federated learning. The models trained via federated learning and the models trained with local data were compared on a testing set that was composed of data from the three hospitals. The micro F1 score was used to evaluate model performance across all 3 centers. RESULTS: The F1 scores of PubMedBERT, RoBERTa (Robustly Optimized BERT Pretraining Approach), ClinicalBERT, and BioBERT (BERT for Biomedical Text Mining) were 0.735, 0.692, 0.711, and 0.721, respectively. The F1 score of the model that retained nonalphanumeric characters was 0.8120, whereas the F1 score after removing these characters was 0.7875-a decrease of 0.0245 (3.11%). The F1 scores on the testing set were 0.6142, 0.4472, 0.5353, and 0.2522 for the federated learning, Far Eastern Memorial Hospital, National Taiwan University Hospital, and Taipei Veterans General Hospital models, respectively. The explainable predictions were displayed with highlighted input words via the label attention architecture. CONCLUSIONS: Federated learning was used to train the ICD-10 classification model on multicenter clinical text while protecting data privacy. The model's performance was better than that of models that were trained locally.

A Precision Health Service for Chronic Diseases: Development and Cohort Study Using Wearable Device, Machine Learning, and Deep Learning.

This paper presents an integrated and scalable precision health service for health promotion and chronic disease prevention. Continuous real-time monitoring of lifestyle and environmental factors is implemented by integrating wearable devices, open environmental data, indoor air quality sensing devices, a location-based smartphone app, and an AI-assisted telecare platform. The AI-assisted telecare platform provided comprehensive insight into patients' clinical, lifestyle, and environmental data, and generated reliable predictions of future acute exacerbation events. All data from 1,667 patients were collected prospectively during a 24-month follow-up period, resulting in the detection of 386 abnormal episodes. Machine learning algorithms and deep learning algorithms were used to train modular chronic disease models. The modular chronic disease prediction models that have passed external validation include obesity, panic disorder, and chronic obstructive pulmonary disease, with an average accuracy of 88.46%, a sensitivity of 75.6%, a specificity of 93.0%, and an F1 score of 79.8%. Compared with previous studies, we establish an effective way to collect lifestyle, life trajectory, and symptom records, as well as environmental factors, and improve the performance of the prediction model by adding objective comprehensive data and feature selection. Our results also demonstrate that lifestyle and environmental factors are highly correlated with patient health and have the potential to predict future abnormal events better than using only questionnaire data. Furthermore, we have constructed a cost-effective model that needs only a few features to support the prediction task, which is helpful for deploying real-world modular prediction models.

Multidisciplinary management of patients with non-small cell lung cancer with leptomeningeal metastasis in the tyrosine kinase inhibitor era.

OBJECTIVE: Leptomeningeal metastasis (LM) is a challenging scenario in non-small cell lung cancer (NSCLC). Considering that outcomes of treatment modalities stratified by LM chronological patterns related to brain metastasis (BM) are lacking, the aim of this study was to evaluate outcomes and explore prognostic factors. METHODS: The authors retrospectively collected data of patients with NSCLC undergoing Ommaya reservoir implantation, ventriculoperitoneal shunt implantation, or lumboperitoneal shunt implantation. Based on radiographic findings and time from diagnosis of NSCLC to LM, the authors divided them into subtypes of LM as follows: LM without BM; LM concurrent with BM; or LM after BM. The Kaplan-Meier method was applied to analyze overall survival (OS) and multivariate Cox regression for prognostic factors. RESULTS: Sixty-one patients with LM were included, with a median OS of 8.1 (range 0.2-70.0) months. Forty-three (70.5%) patients had EGFR-mutant disease. Forty-two (68.9%) patients had 19-del or L858R mutation, and one (1.6%) patient had G719A mutation. Fifty-seven (93.4%) patients had hydrocephalus. Twenty-one (34.4%) patients received whole-brain radiotherapy before LM diagnosis, 3 (4.9%) patients underwent operation for BMs before LM diagnosis, and 42 (68.9%) patients received EGFR tyrosine kinase inhibitor (TKI) therapy before LM diagnosis. Eleven patients were treated with chemotherapy, 10 patients were treated with TKIs, and 32 patients were treated with chemotherapy combined with TKIs before LM diagnosis. Patients with LM after BM had lower Karnofsky Performance Status (KPS) scores (KPS score 50) than did those with LM without BM (KPS score 80) or LM concurrent with BM (KPS score 70; p = 0.003). More patients with LM after BM received intrathecal methotrexate than in the other subgroups (p < 0.001). The median OS was significantly shorter in the LM after BM than in the concurrent LM and BM and the LM without BM subgroups (5.4 vs 5.5 vs 11.6 months; p = 0.019). Cox regression revealed that a KPS score ≥ 70 (HR 0.51; p = 0.027) and shunt implantation (HR 0.41; p = 0.032) were favorable prognostic factors. CONCLUSIONS: Patients with NSCLC who had LM without BM had better survival outcomes (11.6 months) compared with those who had LM after BM or concurrent LM and BM. Aggressive shunt implantation may be favored for LM.

Cervical cerebrospinal fluid venous fistula with syringomyelia treated with suboccipital decompression: illustrative case.

BACKGROUND: Cerebrospinal fluid (CSF) venous fistulas are a recently discovered and underdiagnosed cause of spontaneous spinal CSF leak, which may lead to spontaneous intracranial hypotension. Most cases occur in the thoracic spine, and only 2 cases were reported in the cervical spine. Treatments include the epidural blood patch, fibrin glue injection, and surgical ligation of the fistula. OBSERVATIONS: The authors report the treatment of a C6-7 CSF venous fistula, for which direct ligation was not feasible, with suboccipital decompression, leading to the complete resolution of the symptoms. Based on the clinical course and outcome in our patient, the authors summarize the previous theory and propose a hypothesis for the pathophysiology of headache and other symptoms in patients with CSF venous fistulas. LESSONS: The symptoms of CSF venous fistulas may be linked not only to intracranial hypotension but also to the altered CSF dynamics induced by tonsillar herniation. Suboccipital decompression should be considered as a potential treatment option, especially in patients with Valsalva-induced headache who show a poor response to surgical ligation, patients in whom surgical ligation is not feasible, and patients with foramen magnum obstruction. Further investigation of the pathophysiology of CSF venous fistulas is warranted and should be performed in the future.

Intracranial Seeding Following Surgery and Chemotherapy in a Child with a Spinal Cord Endodermal Sinus Tumor: A Case Report.

We herein report a case of an extremely rare spinal cord endodermal sinus tumor (EST). A nine-year-old boy presented with progressive paraparesis, hypesthesia, and urinary retention. Gadolinium-enhanced magnetic resonance imaging (MRI) revealed multiple intradural enhancing lesions at T1 to T9 without evidence of intracranial tumors. He underwent partial resection of the lesions, and histology revealed an EST. He received chemotherapy, but 12 months after surgery, rapid tumor progression and intracranial metastases with obstructive hydrocephalus were detected. Following external ventricular drainage, the patient's condition rapidly deteriorated, and he ultimately died. EST should be considered when confronting a homogenously enhancing intradural tumor of the spine on post-contrast MRI.

Minimally Invasive Neurosurgery for Spontaneous Intracerebral Hemorrhage-10 Years of Working Progress at National Taiwan University Hospital.

Intracerebral hemorrhage (ICH) is a life-threatening disease with a global health burden. Traditional craniotomy has neither improved functional outcomes nor reduced mortality. Minimally invasive neurosurgery (MIN) holds promise for reducing mortality and improving functional outcomes. To evaluate the feasibility of MIN for ICH, a retrospective analysis of patients with ICH undergoing endoscopic-assisted evacuation was performed. From 2012 to 2018, a total of 391 patients who underwent ICH evacuation and 76 patients who received early (<8 h) MIN were included. The rebleeding, mortality, and morbidity rates were 3.9, 7.9, and 3.9%, respectively, 1 month after surgery. At 6 months, the median [interquartile range (IQR)] Glasgow Coma Scale score was 12 (4.75) [preoperative: 10 (4)], the median (IQR) Extended Glasgow Outcome Scale score was 3 (1), and the median (IQR) Modified Rankin Scale score was 4 (1). The results suggested that early (<8 h) endoscope-assisted ICH evacuation is safe and effective for selected patients with ICH. The rebleeding, morbidity, and mortality rates of MIN in this study are lower than those of traditional craniotomy reported in previous studies. However, the management of intraoperative bleeding and hard clots is critical for performing endoscopic evacuation. With this retrospective analysis of MIN cases, we hope to promote the specialization of ICH surgery in the field of MIN.

Feasibility of Nonintubated Anesthesia for Lumboperitoneal Shunt Implantation.

Lumboperitoneal shunt (LPS) implantation is a cerebrospinal fluid diversion therapy for the communicating type of normal-pressure hydrocephalus (NPH); NPH mainly affects older adults. However, endotracheal intubation for mechanical ventilation with muscle relaxant increases perioperative and postoperative risks for this population. Based on knowledge from nonintubated thoracoscopic surgery, which has been widely performed in recent years, we describe a novel application of nonintubated anesthesia for LPS implantation in five patients. Anesthesia without muscle relaxants, with a laryngeal mask in one patient and a high-flow nasal cannula in four patients, was used to maintain spontaneous breathing during the surgery. The mean anesthesia time was 103.8 min, and the mean operative duration was 55.8 min. All patients recovered from anesthesia uneventfully. In our experience, nonintubated LPS surgery appears to be a promising and safe surgical technique for appropriately selected patients with NPH.