Endoscopic evacuation of septated chronic subdural hemorrhage – Technical considerations, results, and outcome

Background: Chronic subdural hematoma (cSDH) is a common entity in the elderly. Homogeneous or well-liquefied CSDH has a standard line of treatment through burr hole and irrigation. However, the management of septated chronic subdural hematoma (sCSDH) with multiple membranes does not have a well-defined surgical approach. The neomembranes forming septations prevent evacuation of clots through burr holes, and the small remaining loculi with clots will enlarge overtime to cause recurrence. Methods: Patients with sCSDH were operated through a minicraniotomy (2.5 cm × 2.5 cm) using rigid endoscopes for visualization of the subdural space. Using endoscope, the entire subdural space can be visualized. The neomembranes are removed with standard neurosurgical microinstruments. The entire cavity is irrigated under vision to remove all clots and ensures hemostasis. Results: Eighty-three endoscope-assisted evacuations were done in 68 patients from January 2016 to April 2020. Fifty (73.5%) patients had unilateral and 18 (26.5%) had bilateral subdural. Only 1 patient (1.47%) had a clinically significant recollection of subdural bleeding 1 month after the procedure. Over a mean follow-up period of 25.3 months (range 1–53 months), rest of patients did not show any recollection. Conclusion: Endoscopic evacuation of sCSDH is a safe and effective method and can be used to improve clot evacuation, and remove neomembranes under direct vision to reduce the rates of recollection. This method also obviates the need for larger craniotomies to remove membranes.

Transfer Learning of The ResNet-18 and DenseNet-121 Model Used to Diagnose Intracranial Hemorrhage in CT Scanning

Objective: To verify the ability of the deep learning model in identifying five subtypes and normal images in noncontrast enhancement CT of intracranial hemorrhage. Method: A total of 351 patients (39 patients in the normal group, 312 patients in the intracranial hemorrhage group) performed with intracranial hemorrhage noncontrast enhanced CT were selected, with 2768 images in total (514 images for the normal group, 398 images for the epidural hemorrhage group, 501 images for the subdural hemorrhage group, 497 images for the intraventricular hemorrhage group, 415 images for the cerebral parenchymal hemorrhage group, and 443 images for the subarachnoid hemorrhage group). Based on the diagnostic reports of two radiologists with more than 10 years of experience, the ResNet-18 and DenseNet-121 deep learning models were selected. Transfer learning was used. 80% of the data was used for training models, 10% was used for validating model performance against overfitting, and the last 10% was used for the final evaluation of the model. Assessment indicators included accuracy, sensitivity, specificity, and AUC values. Results: The overall accuracy of ResNet-18 and DenseNet-121 models were 89.64% and 82.5%, respectively. The sensitivity and specificity of identifying five subtypes and normal images were above 0.80. The sensitivity of DenseNet-121 model to recognize intraventricular hemorrhage and cerebral parenchymal hemorrhage was lower than 0.80, 0.73, and 0.76 respectively. The AUC values of the two deep learning models were above 0.9. Conclusion: The deep learning model can accurately identify the five subtypes of intracranial hemorrhage and normal images, and it can be used as a new tool for clinical diagnosis in the future.

Traumatic Head Injury and the Diagnosis of Abuse: A Cluster Analysis

OBJECTIVES: Data guiding abusive head trauma (AHT) diagnosis rest on case-control studies that have been criticized for circularity. We wished to sort children with neurologic injury using mathematical algorithms, without reference to physicians’ diagnoses or predetermined diagnostic criteria, and to compare the results to existing AHT data, physicians’ diagnoses, and a proposed triad of findings. METHODS: Unsupervised cluster analysis of an existing data set regarding 500 young patients with acute head injury hospitalized for intensive care. Three cluster algorithms were used to sort (partition) patients into subpopulations (clusters) on the basis of 32 reliable (κ > 0.6) clinical and radiologic variables. P values and odds ratios (ORs) identified variables most predictive of partitioning. RESULTS: The full cohort partitioned into 2 clusters. Variables substantially (P < .001 and OR > 10 in all 3 cluster algorithms) more prevalent in cluster 1 were imaging indications of brain hypoxemia, ischemia, and/or swelling; acute encephalopathy, particularly when lasting >24 hours; respiratory compromise; subdural hemorrhage or fluid collection; and ophthalmologist-confirmed retinoschisis. Variables substantially (P < .001 and OR < 0.10 in any cluster algorithm) more prevalent in cluster 2 were linear parietal skull fracture and epidural hematoma. Postpartitioning analysis revealed that cluster 1 had a high prevalence of physician-diagnosed abuse. CONCLUSIONS: Three cluster algorithms partitioned the population into 2 clusters without reference to predetermined diagnostic criteria or clinical opinion about the nature of AHT. Clinical difference between clusters replicated differences previously described in comparisons of AHT with non-AHT. Algorithmic partition was predictive of physician diagnosis and of the triad of findings heavily discussed in AHT literature.

Traumatic aneurysm at the superior cerebellar artery: illustrative case

BACKGROUND Traumatic aneurysms at the superior cerebellar arteries after head injury are extremely rare and may be overlooked. Rupture of these aneurysms can cause fatal intracranial hemorrhages; thus, early identification of the entity helps prevent detrimental outcomes. OBSERVATIONS A patient suffered from sudden severe headache and decreased consciousness level several weeks after a blunt head injury. He received surgery to remove a progressive enlarging subdural hematoma. The diagnosis of a traumatic aneurysm at the superior cerebellar artery was delayed, made only after a recurrent subdural hemorrhage occurred. He received another surgery to obliterate the aneurysm. LESSONS The patient could have been treated earlier if traumatic aneurysm had been suspected in the beginning. In addition to the case, the authors also reviewed the literature to clarify the pathophysiology, clinical presentation, diagnosis, and management of the disease.

Epilepsy Due to Mild TBI in Children: An Experience at a Tertiary Referral Center

Rationale: Posttraumatic epilepsy (PTE) is a common cause of morbidity in children after a traumatic brain injury (TBI), occurring in 10–20% of children following severe TBI. PTE is diagnosed after two or more unprovoked seizures occurring 1-week post TBI. More often, studies have focused on children with epilepsy due to severe TBI. We aim to understand the utility of head computed tomography (HCT), EEG, and the risk of developing drug-resistant epilepsy in children after mild TBI. Method: We retrospectively studied 321 children with TBI at a tertiary pediatric referral center during a 10-year period. Mild TBI was defined as loss of consciousness (LOC) or amnesia < 30 min, moderate TBI as LOC or amnesia between 30 min and 1 day, and severe TBI as LOC or amnesia > 1 day, subdural hemorrhage, or contusion. Multiple clinical variables were reviewed, including past and present antiepileptic drug(s), seizure control, and mode of injury. First and subsequent post-TBI EEGs/prolonged video-EEGs were obtained acutely, subacutely, and/or chronically (range, day 1–3 years, median 1 month). Descriptive analyses were conducted using medians and ranges for continuous data. Categorical data were reported using frequencies and percentages, while comparisons between groups were made using Fisher’s exact test for small sample sizes. Results: Forty-seven children were diagnosed with posttraumatic epilepsy: eight children (17%) due to mild TBI, 39 children (83%) due to severe TBI. For the eight children with mild TBI whom all had an accidental trauma (non-inflicted), the median follow-up time was 25 months (range 1.5 months–84 months). The median age was 10 years (range 4–18 years), and the median age at the time of injury was seven years (range: 23 months–13 years). No relevant previous medical history was present for six patients (80%), and two patients’ (20%) relevant previous medical histories were unknown. Seven patients (88%) had no history of seizures, and patient #6 (12%) had unknown seizure history. Six patients (75%) had normal routine EEG(s). Patient #6 (13%) had an abnormal VEEG 3 months after the initial normal routine EEG, while patient #1 (13%) had an initial prolonged EEG 8 months after TBI. Compared to the 39 patients with severe TBI, 31 (79%) of whom had abnormal EEGs (routine and/or prolonged with video), mild TBI patients were more likely to have normal EEGs, p = 0.005. Head CT scans were obtained acutely for seven patients (90%), all of which were normal. One patient only had brain magnetic resonance imaging (MRI) 8 months after the injury. Compared to the 39 patients with severe TBI, all of whom had abnormal HCTs, mild TBI patients were less likely to have abnormal HCTs, p < 0.0001. In patients with mild TBI, no patient had both abnormal EEG/VEEG and HCT, and no one was on more than one Antiepileptic drug (AED), p < 0.005. Six patients (75%) had MRIs, of which five (63%) were normal. Two patients (#1, 7) did not have MRIs, while one patient’s (#4) MRI was unavailable. Five patients (63%) had a seizure <24 h post TBI, while the rest had seizures after the first week of injury. Conclusion: Children with epilepsy due to mild TBI, loss of consciousness, or amnesia < 30 min are more likely to have normal HCT and EEG and to be on 0–1 AED. Limitations of our study include the small sample size and retrospective design. The current findings add to the paucity of data in children who suffer from epilepsy due to mild TBI.

Effectiveness of applying clinical simulation scenarios and integrating information technology in medical-surgical nursing and critical nursing courses

Background To determine the impact of combining clinical simulation scenario training and Information Technology Integrated Instruction (ITII) on the teaching of nursing skills. Methods 120 4th-year students in a nursing program who were enrolled in medical and surgical nursing courses. 61 received innovative instruction (experimental group) and 59 received conventional instruction (control group). The ADDIE model, systematic method of course development that includes analysis, design, development, implementation, and evaluation,was used to build simulation teaching and clinical scenarios and to create and modify objective structure clinical examination (OSCE) scenario checklists for acute myocardial infarction (AMI) care, basic life support and operation of automated external defibrillator (BLS), and subdural hemorrhage (SDH) care. The modified OSCE checklists were assessed for reliability, consistency, and validity. The innovative training included flipped classrooms, clinical simulation scenarios, ITII and blended learning formats. Results The reliability and validity of the OSCE checklists developed in this study were acceptable and comparable or higher than checklists in past studies and could be utilized as an OSCE performance tool. Students in innovative instruction obtained significantly better OSCE performance, lab scores and improvements from the previous year’s grades. Significant differences were found in situational awareness (SA). No strong correlations were found between OSCE scores and clinical internship scores, and no significant differences were found between the groups in overall clinical internship performance. Conclusions Innovative instruction showed better performance than conventional methods in summative evaluation of knowledge components, OSCE formative evaluation and clinical nursing internship scores, as well as improved situational awareness in nursing students.

A Case Report of Chronic Expanding Hematoma of the Left Erector Spinae Muscle After Stereotactic Body Radiotherapy for Renal Cell Carcinoma

Background: Hematomas that slowly increase in size for over a period of more than one month after the initial hemorrhage are referred to as chronic expanding hematoma (CEH). We report a case of CEH of left erector spinae muscle after stereotactic body radiotherapy (SBRT) for renal cell carcinoma (RCC). Case presentation: A 74-year-old Japanese male complained of back pain. There was no history of surgery or trauma of his back. He received SBRT for RCC of left kidney of seven years ago. Computed tomography (CT) revealed the left erector spinae muscle was swollen compared to the contralateral side at the third lumbar level. Ultrasonography showed a tumor of 30 mm in size without blood flow in left paraspinal muscle. Positron emission tomography-CT revealed uptake in the left paraspinal muscle. Pathological examination showed radiation-induced CEH. We performed conservative therapy with medication alone because the tumor had been gradually growing. One year after starting observation, the patient died due to subdural hemorrhage after a fall and progression of renal failure. Discussion and conclusions: Because this study was a case study, it is difficult to definite the CEH after SBRT. Since SBRT has recently been increasing, SBRT-induced CEH is considered to be an important complication.