A 46-year-old man presented with severe refractory posterior shoulder pain due to a left scapular fracture sustained during a motor vehicle collision. Despite multimodal oral and intravenous analgesics, the patients pain remained difficult to control. A continuous paravertebral nerve block was performed between the second and third thoracic vertebrae resulting in excellent analgesia of the scapular pain. This case suggests that a continuous thoracic paravertebral block placed between the second and third vertebrae may be considered as part of multimodal analgesia in patients with scapular fractures.

OBJECTIVE: Obesity is frequently debated as a factor associated with increased postoperative complications. Specifically, upper airway surgeries for obstructive sleep apnea (OSA), a common comorbidity among obese patients, may be complicated by obesitys impact on intraoperative ventilation. The aim of this retrospective study was to analyze the association of various degrees of obesity with postoperative outcomes in patients undergoing surgery for OSA. METHODS: The American College of Surgeons National Surgical Quality Improvement database between 2015 and 2019 was used to create a sample of patients diagnosed with OSA who underwent uvulopalatopharyngoplasty, tracheotomy, and surgeries at the base of tongue, maxilla, palate, or nose/turbinate. Inverse probability-weighted logistic regression and unadjusted multivariable logistic regression were used to compare outcomes of non-obese and obesity class 1, class 2, and class 3 groups (World Health Organization classification). Primary outcome was a composite of 30-day readmissions, reoperations, and/or postoperative complications, and a secondary outcome was all-cause same-day hospital admission. RESULTS: There were 1929 airway surgeries identified. The inverse probability-weighted regression comparing class 1, class 2, and class 3 obesity groups to non-obese patients showed no association between obesity and composite outcome and no association between obesity and hospital admission (all p-values > 0.05). CONCLUSION: These results do not provide evidence that obesity is associated with poorer outcomes or hospital admission surrounding upper airway surgery for OSA. While these data points towards the safety of upper airway surgery in obese patients with OSA, larger prospective studies will aid in elucidating the impact of obesity.

Background Severe cases of carpal tunnel syndrome (CTS) are treated with surgical decompression, for which regional nerve blocks are often administered. There is little data about complications associated with these regional techniques for this surgery. The primary objective was to assess the association of ultrasound-guided regional anesthesia nerve blocks in patients undergoing carpal tunnel release with symptom resolution. Methods This single-institution, retrospective study analyzed all patients undergoing open carpal tunnel release from March 2018 to November 2020. Primary exposure was either regional anesthesia (median and ulnar nerve blocks) or non-regional anesthesia (general anesthesia or local infiltration by surgeon). The primary outcome measurement was symptom resolution at postoperative follow-up at 30-60 days. Secondary outcomes were postoperative surgical site infection, time in operating room (minutes), and post-anesthesia care unit (PACU) length of stay (min). The primary outcome was analyzed using multivariable logistic regression. Results A total of 417 patients were included in this study. Of these, 269 (64.5%) subjects received regional anesthesia as their primary anesthetic. When adjusting for confounders, the use of regional anesthesia was not associated with symptoms not improving at postoperative visit (OR 0.52, 95% CI 0.22 - 1.26, P = 0.15), postoperative surgical site infection (OR 1.47, 95% CI 0.44 - 4.85, p = 0.53), or operating room time duration (p = 0.09). However, the use of regional anesthesia was associated with an approximately 15-minute decrease in PACU length of stay (p < 0.001). Conclusions Regional anesthesia is a safe, effective, and time-efficient method for anesthesia in patients undergoing open carpal tunnel release.

Background and objective A high rate of preoperative anemia has been observed in patients undergoing knee and hip arthroplasty. The type of anesthesia that patients receive may play a role in preventing or minimizing adverse outcomes in these patients. In this study, we aimed to examine the complication rates in patients with severe anemia undergoing this surgery. In addition, we explore whether neuraxial anesthesia is associated with better outcomes compared to general anesthesia. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) registry was used to extract data related to patients who underwent total hip or knee arthroplasty from 2014 to 2016. Only those patients with a hematocrit level <30% were included, and they were classified into two groups based on primary anesthesia type received: neuraxial versus general anesthesia. The primary outcome of interest was postoperative transfusion. Secondary outcomes included 30-day hospital readmission and postoperative complications. Multivariable logistic regression was used to model primary anesthesia type to outcomes while controlling for various confounders. The odds ratio (OR) and their 95% confidence intervals (CI) were reported. Results There were 1,723 patients with severe anemia included in our analysis, of which 41.2% received neuraxial anesthesia. Among patients that received neuraxial versus general anesthesia, 170 (31.08%) and 486 (41.33%), respectively, received a postoperative blood transfusion (p<0.001). On multivariable regression analysis, neuraxial anesthesia was associated with 40% decreased odds of postoperative transfusion (OR: 0.63, 95% CI: 0.51-0.79, p<0.0001), but it was not associated with any other outcomes. Conclusion Neuraxial anesthesia can reduce the risk of postoperative transfusion in severely anemic patients undergoing total joint arthroplasty (TJA), ultimately leading to reduced discomfort, hospital expenditure, and adverse outcomes.

The post-anesthesia care unit (PACU) length of stay is an important perioperative efficiency metric. The aim of this study was to develop machine learning models to predict ambulatory surgery patients at risk for prolonged PACU length of stay - using only pre-operatively identified factors - and then to simulate the effectiveness in reducing the need for after-hours PACU staffing. Several machine learning classifier models were built to predict prolonged PACU length of stay (defined as PACU stay ≥ 3 hours) on a training set. A case resequencing exercise was then performed on the test set, in which historic cases were re-sequenced based on the predicted risk for prolonged PACU length of stay. The frequency of patients remaining in the PACU after-hours (≥ 7:00 pm) were compared between the simulated operating days versus actual operating room days. There were 10,928 ambulatory surgical patients included in the analysis, of which 580 (5.31%) had a PACU length of stay ≥ 3 hours. XGBoost with SMOTE performed the best (AUC = 0.712). The case resequencing exercise utilizing the XGBoost model resulted in an over three-fold improvement in the number of days in which patients would be in the PACU past 7pm as compared with historic performance (41% versus 12%, P<0.0001). Predictive models using preoperative patient characteristics may allow for optimized case sequencing, which may mitigate the effects of prolonged PACU lengths of stay on after-hours staffing utilization.

In MRI studies, spatial normalization is required to infer results at the group level. In the presence of a brain lesion, such as in stroke patients, the normalization process can be affected by tissue loss, spatial deformations, signal intensity changes, and other stroke sequelae that introduce confounds into the group analysis results. Previously, most neuroimaging studies with lesioned brains have used normalization methods optimized for intact brains, raising potential concerns about the accuracy of the resulting transformations and, in turn, their reported group level results. In this study, we demonstrate the benefits of creating an intermediate, cohort-specific template in conjunction with diffeomorphism-based methods to normalize structural MRI images in stroke patients. We show that including this cohort-specific template improves accuracy compared to standard methods for normalizing lesioned brains. Critically, this method reduces overall differences in normalization accuracy between stroke patients and healthy controls, and may improve the localization and connectivity of BOLD signal in functional neuroimaging data.

The role of white matter pathways in cognition is a topic of active investigation that is vital to both the fields of clinical neurology and cognitive neuroscience. White matter pathways provide critical connectivity amongst numerous specialized brain regions thereby enabling higher level cognition. While the effects of dissections and lesions of the corpus callosum have been reported, it is less understood how unilateral focal white matter lesions may impact cognitive processes. Here, we report a unique case study in which a small left lateralized stroke in the white matter adjacent to the body of the corpus callosum selectively impaired the ability to name letters and numbers presented to the ipsilesional, left hand. Naming of letters, numbers and objects was tested in both the visual and tactile modalities in both hands. Diffusion-weighted imaging showed a marked reduction in white matter pathway integrity through the body of the corpus callosum. Clinically, this case highlights the significant impact that a focal white matter lesion can have on higher-level cognition, specifically the integration of verbal and tactile information. Moreover, this case adds to prior reports on tactile agnosia by including DTI imaging data and emphasizing the role that white matter pathways through the body of the corpus callosum play in integrating tactile input from the right hemisphere with verbal naming capabilities of the left hemisphere. Finally, the findings also provoke fresh insight into alternative strategies for rehabilitating cognitive functioning when structural connectivity may be compromised.

Visuospatial processing deficits are typically associated with damage to the right hemisphere. However, deficits on spatial working memory have been reported among some individuals with focal left hemisphere damage (LHD). It has been suggested that the left hemisphere may play a role in such non-verbal working memory tasks due to the use of subvocal, verbally-mediated strategies. The current study investigated the role of the left hemisphere in spatial working memory by testing spatial span performance, both forward and backward, in a large group of individuals with a history of left hemisphere stroke. Our first aim was to establish whether individuals with LHD are indeed impaired on spatial span tasks using standardized span tasks with published normative data. Our second aim was to identify the role that language plays in supporting spatial working memory by comparing LHD individuals with and without aphasia, and by relating spatial span performance to performance on a series of language measures. Our third aim was to identify left hemisphere brain regions that contribute to spatial working memory using voxel-based lesion symptom mapping (VLSM), a whole-brain statistical approach that identifies regions critical to a particular behavior on a voxel-by-voxel basis. We found that 28% of individuals with LHD performed in the clinically-impaired range on forward spatial span and 16% performed in the clinically-impaired range on backward spatial span. There were no significant differences in performance between individuals with and without aphasia, and there were no correlations between spatial span performance and language functions such as repetition and comprehension. The VLSM analysis showed that backward spatial span was associated with a left fronto-parietal network consisting of somatosensory cortex, the supramarginal gyrus, lateral prefrontal cortex, and the frontal eye fields. Regions identified in the VLSM analysis of forward spatial span did not reach the conservative statistical threshold for significance. Overall, these results suggest that spatial working memory, as measured by spatial span, can be significantly disrupted in a subset of individuals with LHD whose lesions infringe on a network of regions in the left hemisphere that have been implicated in domain-general working memory and attentional control mechanisms.

BACKGROUND: Days before surgery, add-ons may be scheduled to fill unused surgical block time at an outpatient surgery center. At times, outpatient surgery centers have time limitations for end of block time and discharge from the postanesthesia care unit (PACU). The objective of our study was to develop machine learning models that predicted the following composite outcome: (1) surgery finished by end of operating room block time and (2) patient was discharged by end of recovery room nursing shift. We compared various machine learning models to logistic regression. By evaluating various performance metrics, including F1 scores, we hypothesized that models using ensemble learning will be superior to logistic regression. METHODS: Data were collected from patients at an ambulatory surgery center. The primary outcome measurement was determined to have a value of 1 (versus 0) if they met both criteria: (1) surgery ends by 5 pm and (2) patient is discharged from the recovery room by 7 pm. We developed models to determine if a procedure would meet both criteria if it were scheduled at 1 pm, 2 pm, 3 pm, or 4 pm. We implemented regression, random forest, balanced random forest, balanced bagging, neural network, and support vector classifier, and included the following features: surgery, surgeon, service line, American Society of Anesthesiologists score, age, sex, weight, and scheduled case duration. We evaluated model performance with Synthetic Minority Oversampling Technique (SMOTE). We compared the following performance metrics: F1 score, area under the receiver operating characteristic curve (AUC), specificity, sensitivity, precision, recall, and Matthews correlation coefficient. RESULTS: Among 13,447 surgical procedures, the median total perioperative time (actual case duration and PACU length stay) was 165 minutes. When SMOTE was not used, when predicting whether surgery will end by 5 pm and patient will be discharged by 7 pm, the average F1 scores were best with random forest, balanced bagging, and balanced random forest classifiers. When SMOTE was used, these models had improved F1 scores compared to no SMOTE. The balanced bagging classifier performed best with F1 score of 0.78, 0.80, 0.82, and 0.82 when predicting our outcome if cases were to start at 1 pm, 2 pm, 3 pm, or 4 pm, respectively. CONCLUSIONS: We demonstrated improvement in predicting the outcome at a range of start times when using ensemble learning versus regression techniques. Machine learning may be adapted by operating room management to allow for a better determination whether an add-on case at an outpatient surgery center could be appropriately booked.