Management of a giant adrenal schwannoma.

In this case report, we present a man in his 60s who presented with an incidentally discovered right adrenal mass, which turned out to be an adrenal schwannoma. This is a very rare tumour that originates from Schwann cells and involves the peripheral nerves. The tumour was removed by open adrenalectomy, and this 15-cm adrenal schwannoma is one of the largest reported in the literature, with none >16 cm having ever been reported. This case highlights the importance of keeping an open mind about the cause of an incidentally discovered adrenal mass, which is an increasingly common way for adrenal tumours to present given the increased access to cross-sectional imaging. As well as presenting the case and the pathological basis behind adrenal schwannomas, we include a review of the literature and a general discussion about incidentally discovered adrenal masses.

Large Language Model Capabilities in Perioperative Risk Prediction and Prognostication.

Importance: General-domain large language models may be able to perform risk stratification and predict postoperative outcome measures using a description of the procedure and a patient's electronic health record notes. Objective: To examine predictive performance on 8 different tasks: prediction of American Society of Anesthesiologists Physical Status (ASA-PS), hospital admission, intensive care unit (ICU) admission, unplanned admission, hospital mortality, postanesthesia care unit (PACU) phase 1 duration, hospital duration, and ICU duration. Design, Setting, and Participants: This prognostic study included task-specific datasets constructed from 2 years of retrospective electronic health records data collected during routine clinical care. Case and note data were formatted into prompts and given to the large language model GPT-4 Turbo (OpenAI) to generate a prediction and explanation. The setting included a quaternary care center comprising 3 academic hospitals and affiliated clinics in a single metropolitan area. Patients who had a surgery or procedure with anesthesia and at least 1 clinician-written note filed in the electronic health record before surgery were included in the study. Data were analyzed from November to December 2023. Exposures: Compared original notes, note summaries, few-shot prompting, and chain-of-thought prompting strategies. Main Outcomes and Measures: F1 score for binary and categorical outcomes. Mean absolute error for numerical duration outcomes. Results: Study results were measured on task-specific datasets, each with 1000 cases with the exception of unplanned admission, which had 949 cases, and hospital mortality, which had 576 cases. The best results for each task included an F1 score of 0.50 (95% CI, 0.47-0.53) for ASA-PS, 0.64 (95% CI, 0.61-0.67) for hospital admission, 0.81 (95% CI, 0.78-0.83) for ICU admission, 0.61 (95% CI, 0.58-0.64) for unplanned admission, and 0.86 (95% CI, 0.83-0.89) for hospital mortality prediction. Performance on duration prediction tasks was universally poor across all prompt strategies for which the large language model achieved a mean absolute error of 49 minutes (95% CI, 46-51 minutes) for PACU phase 1 duration, 4.5 days (95% CI, 4.2-5.0 days) for hospital duration, and 1.1 days (95% CI, 0.9-1.3 days) for ICU duration prediction. Conclusions and Relevance: Current general-domain large language models may assist clinicians in perioperative risk stratification on classification tasks but are inadequate for numerical duration predictions. Their ability to produce high-quality natural language explanations for the predictions may make them useful tools in clinical workflows and may be complementary to traditional risk prediction models.

Predicting Out-of-Hospital Cardiac Arrest in the General Population Using Electronic Health Records.

BACKGROUND: The majority of out-of-hospital cardiac arrests (OHCAs) occur among individuals in the general population, for whom there is no established strategy to identify risk. In this study, we assess the use of electronic health record (EHR) data to identify OHCA in the general population and define salient factors contributing to OHCA risk. METHODS: The analytical cohort included 2366 individuals with OHCA and 23 660 age- and sex-matched controls receiving health care at the University of Washington. Comorbidities, electrocardiographic measures, vital signs, and medication prescription were abstracted from the EHR. The primary outcome was OHCA. Secondary outcomes included shockable and nonshockable OHCA. Model performance including area under the receiver operating characteristic curve and positive predictive value were assessed and adjusted for observed rate of OHCA across the health system. RESULTS: There were significant differences in demographic characteristics, vital signs, electrocardiographic measures, comorbidities, and medication distribution between individuals with OHCA and controls. In external validation, discrimination in machine learning models (area under the receiver operating characteristic curve 0.80-0.85) was superior to a baseline model with conventional cardiovascular risk factors (area under the receiver operating characteristic curve 0.66). At a specificity threshold of 99%, correcting for baseline OHCA incidence across the health system, positive predictive value was 2.5% to 3.1% in machine learning models compared with 0.8% for the baseline model. Longer corrected QT interval, substance abuse disorder, fluid and electrolyte disorder, alcohol abuse, and higher heart rate were identified as salient predictors of OHCA risk across all machine learning models. Established cardiovascular risk factors retained predictive importance for shockable OHCA, but demographic characteristics (minority race, single marital status) and noncardiovascular comorbidities (substance abuse disorder) also contributed to risk prediction. For nonshockable OHCA, a range of salient predictors, including comorbidities, habits, vital signs, demographic characteristics, and electrocardiographic measures, were identified. CONCLUSIONS: In a population-based case-control study, machine learning models incorporating readily available EHR data showed reasonable discrimination and risk enrichment for OHCA in the general population. Salient factors associated with OCHA risk were myriad across the cardiovascular and noncardiovascular spectrum. Public health and tailored strategies for OHCA prediction and prevention will require incorporation of this complexity.

Intraoperative Prophylaxis with Palonosetron for Postoperative Nausea and/or Vomiting in Adults Undergoing Cardiothoracic Surgery Under General Anesthesia: A Single-Center Retrospective Study.

OBJECTIVE: This study assessed the efficacy of palonosetron, alone or with dexamethasone, in reducing postoperative nausea and/or vomiting (PONV) and its impact on hospitalization duration in patients who undergo adult cardiothoracic surgery (CTS) under general anesthesia. DESIGN: This retrospective analysis involved 540 adult patients who underwent CTS from a single-center cohort, spanning surgeries between September 2021 and March 2023. Sensitivity, logistic, and Cox regression analyses evaluated antiemetic effects, PONV risk factors, and outcomes. SETTING: At the Virginia Mason Medical Center (VMMC), Seattle, WA. PARTICIPANTS: Adults undergoing cardiothoracic surgery at VMMC during the specified period. INTERVENTIONS: Patients were categorized into the following 4 groups based on antiemetic treatment: dexamethasone, palonosetron, dexamethasone with palonosetron, and no antiemetic. MEASUREMENTS AND MAIN RESULTS: Primary outcomes encompassed PONV incidence within 96 hours postoperatively. Secondary outcomes included intensive care unit stay duration and postoperative opioid use. Palonosetron recipients showed a significantly lower PONV rate of 42% (v controls at 63%). The dexamethasone and palonosetron combined group also demonstrated a lower rate of 40%. Sensitivity analysis revealed a notably lower 0- to 12-hour PONV rate for palonosetron recipients (9% v control at 28%). Logistic regression found decreased PONV risk (palonosetron odds ratio [OR]: 0.24; dexamethasone and palonosetron OR: 0.26). Cox regression identified varying PONV hazard ratios related to female sex, PONV history, and lower body mass index. CONCLUSIONS: This single-center retrospective study underscored palonosetron's efficacy, alone or combined with dexamethasone, in managing PONV among adult patients who undergo CTS. These findings contribute to evolving antiemetic strategies in cardiothoracic surgery, potentially impacting patient outcomes and satisfaction positively.

Public Health Informatics and the Perioperative Physician: Looking to the Future.

The role of informatics in public health has increased over the past few decades, and the coronavirus disease 2019 (COVID-19) pandemic has underscored the critical importance of aggregated, multicenter, high-quality, near-real-time data to inform decision-making by physicians, hospital systems, and governments. Given the impact of the pandemic on perioperative and critical care services (eg, elective procedure delays; information sharing related to interventions in critically ill patients; regional bed-management under crisis conditions), anesthesiologists must recognize and advocate for improved informatic frameworks in their local environments. Most anesthesiologists receive little formal training in public health informatics (PHI) during clinical residency or through continuing medical education. The COVID-19 pandemic demonstrated that this knowledge gap represents a missed opportunity for our specialty to participate in informatics-related, public health-oriented clinical care and policy decision-making. This article briefly outlines the background of PHI, its relevance to perioperative care, and conceives intersections with PHI that could evolve over the next quarter century.

Impact of Ketorolac on Reoperation for Hemorrhage After Pediatric Tonsillectomy: A Single-Center Retrospective Propensity-Matched Study.

OBJECTIVE: To determine if perioperative ketorolac is associated with an increased rate of reoperation for hemorrhage after pediatric tonsillectomy at 30 days and 48 hours. STUDY DESIGN: Single-center retrospective propensity-matched study. SETTING: Quaternary pediatric hospital and ambulatory surgery center. METHODS: Patients less than 18 years old undergoing tonsillectomy or adenotonsillectomy between January 1, 2015 and October 1, 2020 were included. Hemorrhage rates between exposed (K+) and unexposed (K-) patients were calculated for the total cohort and a 1:1 propensity-matched cohort. Additional analyses included: multivariable logistic regression, subgroup analysis of ASA 1 and 2 patients, subgroup analysis comparing children with teenagers. RESULTS: There were 5873 patients (42.1% K+) in the full cohort and 4694 patients in the propensity-matched cohort. Reoperation for hemorrhage within 30 days occurred in 1.9% of K+ patients and 1.6% of K- patients (P = 0.455) in the full cohort and 1.9% of K+ patients and 1.7% of K- patients (odds ratio [OR] 1.10, 95% confidence interval [CI] 0.72-1.69, P = 0.662) in the propensity-matched cohort. Reoperation within 48 hours occurred in 0.65% of K+ patients and 0.53% of K- patients (P = 0.679) in the full cohort and 0.68% of K+ patients and 0.51% of K- patients (OR 1.33, 95% CI 0.63-2.81, P = 0.451) in the propensity-matched cohort. There was no association between perioperative ketorolac administration and reoperation for hemorrhage in any of the other analyses. CONCLUSION: Ketorolac at end of surgery should be considered as part of the nonopioid analgesic regimen for pediatric tonsillectomy.

Perioperative Mortality of the COVID-19 Recovered Patient Compared to a Matched Control: A Multicenter Retrospective Cohort Study.

BACKGROUND: Surgical procedures performed on patients with recent exposure to COVID-19 infection have been associated with increased mortality risk in previous studies. Accordingly, elective surgery is often delayed after infection. The study aimed to compare 30-day hospital mortality and postoperative complications (acute kidney injury, pulmonary complications) of surgical patients with a previous COVID-19 infection to a matched cohort of patients without known previous COVID-19. The authors hypothesized that COVID-19 exposure would be associated with an increased mortality risk. METHODS: In this retrospective observational cohort study, patients presenting for elective inpatient surgery across a multicenter cohort of academic and community hospitals from April 2020 to April 2021 who had previously tested positive for COVID-19 were compared to controls who had received at least one previous COVID-19 test but without a known previous COVID-19-positive test. The cases were matched based on anthropometric data, institution, and comorbidities. Further, the outcomes were analyzed stratified by timing of a positive test result in relation to surgery. RESULTS: Thirty-day mortality occurred in 229 of 4,951 (4.6%) COVID-19-exposed patients and 122 of 4,951 (2.5%) controls. Acute kidney injury was observed in 172 of 1,814 (9.5%) exposed patients and 156 of 1,814 (8.6%) controls. Pulmonary complications were observed in 237 of 1,637 (14%) exposed patients and 164 of 1,637 (10%) controls. COVID-19 exposure was associated with an increased 30-day mortality risk (adjusted odds ratio, 1.63; 95% CI, 1.38 to 1.91) and an increased risk of pulmonary complications (1.60; 1.36 to 1.88), but was not associated with an increased risk of acute kidney injury (1.03; 0.87 to 1.22). Surgery within 2 weeks of infection was associated with a significantly increased risk of mortality and pulmonary complications, but that effect was nonsignificant after 2 weeks. CONCLUSIONS: Patients with a positive test for COVID-19 before elective surgery early in the pandemic have an elevated risk of perioperative mortality and pulmonary complications but not acute kidney injury as compared to matched controls. The span of time from positive test to time of surgery affected the mortality and pulmonary risk, which subsided after 2 weeks.

Prediction of American Society of Anesthesiologists Physical Status Classification from preoperative clinical text narratives using natural language processing.

BACKGROUND: Electronic health records (EHR) contain large volumes of unstructured free-form text notes that richly describe a patient's health and medical comorbidities. It is unclear if perioperative risk stratification can be performed directly from these notes without manual data extraction. We conduct a feasibility study using natural language processing (NLP) to predict the American Society of Anesthesiologists Physical Status Classification (ASA-PS) as a surrogate measure for perioperative risk. We explore prediction performance using four different model types and compare the use of different note sections versus the whole note. We use Shapley values to explain model predictions and analyze disagreement between model and human anesthesiologist predictions. METHODS: Single-center retrospective cohort analysis of EHR notes from patients undergoing procedures with anesthesia care spanning all procedural specialties during a 5 year period who were not assigned ASA VI and also had a preoperative evaluation note filed within 90 days prior to the procedure. NLP models were trained for each combination of 4 models and 8 text snippets from notes. Model performance was compared using area under the receiver operating characteristic curve (AUROC) and area under the precision recall curve (AUPRC). Shapley values were used to explain model predictions. Error analysis and model explanation using Shapley values was conducted for the best performing model. RESULTS: Final dataset includes 38,566 patients undergoing 61,503 procedures with anesthesia care. Prevalence of ASA-PS was 8.81% for ASA I, 31.4% for ASA II, 43.25% for ASA III, and 16.54% for ASA IV-V. The best performing models were the BioClinicalBERT model on the truncated note task (macro-average AUROC 0.845) and the fastText model on the full note task (macro-average AUROC 0.865). Shapley values reveal human-interpretable model predictions. Error analysis reveals that some original ASA-PS assignments may be incorrect and the model is making a reasonable prediction in these cases. CONCLUSIONS: Text classification models can accurately predict a patient's illness severity using only free-form text descriptions of patients without any manual data extraction. They can be an additional patient safety tool in the perioperative setting and reduce manual chart review for medical billing. Shapley feature attributions produce explanations that logically support model predictions and are understandable to clinicians.

Cardiometabolic disease and obesity patterns differentially predict acute kidney injury after total joint replacement: a retrospective analysis.

BACKGROUND: Acute kidney injury (AKI) is a frequent yet understudied postoperative total joint arthroplasty complication. This study aimed to describe cardiometabolic disease co-occurrence using latent class analysis, and associated postoperative AKI risk. METHODS: This retrospective analysis examined patients ≥18 years old undergoing primary total knee or hip arthroplasties within the US Multicenter Perioperative Outcomes Group of hospitals from 2008 to 2019. AKI was defined using modified Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Latent classes were constructed from eight cardiometabolic diseases including hypertension, diabetes, and coronary artery disease, excluding obesity. A mixed-effects logistic regression model was constructed for the outcome of any AKI and the exposure of interaction between latent class and obesity status adjusting for preoperative and intraoperative covariates. RESULTS: Of 81 639 cases, 4007 (4.9%) developed AKI. Patients with AKI were more commonly older and non-Hispanic Black, with more significant comorbidity. A latent class model selected three groups of cardiometabolic patterning, labelled 'hypertension only' (n=37 223), 'metabolic syndrome (MetS)' (n=36 503), and 'MetS+cardiovascular disease (CVD)' (n=7913). After adjustment, latent class/obesity interaction groups had differential risk of AKI compared with those in 'hypertension only'/non-obese. Those 'hypertension only'/obese had 1.7-fold increased odds of AKI (95% confidence interval [CI]: 1.5-2.0). Compared with 'hypertension only'/non-obese, those 'MetS+CVD'/obese had the highest odds of AKI (odds ratio 3.1, 95% CI: 2.6-3.7), whereas 'MetS+CVD'/non-obese had 2.2 times the odds of AKI (95% CI: 1.8-2.7; model area under the curve 0.76). CONCLUSIONS: The risk of postoperative AKI varies widely between patients. The current study suggests that the co-occurrence of metabolic conditions (diabetes mellitus, hypertension), with or without obesity, is a more important risk factor for acute kidney injury than individual comorbid diseases.

Opportunistic screening for osteoporosis by abdominal CT in a British population.

BACKGROUND: It has previously been shown that CT scans performed for other indications can be used to identify patients with osteoporosis. This has not yet been tested in a British population. We sought to evaluate the use of vertebral CT attenuation measures for predicting osteoporosis in a British cohort, using dual-energy X-ray absorptiometry (DEXA) as a reference standard. METHODS: Patients who underwent abdominal CT in 2018 and concomitantly underwent DEXA within a six-month interval were retrospectively included. CT attenuation values in Hounsfield units (HU) were measured by placement of a region-of-interest at the central portion of the L1 vertebral body and then compared to their corresponding DEXA score. Receiver operating characteristic (ROC) curves were generated to evaluate the performance of a logistic regression model and to determine sensitivity and specificity thresholds. RESULTS: 536 patients (394 females, mean age 65.8) were included, of which 174 had DEXA-defined osteoporosis. L1 attenuation measures were significantly different (p < 0.01) between the three DEXA-defined groups of osteoporosis (118 HU), osteopenia (143 HU) and normal bone density (178 HU). The area under the ROC curve was 0.74 (95% CI 0.69-0.78). A threshold of 169 HU was 90% sensitive, and a threshold of 104 HU was 90% specific for diagnosing osteoporosis. CONCLUSIONS: Routine abdominal CT can be used to opportunistically screen for osteoporosis without additional cost or radiation exposure. The thresholds identified in this study are comparable with previous studies in other populations. We recommend radiologists engage with primary care and rheumatology providers to determine appropriate cut-off values for further investigation.

Anesthesiology Performance Improvement and Reporting Exchange (ASPIRE) Quality Metrics in Patients Undergoing Decompressive Craniectomy and Endoscopic Clot Evacuation after Spontaneous Supratentorial Intracerebral Hemorrhage: A Retrospective Observational Study.

BACKGROUND: We report adherence to 6 Anesthesiology Performance Improvement and Reporting Exchange (ASPIRE) quality metrics (QMs) relevant to patients undergoing decompressive craniectomy or endoscopic clot evacuation after spontaneous supratentorial intracerebral hemorrhage (sICH). METHODS: In this retrospective observational study, we describe adherence to the following ASPIRE QMs: acute kidney injury (AKI-01); mean arterial pressure < 65 mm Hg for less than 15 minutes (BP-03); myocardial injury (CARD-02); treatment of high glucose (> 200 mg/dL, GLU-03); reversal of neuromuscular blockade (NMB-02); and perioperative hypothermia (TEMP-03). RESULT: The study included 95 patients (70% male) with median (interquartile range) age 55 (47 to 66) years and ICH score 2 (1 to 3) undergoing craniectomy (n=55) or endoscopic clot evacuation (n=40) after sICH. In-hospital mortality attributable to sICH was 23% (n=22). Patients with American Society of Anesthesiologists physical status class 5 (n=16), preoperative reduced glomerular filtration rate (n=5), elevated cardiac troponin (n=21) and no intraoperative labs with high glucose (n=71), those who were not extubated at the end of the case (n=62) or did not receive a neuromuscular blocker given (n=3), and patients having emergent surgery (n=64) were excluded from the analysis for their respective ASPIRE QM based on predetermined ASPIRE exclusion criteria. For the remaining patients, the adherence to ASPIRE QMs were: AKI-01, craniectomy 34%, endoscopic clot evacuation 1%; BP-03, craniectomy 72%, clot evacuation 73%; CARD-02, 100% for both groups; GLU-03, craniectomy 67%, clot evacuation 100%; NMB-02, clot evacuation 79%, and; TEMP-03, clot evacuation 0% with hypothermia. CONCLUSION: This study found variable adherence to ASPIRE QMs in sICH patients undergoing decompressive craniectomy or endoscopic clot evacuation. The relatively high number of patients excluded from individual ASPIRE metrics is a major limitation.

Evaluating the role for regional analgesia in children with spina bifida: a retrospective observational study comparing the efficacy of regional versus systemic analgesia protocols following major urological surgery.

INTRODUCTION: Regional techniques are a key component of multimodal analgesia and help decrease opioid use perioperatively, but some techniques may not be suitable for all patients, such as those with spina bifida. We hypothesized peripheral regional catheters would reduce postoperative opioid use compared with no regional analgesia without increasing pain scores in pediatric patients with spina bifida undergoing major urological surgery. METHODS: A retrospective review of a multicenter database established for the study of enhanced recovery after surgery was performed of patients from 2009 to 2021 who underwent bladder augmentation or creation of catheterizable channels. Patients without spina bifida and those receiving epidural analgesia were excluded. Opioids were converted into morphine equivalents and normalized to patient weight. RESULTS: 158 patients with pediatric spina bifida from 7 centers were included, including 87 with and 71 without regional catheters. There were no differences in baseline patient factors. Anesthesia setup increased from median 40 min (IQR 34-51) for no regional to 64 min (IQR 40-97) for regional catheters (p<0.01). The regional catheter group had lower median intraoperative opioid usage (0.24 vs 0.80 mg/kg morphine equivalents, p<0.01) as well as lower in-hospital postoperative opioid usage (0.05 vs 0.23 mg/kg/day morphine equivalents, p<0.01). Pain scores were not higher in the regional catheters group. DISCUSSION: Continuous regional analgesia following major urological surgery in children with spina bifida was associated with a 70% intraoperative and 78% postoperative reduction in opioids without higher pain scores. This approach should be considered for similar surgical interventions in this population. TRIAL REGISTRATION NUMBER: NCT03245242.

Completion of an Enhanced Recovery Program in a Pediatric Ambulatory Surgery Center: A Quality Improvement Initiative.

BACKGROUND: Enhanced Recovery After Surgery (ERAS) was first established in 2001 focusing on recovery from complex surgical procedures in adults and recently expanded to ambulatory surgery. The evidence for ERAS in children is limited. In 2018, recognized experts began developing needed pediatric evidence. Center-wide efforts involving all ambulatory surgical patients and procedures have not previously been described. METHODS: A comprehensive assessment and gap analysis of ERAS elements in our ambulatory center identified 11 of 19 existing elements. The leadership committed to implementing an Enhanced Recovery Program (ERP) to improve existing elements and close as many remaining gaps as possible. A quality improvement (QI) team was launched to improve 5 existing ERP elements and to introduce 6 new elements (target 17/19 ERP elements). The project plan was broken into 1 preparation phase to collect baseline data and 3 implementation phases to enhance existing and implement new elements. Statistical process control methodology was used. Team countermeasures were based on available evidence. A consensus process was used to resolve disagreement. Monthly meetings were held to share real-time data, gather new feedback, and modify countermeasure plans as needed. The primary outcome measure selected was mean postanesthesia care unit (PACU) length of stay (LOS). Secondary outcomes measures were mean maximum pain score in PACU and patient/family satisfaction scores. RESULTS: The team had expanded the pool of active ERP elements from 11 to 16 of 19. The mean PACU LOS demonstrated significant reduction (early in phase 1 and again in phase 3). No change was seen for the mean maximum pain score in PACU or surgical complication rates. Patient/family satisfaction scores were high and sustained throughout the period of study (91.1% ± 5.7%). Patient/family and provider engagement/compliance were high. CONCLUSIONS: This QI project demonstrated the feasibility of pediatric ERP in an ambulatory surgical setting. Furthermore, a center-wide approach was shown to be possible. Additional studies are needed to determine the relevance of this project to other institutions.

Liver Fibrosis Marker and Postoperative Mortality in Patients Without Overt Liver Disease.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) can progress to advanced fibrosis, which, in the nonsurgical population, is associated with poor hepatic and extrahepatic outcomes. Despite its high prevalence, NAFLD and related liver fibrosis may be overlooked during the preoperative evaluation, and the role of liver fibrosis as an independent risk factor for surgical-related mortality has yet to be tested. The aim of this study was to assess whether fibrosis-4 (FIB-4), which consists of age, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and platelets, a validated marker of liver fibrosis, is associated with postoperative mortality in the general surgical population. METHODS: A historical cohort of patients undergoing general anesthesia at an academic medical center between 2014 and 2018 was analyzed. Exclusion criteria included known liver disease, acute liver disease or hepatic failure, and alcohol use disorder. FIB-4 score was categorized into 3 validated predefined categories: FIB-4 ≤1.3, ruling out advanced fibrosis; >1.3 and <2.67, inconclusive; and ≥2.67, suggesting advanced fibrosis. The primary analytic method was propensity score matching (FIB-4 was dichotomized to indicate advanced fibrosis), and a secondary analysis included a multivariable logistic regression. RESULTS: Of 19,861 included subjects, 1995 (10%) had advanced fibrosis per FIB-4 criteria. Mortality occurred intraoperatively in 15 patients (0.1%), during hospitalization in 272 patients (1.4%), and within 30 days of surgery in 417 patients (2.1%). FIB-4 ≥2.67 was associated with increased intraoperative mortality (odds ratio [OR], 3.63; 95% confidence interval [CI], 1.25-10.58), mortality during hospitalization (OR, 3.14; 95% CI, 2.37-4.16), and within 30 days from surgery (OR, 2.46; 95% CI, 1.95-3.10), after adjusting for other risk factors. FIB-4 was related to increased mortality in a dose-dependent manner for the 3 FIB-4 categories ≤1.3 (reference), >1.3 and <2.67, and ≥2.67, respectively; during hospitalization (OR, 1.89; 95% CI, 1.34-2.65 and OR, 4.70; 95% CI, 3.27-6.76) and within 30 days from surgery (OR, 1.77; 95% CI, 1.36-2.31 and OR, 3.55; 95% CI, 2.65-4.77). In a 1:1 propensity-matched sample (N = 1994 per group), the differences in mortality remained. Comparing the FIB-4 ≥2.67 versus the FIB-4 <2.67 groups, respectively, mortality during hospitalization was 5.1% vs 2.2% (OR, 2.70; 95% CI, 1.81-4.02), and 30-day mortality was 6.6% vs 3.4% (OR, 2.26; 95% CI, 1.62-3.14). CONCLUSIONS: A simple liver fibrosis marker is strongly associated with perioperative mortality in a population without apparent liver disease, and may aid in future surgical risk stratification and preoperative optimization.

The incidence and outcomes of healthcare-associated respiratory tract infections in non-ventilated neurocritical care patients: Results of a 10-year cohort study.

The incidence of healthcare-associated respiratory tract infections in non-ventilated patients (NVA-HARTI) in neurosurgical intensive care units (ICUs) is unknown. The impact of NVA-HARTI on patient outcomes and differences between NVA-HARTI and ventilator-associated healthcare-associated respiratory tract infections (VA-HARTI) are poorly understood. Our objectives were to report the incidence, hospital length of stay (LOS), ICU LOS, and mortality in NVA-HARTI patients and compare these characteristics to VA-HARTI in neurocritical care patients. This cohort study was conducted in a neurosurgical ICU in Moscow. From 2011 to 2020, all patients with an ICU LOS > 48 h were included. A competing risk model was used for survival and risk analysis. A total of 3,937 ICU admissions were analyzed. NVA-HARTI vs VA-HARTI results were as follows: cumulative incidence 7.2 (95%CI: 6.4-8.0) vs 15.4 (95%CI: 14.2-16.5) per 100 ICU admissions; incidence rate 4.2 ± 2.0 vs 9.5 ± 3.0 per 1000 patient-days in the ICU; median LOS 32 [Q1Q3: 21, 48.5] vs 46 [Q1Q3: 28, 76.5] days; median ICU LOS 15 [Q1Q3: 10, 28.75] vs 26 [Q1Q3: 17, 43] days; mortality 12.3% (95%CI: 7.9-16.8) vs 16.7% (95%CI: 13.6-19.7). The incidence of VA-HARTI decreased over ten years while NVA-HARTI incidence did not change. VA-HARTI was an independent risk factor of death, OR 1.54 (1.11-2.14), while NVA-HARTI was not. Our findings suggest that NVA-HARTI in neurocritical care patients represents a significant healthcare burden with relatively high incidence and associated poor outcomes. Unlike VA-HARTI, the incidence of NVA-HARTI remained constant despite preventive measures. This suggests that extrapolating VA-HARTI research findings to NVA-HARTI should be avoided.

Implementation of App-Based Diabetes Medication Management: Outpatient and Perioperative Clinical Decision Support.

PURPOSE OF REVIEW: Outpatient and perioperative therapeutic decision making for patients with diabetes involves increasingly complex medical-decision making due to rapid advances in knowledge and treatment modalities. We sought to review mobile decision support tools available to clinicians for this essential and increasingly difficult task, and to highlight the development and implementation of novel mobile applications for these purposes. RECENT FINDINGS: We found 211 mobile applications related to diabetes from the search, but only five were found to provide clinical decision support for outpatient diabetes management and none for perioperative decision support. We found a dearth of tools for clinicians to navigate these tasks. We highlight key aspects for effective development of future diabetes decision support. These include just-in-time availability, respect for the five rights of clinical decision support, and integration with clinical workflows including the electronic medical record.

Bridging the gap: interactive, case-based learning in radiology education.

Traditional teaching methods in radiology education have not kept pace with advances in technology that foster successful transition into independent practice. This deficit has been exacerbated by the COVID-19 pandemic, as the need for social distancing and the introduction of hybrid staffing models have decreased the critical educational interactions at the reading room workstations between staff and trainees. By leveraging interactive, case-based learning, educators have the opportunity to bridge the substantial gap between basic pattern recognition and successfully making a diagnosis in independent practice. For the educator, this signals a shift away from perfect case selection and presenter authority, and toward the role of a guide facilitating an active case-based learning experience. This form of learning is best accompanied by guided interpretation and iterative feedback with the goal of developing similar levels of mastery and autonomy among graduating trainees. In this article, we present the tools and methods for incorporating interactive cases into existing and novel teaching materials to meet the unique challenges educators are facing today.