Hanson, Andrew C.

ObjectiveWe aimed to characterize presentation and care pathways of patients with systemic lupus erythematosus (SLE), and delays in access to SLE‐specialized care.MethodsWe included patients with incident SLE from the Lupus Midwest Network registry. Time from the first medical encounter for SLE clinical manifestation to access to SLE‐specialized care, physician diagnosis, and treatment was estimated. Delays were defined as ≥6 months to access specialized care. We compared SLE manifestations, disease activity, and Systemic Lupus International Collaborating Clinics/American College of Rheumatology damage indexes (SDI) between patients with and without delays. Logistic regression models assessed associations with delays.ResultsThe study included 373 patients with SLE. The median time to access SLE‐specialized care was 1.1 (95% confidence interval [CI] 0.9–1.5) months, time to diagnosis was 30.6 (95% CI 18.9–48.1) months, and time to treatment initiation was 4.7 (95% CI 3.9–8.4) months. Approximately 25% of patients (93 out of 373) experienced delays accessing specialized care, which were associated with fewer SLE manifestations at first SLE‐related encounter (fewer than two SLE domains; 92% vs 72%, P < 0.001). Patients with mucocutaneous or musculoskeletal manifestations were less likely to experience delays, whereas hematologic (odds ratio [OR] 1.71, 95% CI 1.03–2.84) or antiphospholipid antibodies domains (OR 6.05, 95% CI 2.46–14.88) were associated with delays. Delays were associated with damage at first access to SLE‐specialized care (SDI ≥1; 30% vs 7%, P < 0.001).ConclusionPatients follow a heterogeneous pathway to receive care. One‐fourth of patients experienced delays accessing SLE‐specialized care, which was associated with disease‐related damage. Fewer manifestations, hematologic manifestations, or antiphospholipid antibodies were associated with delays.image

AbstractBackgroundEvaluations of critical bleeding and massive transfusion have focused on traumatic hemorrhage. However, most critical bleeding in hospitalized patients occurs outside trauma. The purpose of this study was to provide an in‐depth description examining the critical administration threshold (CAT; ≥3 units red blood cells (RBCs) in a 1‐h period) occurrences in nontraumatic hemorrhage. This will assist in establishing the framework for future investigations in nontraumatic hemorrhage.MethodsThis is an observational cohort study of adults experiencing critical bleeding defined as being CAT+ during hospitalization from 2016 to 2021 at a single academic institution. A CAT episode started with administration of the first qualifying RBC unit and ended at the time of completion of the last allogeneic unit prior to a ≥4‐h gap without subsequent transfusion. The primary goal was to describe demographic, clinical and transfusion characteristics of participants with nontraumatic critical bleeding.Results2433 patients suffered critical bleeding, most often occurring in the operating room (71.1%) followed by the intensive care unit (20.8%). 57% occurred on the initial day of hospitalization, with a median duration of 138 (36, 303) minutes. The median number of RBCs transfused during the episode was 5 (4, 8), with median total allogeneic units of 9 (4, 9). Hospital mortality was 19.2%. The most common cause of death was multi‐organ failure (50.3%), however death within 24 h was due to exsanguination (72.7%).DiscussionThe critical administration threshold may be employed to identify critical bleeding in non‐trauma settings of life‐threatening hemorrhage, with a mortality rate of approximately 20%.

Background: Hospitalization represents a major access point for prescription opioids, yet little is known regarding patterns and outcomes of opioid exposures before and after hospitalization for critical illness. Methods: This is an observational, population-based cohort study of adults (≥18 years) hospitalized for critical illness from 2010 to 2019. Multivariable models assess associations between opioid exposures prior to hospitalization, classified according to the Consortium to Study Opioid Risks and Trends, and posthospitalization opioid exposures and clinical outcomes through 1-year posthospitalization. Results: Of 11 496 patients, 6318 (55%) were men with a median age of 66 (51, 79) years and 40% (n = 4623) surgical admissions. Prehospitalization opioid availability included 8449 (73%) none, 2117 (18%) short-term, 471 (4%) episodic, and 459 (4%) long-term. Thirty-nine percent (4144/10 708) of hospital survivors were discharged with opioids, with higher prescribing rates for surgical admissions (55%). Greater preadmission opioid exposures were associated with higher prevalent opioid availability at 1 year (odds ratio [95% confidence interval] 24.1 [18.3-31.8], 9.42 [7.18-12.3], and 2.55 [2.08-3.12] for long-term, episodic, and short-term exposures, respectively, vs none, P < .001). Greater preadmission opioid exposures were associated with longer hospitalizations (1.13 [1.04-1.23], 1.15 [1.06-1.25], and 1.08 [1.04-1.13] multiplicative increase in geometric mean, P < .001), more readmissions (hazard ratio [HR] 2.08 [1.74-2.49], 1.88 [1.56-2.26], and 1.48 [1.33-1.64], P < .001), and higher 1-year mortality (HR 1.59 [1.28-1.98], 1.75 [1.41-2.18], and 1.49 [1.32-1.69], P < .001). Similar associations were observed across surgical and nonsurgical admissions. Conclusions: Prehospitalization opioid exposures in survivors of critical illness are associated with clinical outcomes through 1 year and may serve as important prognostic markers.

Abstract Objectives To examine the clinicopathologic features of patients with polymyalgia rheumatica (PMR) who had thoracic aorta repair surgery. Findings were compared with those of a cohort of patients with giant cell arteritis (GCA) requiring thoracic aorta repair. Methods All patients evaluated at Mayo Clinic in Rochester, MN, with Current Procedural Terminology (CPT) codes for thoracic aorta repair surgery between 2000–2021 were identified. All patients were screened for prior PMR diagnosis. Patients with PMR and no signs of GCA were categorized as clinically isolated PMR. The medical records of all patients were manually reviewed, and pathologists re-examined all the aortic tissues. Results Of the 4621 patients with at least one CPT code for thoracic aorta repair surgery, 43 patients were diagnosed with clinically isolated PMR before the surgery. Detailed histopathological examination of the aortic tissues revealed active inflammation in 30/43 (70%) patients after a median (IQR) of 10.0 (4.7–13.3) years from the PMR diagnosis. When compared with aortic tissue from patients with a prior diagnosis of GCA, the aorta of patients with PMR had more severe inflammation (Grade 3: 15/30 [50%] vs 5/34 [15%], P = 0.002). Patients with PMR and thoracic aorta repair may experience a 40% increased risk of mortality compared with the general population, but this did not reach statistical significance (standardized mortality ratio: 1.40; 95% CI: 0.91–2.07). Conclusions Some patients with PMR have subclinical aortic inflammation that is detectable many years after initial diagnosis and may contribute to the development of aortic aneurysm.

Background. Anesthesia providers categorize patients utilizing the American Society of Anesthesiologists Physical Status (ASA-PS) classification originally created by the ASA in 1941. There is published variability and discordance among providers when assigning patient ASA scores in part due to the subjectivity of scoring utilizing patient medical conditions, but variability is also found using objective findings like BMI. To date, there are few studies evaluating the accuracy of anesthesia providers’ ASA assignment based on objective body mass index (BMI) alone. The aim of this retrospective chart review is to determine improvement in accuracy of anesthesia providers to correctly assign patient ASA scores, based on BMI criteria added to the ASA-PS in October of 2014, utilizing a multifaceted strategy including creation of an active finance committee in the fall of 2015, multiple e-mail communications about the updated definitions and recommendations for ASA-PS scoring in the fall of 2015 and spring of 2016, a department grand rounds presentation in February 2016, placement of laminated copies of the ASA definitions and recommendations in the anesthesia chartrooms, and the development of a tool embedded into our EMR providing a recommendation of ASA-PS based on patient comorbidity findings. Methods. After attaining IRB approval, all eligible patients over the age of 18 who had surgical procedures under general anesthesia at Mayo Clinic in Rochester, MN, between January 1, 2010, and December 31, 2020, were retrospectively analyzed. A segmented logistic regression model was used to estimate the trends (per-year change in odds) of ASA under classification according to severity of obesity during 3 epochs: preimplementation (2010–2014), implementation (2015), and postimplementation (2016–2020). Results. A total of 16,467 patients of the 200,423 (8.2%) patients with obesity (class 1, 2, and 3) were underscored based on BMI alone. Accuracy of ASA-PS classification, as it pertains to BMI alone, was found to show meaningful improvement year-to-year following the updated ASA-PS guidelines with examples released in October of 2014 (P<0.001). Most of the improvement occurred in 2015–2017 with relatively little between-year variability in the rate of underscoring from 2017–2020. Conclusion. Despite updated ASA-PS published guidelines, providers may still be unaware of the updated guidelines and inclusion of examples used within the ASA-PS classification system. Accuracy of scoring did improve annually following the release of the updated guidelines with examples as well as department-wide educational activities on the topic. Additional education and awareness should be offered to those responsible for preanesthesia evaluation and assignment of ASA-PS in patients to improve accuracy as it pertains to BMI.

ABSTRACT Objective: The aim of the study is to develop a predictive model for in-hospital mortality in critically ill patients with cirrhosis and sepsis, using clinical and laboratory data. Design: This is a retrospective cohort study. Setting: Medical and mixed intensive care units (ICUs) of a tertiary medical center. Patients: Cirrhotic adults were admitted with sepsis to the ICUs from January of 2007 to May of 2017. Interventions: None. Measurements and Main Results: Of 2,595 ICU admissions of patients with cirrhosis, 277 with first ICU admission for sepsis were included in the analysis, and 37% died in the hospital. Patients who stayed in the ICU for at least 6 h (n = 275) were considered for the multivariate model. Ten-fold cross-validation was used to estimate best parameter values and model performance, and the final model was chosen as the model maximizing area under the receiver-operating characteristic curve. Variables in order of impact were Acute Physiology and Chronic Health Evaluation (APACHE) III score, initial serum lactate, conjugated bilirubin, serum creatinine, model for end-stage liver disease score, age, body mass index, and serum hemoglobin. The final best model from cross-validation presented an area under the receiver operator characteristic curve (AUC) of 0.75, using a cut-point of 50% estimated probability, sensitivity and specificity were 0.46 and 0.90, respectively, with positive predictive value of 0.72 and negative predictive value of 0.74. These results were similar to the APACHE III only model (AUC = 0.74, sensitivity = 0.43, specificity = 0.89, positive predictive value = 0.69, negative predictive value = 0.73). Conclusion: The combination of initial serum lactate level, conjugated bilirubin, initial serum creatinine, model for end-stage liver disease score, age, body mass index, and serum hemoglobin did not yield meaningful improvement in the AUC and did not provide advantage over the APACHE III score for the prediction of in-hospital mortality in critically ill patients with cirrhosis and sepsis.

Abstract Background The electronic health record (EHR) presents new opportunities for the timely identification of patients at high risk of critical illness and the implementation of preventive strategies. This study aims to externally validate an EHR‐based Elders Risk Assessment (ERA) score to identify older patients at high risk of future critical illness during a primary care visit. Methods This historical cohort study included patients aged ≥65 years who had primary care visits at Mayo Clinic Rochester, MN, between July 2019 and December 2021. The ERA score at the time of the primary care visit was used to predict critical illness, defined as death or ICU admission within 1 year of the visit. Results A total of 12,885 patients were included in the analysis. The median age at the time of the primary care visit was 75 years, with 44.6% being male. 93.7% of participants were White, and 64.2% were married. The median (25th, 75th percentile) ERA score was 4 (0, 9). 11.3% of study participants were admitted to the ICU or died within 1 year of the visit. The ERA score predicted critical illness within 1 year of a primary care visit with an area under the receiver operating characteristic curve of 0.84 (95% CI 0.83–0.85), which indicates good discrimination. An ERA score of 9 was identified as optimal for implementing and testing potential preventive strategies, with the odds ratio of having the primary outcome in patients with ERA score ≥9 being 11.33 (95%CI 9.98–12.87). Conclusions This simple EHR‐based risk assessment model can predict critical illness within 1 year of primary care visits in older patients. The findings of this study can serve as a basis for testing and implementation of preventive strategies to promote the well‐being of older adults at risk of critical illness and its consequences.

BACKGROUND: Preoperative anemia is associated with adverse outcomes in cardiac surgery, yet it remains unclear what proportion of this association is mediated through red blood cell (RBC) transfusions. METHODS: This is a historical observational cohort study of adults undergoing coronary artery bypass grafting or valve surgery on cardiopulmonary bypass at an academic medical center between May 1, 2008, and May 1, 2018. A mediation analysis framework was used to evaluate the associations between preoperative anemia and postoperative outcomes, including a primary outcome of acute kidney injury (AKI). Intraoperative RBC transfusions were evaluated as mediators of preoperative anemia and outcome relationships. The estimated total effect, average direct effect of preoperative anemia, and percent of the total effect mediated through transfusions are presented with 95% confidence intervals and P -values. RESULTS: A total of 4117 patients were included, including 1234 (30%) with preoperative anemia. Overall, 437 of 4117 (11%) patients went on to develop AKI, with a greater proportion of patients having preoperative anemia (219 of 1234 [18%] vs 218 of 2883 [8%]). In multivariable analyses, the presence of preoperative anemia was associated with increased postoperative AKI (6.4% [4.2%–8.7%] absolute difference in percent with AKI, P < .001), with incremental decreases in preoperative hemoglobin concentrations displaying greater AKI risk (eg, 11.9% [6.9%–17.5%] absolute increase in probability of AKI for preoperative hemoglobin of 9 g/dL compared to a reference of 14 g/dL, P < .001). The association between preoperative anemia and postoperative AKI was primarily due to direct effects of preoperative anemia (5.9% [3.6%–8.3%] absolute difference, P < .001) rather than mediated through intraoperative RBC transfusions (7.5% [−4.3% to 21.1%] of the total effect mediated by transfusions, P = .220). Preoperative anemia was also associated with longer hospital durations (1.07 [1.05–1.10] ratio of geometric mean length of stay, P < .001). Of this total effect, 38% (22%, 62%; P < .001) was estimated to be mediated through subsequent intraoperative RBC transfusion. Preoperative anemia was not associated with reoperation or vascular complications. CONCLUSIONS: Preoperative anemia was associated with higher odds of AKI and longer hospitalizations in cardiac surgery. The attributable effects of anemia and transfusion on postoperative complications are likely to differ across outcomes. Future studies are necessary to further evaluate mechanisms of anemia-associated postoperative organ injury and treatment strategies.

Objectives The objective is to examine utilisation of cardiovascular preventive services in patients with rheumatoid arthritis (RA), compared with a non-RA population, and to examine cardiovascular disease (CVD) screening rates among RA patients without diabetes mellitus (DM), hypertension or hyperlipidaemia to non-RA patients with one of these diagnoses. Methods All ≥18-year-old patients with an RA diagnosis living in one of eight Minnesota counties on 1 January 2015 were included and matched (1:1) by sex, age and county to non-RA comparators. Rates of screening for CVD risk factors, including DM (ie, glucose), hypertension (ie, blood pressure) and hyperlipidaemia (ie, lipids), were compared between groups using Cox models. Results The study included 1614 patients with RA and 1599 non-RA comparators. DM screening was more common among patients with RA (HR: 1.10, 95% CI: 1.01 to 1.19), as was hypertension screening (HR: 1.37, 95% CI: 1.24 to 1.52). Hyperlipidaemia screening in RA was similar to comparators (HR: 0.99, 95% CI: 0.89 to 1.10). Conversely, patients with RA and no CVD risk factors had a lower probability of undergoing diabetes (HR: 0.67, 95% CI: 0.57 to 0.78) and hyperlipidaemia screening (HR: 0.65, 95% CI: 0.54 to 0.79) than non-RA patients with only one CVD risk factor diagnosis. Hypertension screening was similar between both groups. Conclusions RA patients undergo CVD preventive screening at rates at least comparable to the general population. However, patients with RA as their sole CVD risk factor were less likely to undergo screenings, despite an equivalent-to-higher risk as the traditional CVD risk factors. These findings demonstrate opportunities for improvement of RA patient care.