Differences in Out-of-Hospital Cardiac Arrest Outcomes Among 5 Racial/Ethnic Groups.

OBJECTIVE: Out-of-hospital cardiac arrest (OHCA) is a major health problem and one of the leading causes of death in adults older than 40. Multiple prior studies have demonstrated survival disparities based on race/ethnicity, but most of these focus on a single racial/ethnic group. This study evaluated OHCA variables and outcomes among on 5 racial/ethnic groups. METHODS: This is a retrospective review of data for adult patients in the Cardiac Arrest Registry to Enhance Survival (CARES) from 3 racially diverse urban counties in the San Francisco Bay Area from May 2009 to October 2021. Stratifying by 5 racial/ethnic groups, we evaluated patient survival outcomes based on patient demographics, emergency medical services response location, cardiac arrest characteristics, and hospital interventions. Adjusted risk ratios were calculated for survival to hospital discharge, controlling for sex, age, response locations, median income of response location, arrest witness, shockable rhythm, and bystander cardiopulmonary resuscitation as well as clustering by census tract. RESULTS: There were 10,757 patient entries analyzed: 42% White, 24% Black, 18% Asian, 9.3% Hispanic, 6.0% Pacific Islander, 0.7% American Indian/Alaska Native, and 0.1% multiple races selected; however, only the first 5 racial/ethnic groups had sufficient numbers for comparison. The adjusted risk ratio for survival to hospital discharge was lower among the 4 racial/ethnic groups compared with the White reference group: Black (0.79, p = 0.003), Asian (0.78 p = 0.004), Hispanic (0.79, p = 0.018), and Pacific Islander (0.78, p = 0.041) groups. The risk difference for positive neurologic outcome was also lower among all 4 racial/ethnic groups compared with the White reference group. CONCLUSIONS: The Black, Asian, Hispanic, and Pacific Islander groups were less likely to survive to hospital discharge from OHCA when compared with the White reference group. No variables were associated with decreased survival across any of these 4 groups.

Novel Automated Self-adjusting Subcutaneous Insulin Algorithm Improves Glycemic Control and Physician Efficiency in Hospitalized Patients.

BACKGROUND: Hyperglycemia occurs in 22% to 46% of hospitalized patients, negatively affecting patient outcomes, including mortality, inpatient complications, length of stay, and hospital costs. Achieving inpatient glycemic control is challenging due to inconsistent caloric intake, changes from home medications, a catabolic state in the setting of acute illness, consequences of acute inflammation, intercurrent infection, and limitations in labor-intensive glucose monitoring and insulin administration. METHOD: We conducted a retrospective cross-sectional analysis at the University of California San Francisco hospitals between September 3, 2020 and September 2, 2021, comparing point-of-care glucose measurements in patients on nil per os (NPO), continuous total parenteral nutrition, or continuous tube feeding assigned to our novel automated self-adjusting subcutaneous insulin algorithm (SQIA) or conventional, physician-driven insulin dosing. We also evaluated physician efficiency by tracking the number of insulin orders placed or modified. RESULTS: The proportion of glucose in range (70-180 mg/dL) was higher in the SQIA group than in the conventional group (71.0% vs 69.0%, P = .153). The SQIA led to a lower proportion of severe hyperglycemia (>250 mg/dL; 5.8% vs 7.2%, P = .017), hypoglycemia (54-69 mg/dL; 0.8% vs 1.2%, P = .029), and severe hypoglycemia (<54 mg/dL; 0.3% vs 0.5%, P = .076) events. The number of orders a physician had to place while a patient was on the SQIA was reduced by a factor of more than 12, when compared with while a patient was on conventional insulin dosing. CONCLUSIONS: The SQIA reduced severe hyperglycemia, hypoglycemia, and severe hypoglycemia compared with conventional insulin dosing. It also improved physician efficiency by reducing the number of order modifications a physician had to place.

Accuracy and Feasibility of Real-time Continuous Glucose Monitoring in Critically Ill Patients After Abdominal Surgery and Solid Organ Transplantation.

OBJECTIVE: Glycemia management in critical care is posing a challenge in frequent measuring and adequate insulin dose adjustment. In recent years, continuous glucose measurement has gained accuracy and reliability in outpatient and inpatient settings. The aim of this study was to assess the feasibility and accuracy of real-time continuous glucose monitoring (CGM) in ICU patients after major abdominal surgery. RESEARCH DESIGN AND METHODS: We included patients undergoing pancreatic surgery and solid organ transplantation (liver, pancreas, islets of Langerhans, kidney) requiring an ICU stay after surgery. We used a Dexcom G6 sensor, placed in the infraclavicular region, for real-time CGM. Arterial blood glucose measured by the amperometric principle (ABL 800; Radiometer, Copenhagen, Denmark) served as a reference value and for calibration. Blood glucose was also routinely monitored by a StatStrip bedside glucose meter. Sensor accuracy was assessed by mean absolute relative difference (MARD), bias, modified Bland-Altman plot, and surveillance error grid for paired samples of glucose values from CGM and acid-base analyzer (ABL). RESULTS: We analyzed data from 61 patients and obtained 1,546 paired glucose values from CGM and ABL. Active sensor use was 95.1%. MARD was 9.4%, relative bias was 1.4%, and 92.8% of values fell in zone A, 6.1% fell in zone B, and 1.2% fell in zone C of the surveillance error grid. Median time in range was 78%, with minimum (<1%) time spent in hypoglycemia. StatStrip glucose meter MARD compared with ABL was 5.8%. CONCLUSIONS: Our study shows clinically applicable accuracy and reliability of Dexcom G6 CGM in postoperative ICU patients and a feasible alternative sensor placement site.

Association between psoriasis and cardiometabolic comorbidities in a racially and ethnically diverse low-income primary care population.

Psoriasis is associated with cardiometabolic comorbidities, including obesity, diabetes, hyperlipidaemia and hypertension. Many studies that established these associations originated from primarily White and/or relatively affluent populations. To evaluate whether there is a differential risk for cardiometabolic comorbidities in racial/ethnic minorities, we performed a cross-sectional analysis comparing cardiometabolic comorbidities between those with and without psoriasis in a racially and ethnically diverse population of 56 987 low-income patients, stratified by race/ethnicity, and assessed whether race/ethnicity acts as an effect modifier for cardiometabolic comorbidities. We found that psoriasis was statistically significantly associated with obesity, diabetes, hyperlipidaemia and hypertension. The association of psoriasis with comorbidities did not differ significantly by race/ethnicity; thus, we did not find evidence of effect modification. However, our diverse, low-income population had an extremely high baseline prevalence of cardiometabolic comorbidities compared with previous populations studied. Our results suggest education and intervention regarding modifiable risk factors are particularly important among vulnerable populations.

The walking man approach to interpreting the receiver operating characteristic curve and area under the receiver operating characteristic curve.

An accuracy study of a test that produces a wide range of results will often present a receiver operating characteristic (ROC) curve and report the area under the ROC curve (AUROC). The AUROC is a summary measure of how well the test discriminates between those with the condition or disease in question and those without it. A test that perfectly separates individuals with and without the condition has an AUROC of 1.0, and a test that doesn't separate them at all has an AUROC of 0.5. The AUROC is also the probability that a random individual with the condition will have a more abnormal test result than a random individual without the condition. In this Key Concepts article, we present our "walking man" approach to understanding ROC curves and the AUROC.

Association of an Emergency Critical Care Program With Survival and Early Downgrade Among Critically Ill Medical Patients in the Emergency Department.

OBJECTIVES: To determine whether implementation of an Emergency Critical Care Program (ECCP) is associated with improved survival and early downgrade of critically ill medical patients in the emergency department (ED). DESIGN: Single-center, retrospective cohort study using ED-visit data between 2015 and 2019. SETTING: Tertiary academic medical center. PATIENTS: Adult medical patients presenting to the ED with a critical care admission order within 12 hours of arrival. INTERVENTIONS: Dedicated bedside critical care for medical ICU patients by an ED-based intensivist following initial resuscitation by the ED team. MEASUREMENTS AND MAIN RESULTS: Primary outcomes were inhospital mortality and the proportion of patients downgraded to non-ICU status while in the ED within 6 hours of the critical care admission order (ED downgrade <6 hr). A difference-in-differences (DiD) analysis compared the change in outcomes for patients arriving during ECCP hours (2 pm to midnight, weekdays) between the preintervention period (2015-2017) and the intervention period (2017-2019) to the change in outcomes for patients arriving during non-ECCP hours (all other hours). Adjustment for severity of illness was performed using the emergency critical care Sequential Organ Failure Assessment (eccSOFA) score. The primary cohort included 2,250 patients. The DiDs for the eccSOFA-adjusted inhospital mortality decreased by 6.0% (95% CI, -11.9 to -0.1) with largest difference in the intermediate illness severity group (DiD, -12.2%; 95% CI, -23.1 to -1.3). The increase in ED downgrade less than 6 hours was not statistically significant (DiD, 4.8%; 95% CI, -0.7 to 10.3%) except in the intermediate group (DiD, 8.8%; 95% CI, 0.2-17.4). CONCLUSIONS: The implementation of a novel ECCP was associated with a significant decrease in inhospital mortality among critically ill medical ED patients, with the greatest decrease observed in patients with intermediate severity of illness. Early ED downgrades also increased, but the difference was statistically significant only in the intermediate illness severity group.

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings.

BACKGROUND: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. METHODS: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. RESULTS: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. CONCLUSION: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

A Pilot Randomized Clinical Trial of Early Ambulation after Groin Reconstruction with Sartorius Muscle Flaps.

The use of muscle flaps, such as the sartorius muscle, for groin coverage in high-risk vascular patients has been shown to reduce complication rates. However, it remains unknown whether earlier postoperative ambulation is associated with improved postoperative outcomes for groin muscle flaps following infrainguinal vascular surgery. Methods: We performed a pilot randomized trial to analyze the effect of early ambulation on postoperative outcomes in patients who had groin reconstruction with sartorius muscle flaps following infrainguinal vascular surgery at our academic institution. Results: Fourteen patients were randomized to standard ambulation (on postoperative day 6), and 14 patients were randomized to early ambulation (on postoperative day 2). The treatment arms were similar with respect to age, body mass index, risk category, smoking status, and comorbidities. Median length of stay was 6 days in the early group versus 7 days in the standard group. Immediate and long-term physical function and general health were better in the early group There were slightly more wound complications in the standard (57.1%) versus the early group (42.9%), and the early group had more lymphatic complications (35.7% versus 14.3%). Conclusions: The decision to ambulate a patient after this surgery continues to be a decision between the vascular and plastic surgeons. However, this pilot trial has shown the safety profile of early ambulation and that it should be considered for specific patients. Additionally, this trial has provided valuable information for performing a larger scale randomized controlled trial to determine the optimal postoperative protocol for patients with these reconstructions.

Utility of prehospital call center ambulance dispatch data for COVID-19 cluster surveillance: A retrospective analysis.

INTRODUCTION: Cluster surveillance, identification, and containment are primary outbreak management techniques; however, adapting these for low- and middle-income countries is an ongoing challenge. We aimed to evaluate the utility of prehospital call center ambulance dispatch (CCAD) data for surveillance by examining the correlation between influenza-like illness (ILI)-related dispatch calls and COVID-19 cases. METHODS: We performed a retrospective analysis of state-level CCAD and COVID-19 data recorded between January 1 and April 30, 2020, in Telangana, India. The primary outcome was a time series correlation between ILI calls in CCAD and COVID-19 case counts. Secondarily, we looked for a year-to-year correlation of ILI calls in the same period over 2018, 2019, and 2020. RESULTS: On average, ILI calls comprised 12.9% (95% CI 11.7%-14.1%) of total daily calls in 2020, compared to 7.8% (95% CI 7.6%-8.0%) in 2018, and 7.7% (95% CI 7.5%-7.7%) in 2019. ILI call counts from 2018, 2019, and 2020 aligned closely until March 19, when 2020 ILI calls increased, representing 16% of all calls by March 23 and 27.5% by April 7. In contrast to the significant correlation observed between 2020 and previous years' January-February calls (2020 and 2019-Durbin-Watson test statistic [DW] = 0.749, p < 0.001; 2020 and 2018-DW = 1.232, p < 0.001), no correlation was observed for March-April calls (2020 and 2019-DW = 2.012, p = 0.476; 2020 and 2018-DW = 1.820, p = 0.208). In March-April 2020, the daily reported COVID-19 cases by time series significantly correlated with the ILI calls (DW = 0.977, p < 0.001). The ILI calls on a specific day significantly correlated with the COVID-19 cases reported 6 days prior and up to 14 days after (cross-correlation > 0.251, the 95% upper confidence limit). CONCLUSIONS: The statistically significant time series correlation between ILI calls and COVID-19 cases suggests prehospital CCAD can be part of early warning systems aiding outbreak cluster surveillance, identification, and containment.

Validity of at-home rapid antigen lateral flow assay and artificial intelligence read to detect SARS-CoV-2.

BACKGROUND: The gold standard for COVID-19 diagnosis-reverse-transcriptase polymerase chain reaction (RT-PCR)- is expensive and often slow to yield results whereas lateral flow tests can lack sensitivity. METHODS: We tested a rapid, lateral flow antigen (LFA) assay with artificial intelligence read (LFAIR) in subjects from COVID-19 treatment trials (N = 37; daily tests for 5 days) and from a population-based study (N = 88; single test). LFAIR was compared to RT-PCR from same-day samples. RESULTS: Using each participant's first sample, LFAIR showed 86.2% sensitivity (95% CI 73.6%-98.8) and 94.3% specificity (88.8%-99.7%) compared to RT-PCR. Adjusting for days since symptom onset and repeat testing, sensitivity was 97.8% (89.9%-99.5%) on the first symptomatic day and decreased with each additional day. Sensitivity improved with artificial intelligence (AI) read (86.2%) compared to the human eye (71.4%). CONCLUSION: LFAIR showed improved accuracy compared to LFA alone. particularly early in infection.

Is AVPU comparable to GCS in critical prehospital decisions? - A cross-sectional study.

BACKGROUND: Advanced Trauma Life Support field triage utilizes the Glasgow Coma Scale (GCS) to assess the level of consciousness. However, prehospital care providers in low- and middle-income countries (LMICs) often use the Alert, Verbal, Pain, and Unresponsive (AVPU) scale to assess the level of consciousness. This study aimed to determine whether prehospital AVPU categorization correlates with mortality rates in trauma victims, similarly to GCS. METHODS: In this cross-sectional study conducted between November 2015 and January 2016, we enrolled a convenience sample of prehospital trauma-related field activations. The primary outcome measure was the probability of death within 48 h for each category of AVPU. RESULTS: In a convenience sample of 4514 activations, 1606 (35.6%) met exclusion criteria, four did not have AVPU, and four did not have GCS, leaving 2900 (64.2%) trauma activations with both AVPU and GCS available for analysis. Forty-eight-hour follow-up data were available for 2184 (75.3%) activations out of these 2900. The 48-h mortality rates for each category of AVPU were 1.1% (Alert), 4.3% (Verbal), 17.9% (Pain), 53.2% (Unresponsive); and, for each GCS-based injury severity category, they were 0.9% (Mild, GCS 13-15), 8.1% (Moderate, GCS 9-12), 43.5% (Severe, GCS ≤ 8). Overall, there was a statistically significant difference in GCS for each category of AVPU (p < 0.001) except between patients responding to verbal commands and those responding to pain (p = 0.18). The discriminative ability of AVPU (AUC 79.7% (95% CI 73.4-86.1)) and GCS (AUC 81.5% (95% CI 74.8-88.2)) for death within 48-h following hospital drop-off were comparable. CONCLUSION: EMT assessments of AVPU and GCS relate to each other, and AVPU predicts mortality at 48 h. Future studies using AVPU to assess the level of consciousness in prehospital trauma protocols may simplify their global application without impacting the overall quality of care.

Diagnostic accuracy of point-of-care ultrasonography for intussusception in children: A systematic review and meta-analysis.

OBJECTIVES: Ileocolic intussusception can be challenging to diagnose due to vague complaints, but rapid diagnosis and treatment can help prevent morbidity and mortality. Prior research has focused on radiologic ultrasound, with more recent studies focusing on point-of-care ultrasonography (POCUS). This systematic review and meta-analysis assesses the diagnostic accuracy of POCUS for children with suspected ileocolic intussusception. METHODS: PubMed, Embase, CINAHL, LILACS, the Cochrane databases, Google Scholar, conference abstracts, and bibliographies of selected articles were searched for studies evaluating the accuracy of POCUS for the diagnosis of intussusception in children. Data were dual extracted into a predefined worksheet, and quality analysis was performed with the QUADAS-2 tool. Data were summarized, and a meta-analysis was performed. RESULTS: Eleven studies (n = 2400 children) met our inclusion criteria. Overall, 14.4% of children had intussusception. POCUS was 95.1% (95% CI: 90.3% to 97.2%) sensitive and 98.1% (95% CI: 95.8% to 99.2%) specific with a positive likelihood ratio of 50 (95% CI: 23 to 113) and a negative likelihood ratio of 0.05 (95% CI: 0.03 to 0.09). CONCLUSIONS: POCUS has excellent diagnostic accuracy for intussusception in children presenting to the emergency department.

External validation of the 4C Mortality Score for hospitalised patients with COVID-19 in the RECOVER network.

OBJECTIVES: Estimating mortality risk in hospitalised SARS-CoV-2+ patients may help with choosing level of care and discussions with patients. The Coronavirus Clinical Characterisation Consortium Mortality Score (4C Score) is a promising COVID-19 mortality risk model. We examined the association of risk factors with 30-day mortality in hospitalised, full-code SARS-CoV-2+ patients and investigated the discrimination and calibration of the 4C Score. This was a retrospective cohort study of SARS-CoV-2+ hospitalised patients within the RECOVER (REgistry of suspected COVID-19 in EmeRgency care) network. SETTING: 99 emergency departments (EDs) across the USA. PARTICIPANTS: Patients ≥18 years old, positive for SARS-CoV-2 in the ED, and hospitalised. PRIMARY OUTCOME: Death within 30 days of the index visit. We performed logistic regression analysis, reporting multivariable risk ratios (MVRRs) and calculated the area under the ROC curve (AUROC) and mean prediction error for the original 4C Score and after dropping the C reactive protein (CRP) component. RESULTS: Of 6802 hospitalised patients with COVID-19, 1149 (16.9%) died within 30 days. The 30-day mortality was increased with age 80+ years (MVRR=5.79, 95% CI 4.23 to 7.34); male sex (MVRR=1.17, 1.05 to 1.28); and nursing home/assisted living facility residence (MVRR=1.29, 1.1 to 1.48). The 4C Score had comparable discrimination in the RECOVER dataset compared with the original 4C validation dataset (AUROC: RECOVER 0.786 (95% CI 0.773 to 0.799), 4C validation 0.763 (95% CI 0.757 to 0.769). Score-specific mortalities in our sample were lower than in the 4C validation sample (mean prediction error 6.0%). Dropping the CRP component from the 4C Score did not substantially affect discrimination and 4C risk estimates were now close (mean prediction error 0.7%). CONCLUSIONS: We independently validated 4C Score as predicting risk of 30-day mortality in hospitalised SARS-CoV-2+ patients. We recommend dropping the CRP component of the score and using our recalibrated mortality risk estimates.

Studies of diagnostic test accuracy: Partial verification bias and test result-based sampling.

BACKGROUND: Partial verification bias occurs in studies assessing the accuracy of existing diagnostic tests when a positive index test makes application of the reference standard more likely. METHODS: This article first describes alternative sampling frames for a diagnostic test accuracy study then discusses partial verification bias. RESULTS: One approach to avoiding partial verification bias is to apply the reference standard to all individuals who are positive on the index test and a random sample of those who are negative. Estimating sensitivity and specificity then requires adjusting for the sampling fraction in the test-negative group. CONCLUSION: If a finding was already used to determine who should get the definitive test, one can't look at those who got the definitive test to determine the usefulness of the finding.

Selection bias in estimating the relationship between prolonged ED boarding and mortality in emergency critical care patients.

OBJECTIVES: Studies have found that prolonged boarding time for intensive care unit (ICU) patients in the emergency department (ED) is associated with higher in-hospital mortality. However, these studies introduced selection bias by excluding patients with ICU admission orders who were downgraded and never arrived in the ICU. Consequently, they may overestimate mortality in prolonged ED boarders. METHODS: This was a retrospective cohort study at a single center covering the period from August 14, 2015 to August 13, 2019. Adult ED patients with medical ICU admission orders and at least 6 hours of subsequent critical care in either the ED or the ICU were included. Patients were classified as having either prolonged (>6 hours) or non-prolonged (≤6 hours) ED boarding. Downgraded patients were identified, and mortality was compared, both including and excluding downgraded patients. RESULTS: Of 1862 patients, 612 (32.9%) had prolonged boarding; at 6 hours after ICU admission order entry, they were still in the ED. The remaining 1250 (67.1%) had non-prolonged boarding; at 6 hours after the ICU admission order entry, they were already in the ICU. In-hospital mortality in the non-prolonged boarding group was 18.9%. In the prolonged boarding group, 296 (48.4%) patients were downgraded in the ED and never arrived in the ICU. Including these ED downgrades, the mortality in the prolonged boarding group was 13.4% (risk difference -5.5%, 95% confidence interval [CI] -8.9% to -2.0%, P = 0.0031). When we excluded downgrades, the mortality in the prolonged boarding group increased to 17.4% (risk difference -1.5%, 95% CI -6.2% to 3.2%, P = 0.5720). The lower mortality in the prolonged group was attributable to lower severity of illness (mean emergency critical care SOFA [eccSOFA] difference: -0.8, 95% CI -1.1 to -0.4, P < 0.0001). CONCLUSIONS: Excluding critical care patients who were downgraded in the ED leads to selection bias and overestimation of mortality among prolonged ED boarders.