Explore the vast range of titles available.

A retrospective cohort study analyzed data from a Louisiana health system whose population is 31% black non-Hispanic. A total of 76.9% of the patients who were hospitalized with Covid-19 and 70.6% of those who died from the disease were black. Black race was not associated with higher in-hospital mortality after adjustment for patients’ baseline characteristics.

Using a novel recruitment method and paired molecular and antibody testing for severe acute respiratory syndrome coronavirus 2 infection, we determined seroprevalence in a racially diverse municipality in Louisiana, USA. Infections were highly variable by ZIP code and differed by race/ethnicity. Overall census-weighted seroprevalence was 6.9%, and the calculated infection fatality ratio was 1.63%.

By using paired molecular and antibody testing for severe acute respiratory syndrome coronavirus 2 infection, we determined point prevalence and seroprevalence in Louisiana, USA, during the second phase of reopening. Infections were highly variable by race and ethnicity, work environment, and ZIP code. Census-weighted seroprevalence was 3.6%, and point prevalence was 3.0%.

Objective Determine whether an individual is at greater risk of severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) infection because of their community or their individual risk factors. Study design and setting 4,752 records from two large prevalence studies in New Orleans and Baton Rouge, Louisiana were used to assess whether zip code tabulation areas (ZCTA)-level area deprivation index (ADI) or individual factors accounted for risk of infection. Logistic regression models assessed associations of individual-level demographic and socioeconomic factors and the zip code-level ADI with SARS-CoV-2 infection. Results In the unadjusted model, there were increased odds of infection among participants residing in high versus low ADI (both cities) and high versus mid-level ADI (Baton Rouge only) zip codes. When individual-level covariates were included, the odds of infection remained higher only among Baton Rouge participants who resided in high versus mid-level ADI ZCTAs. Several individual factors contributed to infection risk. After adjustment for ADI, race and age (Baton Rouge) and race, marital status, household size, and comorbidities (New Orleans) were significant. Conclusions While higher ADI was associated with higher risk of SARS-CoV-2 infection, individual-level participant characteristics accounted for a significant proportion of this association. Additionally, stage of the pandemic may affect individual risk factors for infection.

Background. Nocardia species cause infections in both immunocompromised and otherwise immunocompetent patients, although the mechanisms defining susceptibility in the latter group are elusive. Anticytokine autoantibodies are an emerging cause of pathogen-specific susceptibility in previously healthy human immunodeficiency virus-uninfected adults, including anti–granulocyte macrophage colony-stimulating factor (GM-CSF) autoantibodies with cryptococcal meningitis. Methods. Plasma from patients with disseminated/extrapulmonary nocardiosis and healthy controls was screened for anticytokine autoantibodies using a particle-based approach. Autoantibody function was assessed by intranuclear staining for GM-CSF–induced STAT5 phosphorylation in normal cells incubated with either patient or normal plasma. GM-CSF–mediated cellular activation by Nocardia was assessed by staining for intracellular cytokine production and intranuclear STAT5 phosphorylation. Results. We identified neutralizing anti–GM-CSF autoantibodies in 5 of 7 patients studied with central nervous system nocardiosis and in no healthy controls (n = 14). GM-CSF production was induced by Nocardia in vitro, suggesting a causative role for anti–GM-CSF autoantibodies in Nocardia susceptibility and dissemination. Conclusions. In previously healthy adults with otherwise unexplained disseminated/extrapulmonary Nocardia infections, anti–GM-CSF autoantibodies should be considered. Their presence may suggest that these patients may be at risk for later development of pulmonary alveolar proteinosis or other opportunistic infections, and that patients may benefit from therapeutic GM-CSF administration.

Background and Aims: Atrial fibrillation frequently occurs in the postoperative period of cardiac surgery, associated with an increase in morbidity and mortality. The scores POAF, CHA2DS2-VASc and HATCH demonstrated a validated ability to predict atrial fibrillation after cardiac surgery (AFCS). The objective is to develop and validate a risk score to predict AFCS from the combination of the variables with highest predictive value of POAF, CHA2DS2-VASc and HATCH models. Methods: We conducted a single-center cohort study, performing a retrospective analysis of prospectively collected data. The study included consecutive patients undergoing cardiac surgery in 2010-2016. The primary outcome was the development of new-onset AFCS. The variables of the POAF, CHA2DS2-VASc and HATCH scores were evaluated in a multivariate regression model to determine the predictive impact. Those variables that were independently associated with AFCS were included in the final model. Results: A total of 3113 patients underwent cardiac surgery, of which 21% presented AFCS. The variables included in the new score COM-AF were: age (≥75: 2 points, 65-74: 1 point), heart failure (2 points), female sex (1 point), hypertension (1 point), diabetes (1 point), previous stroke (2 points). For the prediction of AFCS, COM-AF presented an AUC of 0.78 (95% CI 0.76-0.80), the rest of the scores presented lower discrimination ability (P < 0.001): CHA2DS2-VASc AUC 0.76 (95% CI 0.74-0.78), POAF 0.71 (95% CI 0.69-0.73) and HATCH 0.70 (95% CI: 0, 67-0.72). Multivariable analysis demonstrated that COM-AF score was an independent predictor of AFCS: OR 1,91 (IC 95% 1,63-2,23). Conclusion: From the combination of variables with higher predictive value included in the POAF, CHA2DS2-VASc, and HATCH scores, a new risk model system called COM-AF was created to predict AFCS, presenting a greater predictive ability than the original ones. Being necessary future prospective validations.

Introduction: High leuko-glycaemic index (LGI) (> 2000) has been associated with poor prognosis in many critical care settings. However, there is no evidence of LGI’s prognostic value in the postoperative period of coronary artery bypass grafting (CABG). This study aims to analyze the prognostic value of LGI in the postoperative period of CABG. Methods: Single-center retrospective analysis of prospectively collected data was performed. Consecutive adult patients undergoing CABG between 2007 and 2019 were included. Blood glucose levels and white blood cells count were evaluated in the immediate postoperative period. LGI was calculated by multiplying both values and dividing them by 1,000 and analyzed in quartiles. Receiver operating characteristic curve was used to determine the best cutoff value. The primary combined endpoint was in-hospital mortality, low cardiac output (LCO), or acute kidney injury (AKI). Secondary endpoints included in-hospital death, AKI, atrial fibrillation, and LCO. Results: The study evaluated 3,813 patients undergoing CABG (88.5% male, 89.8% off-pump surgery, aged 64.6 years [standard deviation 9.6]). The median of LGI was 2,035. Presence of primary endpoint significantly increased per LGI quartile (9.2%, 9.7%, 11.8%, and 15%; P<0.001). High LGI was associated with increased occurrence of in-hospital mortality, LCO, AKI, and atrial fibrillation. The best prognostic cutoff value for primary endpoint was 2,000. In a multivariate logistic regression model, high LGI was independently associated with in-hospital death, LCO, or AKI. Conclusion: High LGI was an independent predictor of in-hospital mortality, LCO, or AKI in postoperative period of CABG. It was also associated with higher in-hospital death.

Venoarterial extracorporeal membrane oxygenation (VA ECMO) is a form of temporary mechanical circulatory support and simultaneous extracorporeal gas exchange for acute cardiorespiratory failure, including refractory cardiogenic shock (CS) and cardiac arrest (CA). Few studies have assessed predictors of successful weaning (SW) from VA ECMO. This systematic review and meta-analysis aimed to identify a multiparameter strategy associated with SW from VA ECMO. PubMed and the Cochrane Library and the International Clinical Trials Registry Platform were searched. Studies reporting adult patients with CS or CA treated with VA ECMO published from the year 2000 onwards were included. Primary outcomes were hemodynamic, laboratory, and echocardiography parameters associated with a VA ECMO SW. A total of 11 studies (n=653) were included in this review. Pooled VA ECMO SW was 45% (95%CI: 39-50%, I2 7%) and in-hospital mortality rate was 46.6% (95%CI: 33-60%; I2 36%). In the SW group, pulse pressure [MD 12.7 (95%CI: 7.3-18) I2 = 0%] and mean blood pressure [MD 20.15 (95%CI: 13.8-26.4 I2 = 0) were higher. They also had lower values of creatinine [MD -0.59 (95%CI: -0.9 to -0.2) I2 = 7%], lactate [MD -3.1 (95%CI: -5.4 to -0.7) I2 = 89%], and creatine kinase [-2779.5 (95%CI: -5387 to -171) I2 = 38%]. And higher left and right ventricular ejection fraction, MD 17.9% (95%CI: -0.2-36.2) I2 = 91%, and MD 15.9% (95%CI 11.9-20) I2 = 0%, respectively. Different hemodynamic, laboratory, and echocardiographic parameters were associated with successful device removal. This systematic review demonstrated the relationship of multiparametric assessment on VA ECMO SW.

The Ac ute R espiratory I llness S urveillance (AcRIS) Study was a low-interventional trial that examined voice changes with respiratory illnesses. This longitudinal trial was the first of its kind, conducted in a fully decentralized manner via a Bring Your Own Device mobile application. The app enabled social-media-based recruitment, remote consent, at-home sample collection, and daily remote voice and symptom capture in real-world settings. From April 2021 to April 2022, the trial enrolled 9151 participants, followed for up to eight weeks. Despite mild symptoms experienced by reverse transcription polymerase chain reaction (RT-PCR) positive participants, two machine learning algorithms developed to screen respiratory illnesses reached the pre-specified success criteria. Algorithm testing on independent cohorts demonstrated that the algorithm’s sensitivity increased as symptoms increased, while specificity remained consistent. Study findings suggest voice features can identify individuals with viral respiratory illnesses and provide valuable insights into fully decentralized clinical trials design, operation, and adoption (study registered at ClinicalTrials.gov (NCT04748445) on 5 February 2021).

Purpose This paper aims to extend the consideration of distributed leadership in health-care settings. Leadership is typically studied from the classical notion of the place of single leaders and continues to examine distributed leadership within small teams or horizontally. The purpose is to develop a practical understanding of how distributed leadership may occur vertically, between different layers of the health-care leadership hierarchy, examining its influence on health-care outcomes across two hospitals. Design/methodology/approach Using semi-structured interviews, data were collected from 107 hospital employees (including executive leadership, clinical management and clinicians) from two hospitals in Australia and the USA. Using thematic content analysis, an iterative process was adopted characterized by alternating between social identity and distributed leadership literature and empirical themes to answer the question of how the practice of distributed leadership influences performance outcomes in hospitals? Findings The perceived social identities of leadership groups shaped communication and performance both positively and negatively. In one hospital a moderating structure emerged as a leadership dyad, where leadership was distributed vertically between hospital hierarchal layers, observed to overcome communication limitations. Findings suggest dyad creation is an effective mechanism to overcome hospital hierarchy-based communication issues and ameliorate health-care outcomes. Originality/value The study demonstrates how current leadership development practices that focus on leadership relational and social competencies can benefit from a structural approach to include leadership dyads that can foster these same competencies. This approach could help develop future hospital leaders and in doing so, improve hospital outcomes.