Identifying predictors and determining mortality rates of septic cardiomyopathy and sepsis-related cardiogenic shock: A retrospective, observational study.

INTRODUCTION: Septic shock is a severe form of sepsis that has a high mortality rate, and a substantial proportion of these patients will develop cardiac dysfunction, often termed septic cardiomyopathy (SCM). Some SCM patients may develop frank cardiac failure, termed sepsis-related cardiogenic shock (SeRCS). Little is known of SeRCS. This study describes baseline characteristics of patients with SCM and SeRCS compared to patients with septic shock without cardiac dysfunction. We compare clinical outcomes among SCM, SeRCS, and septic shock, and identify risk factors for the development of SCM and SeRCS. METHODS: Septic patients admitted to the ICU with an echocardiogram obtained within 72 hours were included. Left ventricular ejection fraction of ≤55% was used to define SCM, and cardiac index ≤2.1 L/min/m2 among patients with SCM defined SeRCS. Machine learning was used to identify risk factors for development of SCM and SeRCS. Logistic regression was used to compare mortality among groups. RESULTS: Among 1229 patients, 977 patients had septic shock without cardiac dysfunction, 207 had SCM, and 45 had SeRCS. In patients with septic shock, the strongest predictor for developing SCM and SeRCs was a prior history of cardiac dysfunction. Mortality did not significantly differ among the three groups. CONCLUSIONS: SCM and SeRCS affect a minority of patients with septic shock, disproportionately affecting individuals with a history of cardiac disease. We did not identify a mortality difference associated with SCM or SeRCS. Additional work is needed to define further subtypes and treatment options for this patient population.

Patient experiences with SARS-CoV-2: Associations between patient experience of disease and coping profiles.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2, (SARS-CoV-2,) caused an influx of patients with acute disease characterized by a variety of symptoms termed COVID-19 disease, with some patients going on to develop post-acute COVID-19 syndrome. Individual factors like sex or coping styles are associated with a person's disease experience and quality of life. Individual differences in coping styles used to manage COVID-19 related stress correlate with physical and mental health outcomes. Our study sought to understand the relationship between COVID-19 symptoms, severity of acute disease, and coping profiles. METHODS: An online survey to assess symptoms, functional status, and recovery in a large group of patients was nationally distributed online. The survey asked about symptoms, course of illness, and included the Brief-COPE and the adapted Social Relationship Inventory. We used descriptive and cluster analyses to characterize patterns of survey responses. RESULTS: 976 patients were included in the analysis. The most common symptoms reported by the patients were fatigue (72%), cough (71%), body aches/joint pain (66%), headache (62%), and fever/chills (62%). 284 participants reported PACS. We described three different coping profiles: outward, inward, and dynamic copers. DISCUSSION: Fatigue, cough, and body aches/joint pains were the most frequently reported symptoms. PACS patients were sicker, more likely to have been hospitalized. Of the three coping profiles, outward copers were more likely to be admitted to the hospital and had the healthiest coping strategies. Dynamic copers activated several coping strategies both positive and negative; they were also younger and more likely to report PACS. CONCLUSION: Cough, fatigue, and body aches/joint pain are common and most important to patients with acute COVID-19, while shortness of breath defined the experience for patients with PACS. Of the three coping profiles, dynamic copers were more likely to report PACS. Additional investigations into coping profiles in general, and the experience of COVID-19 and PACS is needed.

The Epidemiology of Acute Respiratory Distress Syndrome Before and After Coronavirus Disease 2019.

Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome of high morbidity and mortality with global impact. Current epidemiologic estimates are imprecise given differences in patient populations, risk factors, resources, and practice styles around the world. Despite improvement in supportive care which has improved mortality, effective targeted therapies remain elusive. The Coronavirus Disease 2019 pandemic has resulted in a large number of ARDS cases that, despite less heterogeneity than multietiologic ARDS populations, still exhibit wide variation in physiology and outcomes. Intensive care unit rates of death have varied widely in studies to date because of a variety of patient and hospital-level factors. Despite some controversy, the best management of these patients is likely the same supportive measures shown to be effective in classical ARDS. Further epidemiologic studies are needed to help characterize the epidemiology of ARDS subphenotypes to facilitate identification of targeted therapies.

Enhanced Detection of Community-Acquired Pneumonia Pathogens With the BioFire® Pneumonia FilmArray® Panel.

BACKGROUND: Although most observational studies identify viral or bacterial pathogens in 50% or less of patients hospitalized with community-acquired pneumonia (CAP), we previously demonstrated that a multi-test bundle (MTB) detected a potential pathogen in 73% of patients. This study compares detection rates for potential pathogens with the MTB versus the Biofire® Pneumonia FilmArray® panel (BPFA) multiplex PCR platform and presents an approach for integrating BPFA results as a foundation for subsequent antibiotic stewardship (AS) activities. METHODS: Between January 2017 to March 2018, all patients admitted for CAP were enrolled. Patients were considered evaluable if all elements of the MTB and the BPFA were completed, and they met other a priori inclusion criteria. The primary endpoint was the percentage of potential pathogens detected using the MTB (8 viral and 6 bacterial targets) versus the BPFA (8 viral and 18 bacterial targets). Blood and sputum cultures were performed on all patients. Two or more procalcitonin (PCT) levels assisted clinical assessments as to whether detected bacteria were invading or colonizing. RESULTS: Of 585 enrolled patients, 274 were evaluable. A potential viral pathogen was detected in 40.5% with MTB versus 60.9% of patients with BPFA with an odds ratio (95% CI) of 9.00 (4.12 to 23.30) p<0.01. A potential bacterial pathogen was identified in 66.4% with the MTB vs 75.5% with the BPFA odds ratio (95% CI) of 2.09 (1.24 to 3.59), p 0.003). Low PCT levels helped identify detected bacteria as colonizers.