Early, biomarker-guided steroid dosing in COVID-19 Pneumonia: a pilot randomized controlled trial.

ClinicalTrials.gov identifier (NCT number): NCT03852537 , Registered February 25, 2019.

Clinical Strategies to Prevent Acute Respiratory Distress Syndrome.

Acute respiratory distress syndrome (ARDS) remains an important clinical entity in the intensive care unit with a significant impact on morbidity and mortality. Effective therapeutic interventions are limited; thus current research focus has shifted from treatment to the prevention of this pulmonary syndrome. In recent decades, a decrease in the incidence of ARDS has been observed and this reduction is largely due to preventive strategies including safe lung ventilation practices, avoidance of iatrogenic exposures, and improvement in care of predisposing conditions such as sepsis and pneumonia. Early identification of at-risk patients, prompt treatment of predisposing conditions, and adoption of evidence-based best practice including restrictive transfusion strategies, conservative fluid management, avoidance of large tidal volume ventilation, and aspiration precaution practices are key preventive strategies with demonstrated benefits. There are currently no effective pharmacological preventive strategies for ARDS.

Does Low FEV1 in Addition to Fixed Ratio and/or Lower Limit of Normal of FEV1/FVC Improve Prediction of Mortality in COPD? The NHANES-III-linked-mortality Cohort.

PURPOSE: There is presently an ongoing debate on the relative merits of suggested criteria for spirometric airway obstruction. This study tests the null hypothesis that no superiority exists with the use of fixed ratio (FR) of forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) < 0.7 versus less than lower limit predicted (LLN) criteria with or without FEV1 <80% predicted in regards to future mortality. METHODS: In 1988-1994 the Third National Health and Nutrition Examination Survey (NHANES III) measured FEV1 and FVC with mortality follow-up data through December 31, 2011. For this survival analysis 7472 persons aged 40 and over with complete data formed the analytic sample. RESULTS: There were a total of 3554 deaths. Weighted Cox proportional hazards regression revealed an increased hazard ratio in persons with both fixed ratio and lower limit of normal with a low FEV1 (1.79, p < 0.0001), in those with fixed ratio only with a low FEV1 (1.77, p < 0.0001), in those with abnormal fixed ratio only with a normal FEV1 (1.28, p < 0.0001) compared with persons with no airflow obstruction (reference group). These remained significant after adjusting for demographic variables and other confounding variables. CONCLUSIONS: The addition of FEV1 < 80% of predicted increased the prognostic power of the fixed ratio <0.7 and/or below the lower limit of predicted criteria for airway obstruction.

A Rapidly Enlarging Asymptomatic Parapneumonic Effusion: A Case Report.

A pleural effusion is an accumulation of fluid in the pleural space due to an imbalance between formation and removal. They're commonly caused by heart failure or infections. We report a case of a 56-year-old male with community-acquired pneumonia and a trace pleural effusion on presentation. Despite clinical improvement with antibiotic therapy, the effusion significantly increased on day two. This case report is unique because the patient had an enlarging effusion, but remained asymptomatic and denied worsening shortness of breath, chest pain, or cough. The patient was treated successfully with chest tube placement and intrapleural fibrinolytic therapy. This report emphasizes the importance of repeat imaging for asymptomatic parapneumonic effusions (PPE) that can complicate community-acquired pneumonia. We aim to raise awareness of the atypical presentation and management of parapneumonic effusions through a case report.

Influenza-Associated Outcomes and Healthcare Utilization by Race and Ethnicity in the USA: a Retrospective Cohort Study Using the National Inpatient Sample Database.

BACKGROUND: The influenza virus continues to be a public health concern every season. We aimed to evaluate influenza-associated outcomes and healthcare utilization by race and ethnicity. METHODS: We conducted a retrospective cohort study using the National Inpatient Sample across 2019 and 2020. Influenza pneumonia was selected as the principal diagnosis. Outcomes included mortality, use of respiratory support ventilation, length of stay, and total hospitalization charge. Regression models were adjusted for age, gender, Charlson Comorbidity Index, hospitals' region, bed size, teaching status, insurance status, and median income. RESULTS: We identified 73,098 individuals hospitalized with influenza pneumonia; 39,807 and 33,291 were admitted in 2019 and 2020, respectively. The sample included 49,829 (68%) White, 11,356 (15.5%) Black, 7526 (10%) Hispanic, 1860 (2.5%) Asian/Pacific, and 617 (0.84%) Native American patients. In-hospital mortality rates and respiratory support (non-invasive ventilation and invasive mechanical ventilation) in 2019 and 2020 were not significantly different across all the races. In 2019 and 2020, the adjusted odds ratios of in-patient mortality were not significantly different. Asians had higher odds of receiving NIV in 2019 but not in 2020 compared to White patients (adjusted odds ratio (aOR) 1.67, p value 0.04). The adjusted odds ratios for receiving IMV were not significantly different between the races in 2019 and 2020. CONCLUSIONS: This study contributes valuable insight into influenza-associated outcomes and healthcare utilization patterns among diverse racial and ethnic groups. Disparities in healthcare utilization were observed among younger (< 65 years) individuals of Black and Hispanic ethnicity.

The Neutrophil/Lymphocyte Ratio and Outcomes in Hospitalized Patients with Community-Acquired Pneumonia: A Retrospective Cohort Study.

We aimed to assess the prognostic role of the neutrophil/lymphocyte ratio (NLR) in community-acquired pneumonia (CAP) via a single-center retrospective cohort of hospitalized adult patients from 1/2009 to 12/2019. Patients were dichotomized into lower NLR (≤12) and higher NLR (>12). The primary outcome was mortality. ICU admission and hospital- and ICU-free days were secondary outcomes. The pneumonia severity index (PSI) and the NLR's ability to predict outcomes was also tested. An NLR ≤12 was observed in 2513 (62.2%) patients and >12 in 1526 (37.8%). After adjusting for PSI, the NLR was not associated with hospital mortality (odds ratio [OR] 1.115; 95% confidence interval [CI] 0.774, 1.606; p = 0.559), but it was associated with a higher risk of ICU admission (OR 1.405; 95% CI 1.216, 1.624; p < 0.001). The PSI demonstrated acceptable discrimination for mortality (area under the receiver operating characteristic curve [AUC] 0.78; 95% CI 0.75, 0.82) which was not improved by adding the NLR (AUC 0.78; 95% CI 0.75, 0.82, p = 0.4476). The PSI's performance in predicting ICU admission was also acceptable (AUC 0.75; 95% CI 0.74, 0.77) and improved by including the NLR (AUC 0.76, 95% CI 0.74, 0.77, p = 0.008), although with limited clinical significance. The NLR was not superior to the PSI for predicting mortality in hospitalized CAP patients.

Early machine learning prediction of hospitalized patients at low risk of respiratory deterioration or mortality in community-acquired pneumonia: Derivation and validation of a multivariable model.

Current prognostic tools for pneumonia predominantly focus on mortality, often neglecting other crucial outcomes such as the need for advanced respiratory support. The objective of this study was to develop and validate a tool that predicts the early risk of non-occurrence of respiratory deterioration or mortality. We conducted a single-center, retrospective cohort study involving hospitalized adult patients with community-acquired pneumonia (CAP) and acute hypoxic respiratory failure from January 2009 to December 2019 (n = 4379). We employed the gradient boosting machine (GBM) learning to create a model that estimates the likelihood of patients requiring advanced respiratory support (high flow nasal cannula [HFNC], non-invasive mechanical ventilation [NIMV], and invasive mechanical ventilation [IMV]) or facing mortality during hospitalization. This model utilized readily available data including demographic, physiologic, and laboratory data, sourced from electronic health records and obtained within the first six hours of admission. Out of the cohort, 890 patients (25.2%) either required advanced respiratory support or died during their hospital stay. Our predictive model displayed superior discrimination and higher sensitivity (cross-validation C-statistic = 0.71; specificity = 0.56; sensitivity = 0.72) compared to the pneumonia severity index (PSI) (C-statistic = 0.65; specificity = 0.91; sensitivity = 0.24; P value < 0.001), while maintaining a negative predictive value (NPV) of approximately 0.85. These data demonstrate that our machine learning model predicted the non-occurrence of respiratory deterioration or mortality among hospitalized CAP patients more accurately than the PSI. The enhanced sensitivity of this model holds potential for reliably excluding low-risk patients from pneumonia clinical trials.

Development and Validation of an Acute Respiratory Distress Syndrome Prediction Model in Coronavirus Disease 2019: Updated Lung Injury Prediction Score.

OBJECTIVE: To develop and validate an updated lung injury prediction score for coronavirus disease 2019 (COVID-19) (c-LIPS) tailored for predicting acute respiratory distress syndrome (ARDS) in COVID-19. PATIENTS AND METHODS: This was a registry-based cohort study using the Viral Infection and Respiratory Illness Universal Study. Hospitalized adult patients between January 2020 and January 2022 were screened. Patients who qualified for ARDS within the first day of admission were excluded. Development cohort consisted of patients enrolled from participating Mayo Clinic sites. The validation analyses were performed on remaining patients enrolled from more than 120 hospitals in 15 countries. The original lung injury prediction score (LIPS) was calculated and enhanced using reported COVID-19-specific laboratory risk factors, constituting c-LIPS. The main outcome was ARDS development and secondary outcomes included hospital mortality, invasive mechanical ventilation, and progression in WHO ordinal scale. RESULTS: The derivation cohort consisted of 3710 patients, of whom 1041 (28.1%) developed ARDS. The c-LIPS discriminated COVID-19 patients who developed ARDS with an area under the curve (AUC) of 0.79 compared with original LIPS (AUC, 0.74; P<.001) with good calibration accuracy (Hosmer-Lemeshow P=.50). Despite different characteristics of the two cohorts, the c-LIPS's performance was comparable in the validation cohort of 5426 patients (15.9% ARDS), with an AUC of 0.74; and its discriminatory performance was significantly higher than the LIPS (AUC, 0.68; P<.001). The c-LIPS's performance in predicting the requirement for invasive mechanical ventilation in derivation and validation cohorts had an AUC of 0.74 and 0.72, respectively. CONCLUSION: In this large patient sample c-LIPS was successfully tailored to predict ARDS in COVID-19 patients.

Rule-Based Cohort Definitions for Acute Respiratory Distress Syndrome: A Computable Phenotyping Strategy Based on the Berlin Definition.

Accurate identification of acute respiratory distress syndrome is essential for understanding its epidemiology, patterns of care, and outcomes. We aimed to design a computable phenotyping strategy to detect acute respiratory distress syndrome in electronic health records of critically ill patients. DESIGN: This is a retrospective cohort study. Using a near real-time copy of the electronic health record, we developed a computable phenotyping strategy to detect acute respiratory distress syndrome based on the Berlin definition. SETTING: Twenty multidisciplinary ICUs in Mayo Clinic Health System. SUBJECTS: The phenotyping strategy was applied to 196,487 consecutive admissions from year 2009 to 2019. INTERVENTIONS: The acute respiratory distress syndrome cohort generated by this novel strategy was compared with the acute respiratory distress syndrome cohort documented by clinicians during the same period. The sensitivity and specificity of the phenotyping strategy were calculated in randomly selected patient cohort (50 patients) using the results from manual medical record review as gold standard. MEASUREMENTS AND MAIN RESULTS: Among the patients who did not have acute respiratory distress syndrome documented, the computable phenotyping strategy identified 3,169 adult patients who met the Berlin definition, 676 patients (21.3%) were classified to have severe acute respiratory distress syndrome (Pao2/Fio2 ratio ≤ 100), 1,535 patients (48.4%) had moderate acute respiratory distress syndrome (100 < Pao2/Fio2 ratio ≤ 200), and 958 patients (30.2%) had mild acute respiratory distress syndrome (200 < Pao2/Fio2 ratio ≤ 300). The phenotyping strategy achieved a sensitivity of 94.4%, specificity of 96.9%, positive predictive value of 94.4%, and negative predictive value of 96.9% in a randomly selected patient cohort. The clinicians documented acute respiratory distress syndrome in 1,257 adult patients during the study period. The clinician documentation rate of acute respiratory distress syndrome was 28.4%. Compared with the clinicians' documentation, the phenotyping strategy identified a cohort that had higher acuity and complexity of illness suggested by higher Sequential Organ Failure Assessment score (9 vs 7; p < 0.0001), higher Acute Physiology and Chronic Health Evaluation score (76 vs 63; p < 0.0001), higher rate of requiring invasive mechanical ventilation (99.1% vs 71.8%; p < 0.0001), higher ICU mortality (20.6% vs 16.8%; p < 0.0001), and longer ICU length of stay (5.1 vs 4.2 d; p < 0.0001). CONCLUSIONS: Our rule-based computable phenotyping strategy can accurately detect acute respiratory distress syndrome in critically ill patients in the setting of high clinical complexity. This strategy can be applied to enhance early recognition of acute respiratory distress syndrome and to facilitate best-care delivery and clinical research in acute respiratory distress syndrome.

FIO2 Trajectory as a Pragmatic Intermediate Marker in Acute Hypoxic Respiratory Failure.

BACKGROUND: Several markers of oxygenation are used as prognostic markers in acute hypoxemic respiratory failure. Real-world use is limited by the need for invasive measurements and unreliable availability in the electronic health record. A pragmatic, reliable, and accurate marker of acute hypoxemic respiratory failure is needed to facilitate epidemiologic studies, clinical trials, and shared decision-making with patients. [Formula: see text] is easily obtained at the bedside and from the electronic health record. The [Formula: see text] trajectory may be a valuable marker of recovery in patients with acute hypoxemic respiratory failure. METHODS: This was a historical cohort study of adult subjects admitted to an ICU with acute hypoxemic respiratory failure secondary to community-acquired pneumonia and/or ARDS. RESULTS: Our study included 2,670 subjects. [Formula: see text] and [Formula: see text] were consistently more available than was [Formula: see text] in the electronic health record: ([Formula: see text] vs [Formula: see text] vs [Formula: see text] : 100 vs 100 vs 72.8% on day 1, and 100 vs 99 vs 21% on day 5). A worsening [Formula: see text] trajectory was associated with reduced ventilator-free days. From days 2 to 5, every increase in [Formula: see text] by 10% from the previous day was associated with fewer ventilator-free days (on day 2: adjusted mean -1.25 [95% CI -1.45 to -1.05] d, P < .001). The [Formula: see text] trajectory also provided prognostic information. On days 3 - 5, an increase in [Formula: see text] from the previous day was associated with increased ventilator-free days (on day 3: adjusted mean 2.09 (95% CI 1.44-2.74) d; P < .001). [Formula: see text] models did not add predictive information compared with models with [Formula: see text] alone (on day 2: adjusted [Formula: see text] vs [Formula: see text] R2 0.122 vs 0.119; and on day 3: 0.153 vs 0.163). CONCLUSIONS: [Formula: see text] and [Formula: see text] are pragmatic and readily available intermediate prognostic markers in acute hypoxic respiratory failure. The [Formula: see text] trajectory in the first 5 d of ICU admission provided important prognostic information (ventilator-free days). Although the [Formula: see text] trajectory was also associated with ventilator-free days, it did not provide more information than the [Formula: see text] trajectory alone.

Biomarker-Concordant Steroid Use in Critically Ill Patients with Pneumonia.

OBJECTIVES: To evaluate the frequency and consequences of prescribing corticosteroids for pneumonia in a biomarker-concordant manner. PATIENTS AND METHODS: This was a single-center retrospective cohort study of adults with pneumonia admitted to the medical intensive care unit (ICU) at Mayo Clinic in Rochester, Minnesota, between January 1, 2009, and June 30, 2014. Steroid use was "biomarker concordant" if given when C-reactive protein (CRP) was ≥150 mg/L or withheld when CRP was <150 mg/L, and vice versa for biomarker discordant. RESULTS: Of 3481 ICU admissions with community-acquired pneumonia, 169 (4.9%) had CRPs measured within 48 hours of admission to the ICU. Steroid use in the ICU was biomarker concordant in 88 (52%) patients and biomarker discordant in 81 (48%) patients. Biomarker-concordant steroid use was associated with faster resolution of lung injury: median fraction of inspired oxygen on day 3 (0.4 [0.3, 0.5] vs 0.3 [0.21, 0.4], P=.005), day 4 (0.35 [0.3, 0.5] vs 0.28 [0.21, 0.38], P=<.001), and day 5 (0.30 [0.24, 0.45] vs 0.28 [0.21, 0.40], P=.03), and increased ICU (3.5; 95% CI, 0.5 to 6.4, P=.02), and hospital-free days (3.6; 95% CI, 0.4 to 6.8, P=.03) on multivariate analysis. CONCLUSIONS: In critically ill patients with community-acquired pneumonia, steroid use is rarely biomarker informed and often discordant with inflammatory biomarker levels. Biomarker-concordant steroid use was associated with a faster recovery of hypoxemia and increased ICU- and hospital-free days. Future well-designed prospective studies are justified to test the potential value of biomarker-concordant steroid therapy.

Airflow obstruction, cognitive function and mortality in a US national cohort: NHANES-III.

OBJECTIVE: To test the hypothesis that cognitive impairment increases mortality independent of airflow obstruction. MATERIALS AND METHODS: In 1988-1994 the Third National Health and Nutrition Examination Survey (NHANES III) measured forced expiratory volume in the first second (FEV1) and the forced vital capacity (FVC) and selected items on cognitive function with mortality follow-up. For this survival analysis 4365 persons aged 60 and over with complete data formed the analytic sample. RESULTS: The FEV1/FVC less than the lower limit of predicted ratio (LLP) defined airflow obstruction and Composite Cognitive Function Score (CCF) ≤4, cognitive impairment. The percentage who died during follow up was 67% among those with neither FEV1/FVC < LLP nor CCF ≤4, 82% with FEV1/FVC < LLP only, 85% with CCF score ≤4 only and 93% with both FEV1/FVC LLP and CCF score ≤4 (P < .001). Weighted Cox proportional hazards regression revealed an increased hazard ratio (HR) in persons with FEV1/FVC