Patiromer utility as an adjunct treatment in patients needing urgent hyperkalaemia management (PLATINUM): design of a multicentre, randomised, double-blind, placebo-controlled, parallel-group study.

INTRODUCTION: Hyperkalaemia is common, life-threatening and often requires emergency department (ED) management; however, no standardised ED treatment protocol exists. Common treatments transiently reducing serum potassium (K+) (including albuterol, glucose and insulin) may cause hypoglycaemia. We outline the design and rationale of the Patiromer Utility as an Adjunct Treatment in Patients Needing Urgent Hyperkalaemia Management (PLATINUM) study, which will be the largest ED randomised controlled hyperkalaemia trial ever performed, enabling assessment of a standardised approach to hyperkalaemia management, as well as establishing a new evaluation parameter (net clinical benefit) for acute hyperkalaemia treatment investigations. METHODS AND ANALYSIS: PLATINUM is a Phase 4, multicentre, randomised, double-blind, placebo-controlled study in participants who present to the ED at approximately 30 US sites. Approximately 300 adult participants with hyperkalaemia (K+ ≥5.8 mEq/L) will be enrolled. Participants will be randomised 1:1 to receive glucose (25 g intravenously <15 min before insulin), insulin (5 units intravenous bolus) and aerosolised albuterol (10 mg over 30 min), followed by a single oral dose of either 25.2 g patiromer or placebo, with a second dose of patiromer (8.4 g) or placebo after 24 hours. The primary endpoint is net clinical benefit, defined as the mean change in the number of additional interventions less the mean change in serum K+, at hour 6. Secondary endpoints are net clinical benefit at hour 4, proportion of participants without additional K+-related medical interventions, number of additional K+-related interventions and proportion of participants with sustained K+ reduction (K+ ≤5.5 mEq/L). Safety endpoints are the incidence of adverse events, and severity of changes in serum K+ and magnesium. ETHICS AND DISSEMINATION: A central Institutional Review Board (IRB) and Ethics Committee provided protocol approval (#20201569), with subsequent approval by local IRBs at each site, and participants will provide written consent. Primary results will be published in peer-reviewed manuscripts promptly following study completion. TRIAL REGISTRATION NUMBER: NCT04443608.

Longitudinal Chest X-ray Scores and their Relations with Clinical Variables and Outcomes in COVID-19 Patients.

Background: This study evaluated the temporal characteristics of lung chest X-ray (CXR) scores in COVID-19 patients during hospitalization and how they relate to other clinical variables and outcomes (alive or dead). Methods: This is a retrospective study of COVID-19 patients. CXR scores of disease severity were analyzed for: (i) survivors (N = 224) versus non-survivors (N = 28) in the general floor group, and (ii) survivors (N = 92) versus non-survivors (N = 56) in the invasive mechanical ventilation (IMV) group. Unpaired t-tests were used to compare survivors and non-survivors and between time points. Comparison across multiple time points used repeated measures ANOVA and corrected for multiple comparisons. Results: For general-floor patients, non-survivor CXR scores were significantly worse at admission compared to those of survivors (p < 0.05), and non-survivor CXR scores deteriorated at outcome (p < 0.05) whereas survivor CXR scores did not (p > 0.05). For IMV patients, survivor and non-survivor CXR scores were similar at intubation (p > 0.05), and both improved at outcome (p < 0.05), with survivor scores showing greater improvement (p < 0.05). Hospitalization and IMV duration were not different between groups (p > 0.05). CXR scores were significantly correlated with lactate dehydrogenase, respiratory rate, D-dimer, C-reactive protein, procalcitonin, ferritin, SpO2, and lymphocyte count (p < 0.05). Conclusions: Longitudinal CXR scores have the potential to provide prognosis, guide treatment, and monitor disease progression.

Deep learning of longitudinal chest X-ray and clinical variables predicts duration on ventilator and mortality in COVID-19 patients.

OBJECTIVES: To use deep learning of serial portable chest X-ray (pCXR) and clinical variables to predict mortality and duration on invasive mechanical ventilation (IMV) for Coronavirus disease 2019 (COVID-19) patients. METHODS: This is a retrospective study. Serial pCXR and serial clinical variables were analyzed for data from day 1, day 5, day 1-3, day 3-5, or day 1-5 on IMV (110 IMV survivors and 76 IMV non-survivors). The outcome variables were duration on IMV and mortality. With fivefold cross-validation, the performance of the proposed deep learning system was evaluated by receiver operating characteristic (ROC) analysis and correlation analysis. RESULTS: Predictive models using 5-consecutive-day data outperformed those using 3-consecutive-day and 1-day data. Prediction using data closer to the outcome was generally better (i.e., day 5 data performed better than day 1 data, and day 3-5 data performed better than day 1-3 data). Prediction performance was generally better for the combined pCXR and non-imaging clinical data than either alone. The combined pCXR and non-imaging data of 5 consecutive days predicted mortality with an accuracy of 85 ± 3.5% (95% confidence interval (CI)) and an area under the curve (AUC) of 0.87 ± 0.05 (95% CI) and predicted the duration needed to be on IMV to within 2.56 ± 0.21 (95% CI) days on the validation dataset. CONCLUSIONS: Deep learning of longitudinal pCXR and clinical data have the potential to accurately predict mortality and duration on IMV in COVID-19 patients. Longitudinal pCXR could have prognostic value if these findings can be validated in a large, multi-institutional cohort.

Bacterial infections and death among patients with Covid-19 versus non Covid-19 patients with pneumonia.

BACKGROUND: Many patients with Coronavirus disease-2019 (Covid-19) present with radiological evidence of pneumonia. Because it is difficult to determine co-existence of bacterial pneumonia, many of these patients are initially treated with antibiotics. We compared the rates of bacterial infections and mortality in Covid-19 patients with pulmonary infiltrates versus patients diagnosed with 'pneumonia' the year previously. METHODS: We conducted a medical record review of patients admitted with Covid-19 and a pulmonary infiltrate and compared them with patients diagnosed with pneumonia admitted in the prior year before the pandemic. Data abstracted included baseline demographics, comorbidities, signs and symptoms, laboratory and microbiological results, and imaging findings. Outcomes were bacterial infections and mortality. Patients presenting with and without Covid-19 were compared using univariable and multivariable analyses. RESULTS: There were 1398 and 1001 patients admitted through the emergency department (ED) with and without Covid-19 respectively. Compared with non-Covid-19 patients, those with Covid-19 were younger (61±18 vs. 65±25 years, P < 0.001) and had a lower Charlson Comorbidity Index (0.7 vs. 1.2, P < 0.001). Bacterial infections were present in fewer Covid-19 than non-Covid-19 patients (8% vs. 13%, P < 0.001), and most infections in Covid-19 were nosocomial as opposed to community acquired in non-Covid-19 patients. CXR was more often read as abnormal and with bilateral infiltrates in patients with Covid-19 (82% vs. 70%, P < 0.001 and 81% vs. 48%, P < 0.001, respectively). Mortality was higher in patients with Covid-19 vs. those without (15% vs. 9%, P < 0.001). Multivariable predictors (OR [95%CI]) of mortality were age (1.04 [1.03-1.05]/year), tachypnea (1.55 [1.12-2.14]), hypoxemia (2.98 [2.04-4.34]), and bacterial infection (2.80 [1.95-4.02]). Compared with non-Covid-19 patients with pneumonia, patients with Covid-19 were more likely to die (2.68 [1.97-3.63]). CONCLUSIONS: The rate of bacterial infections is lower in Covid-19 patients with pulmonary infiltrates compared with patients diagnosed with pneumonia prior to the pandemic and most are nosocomial. Mortality was higher in Covid-19 than non-Covid-19 patients even after adjusting for age, tachypnea, hypoxemia, and bacterial infection.

Survival of COVID-19 Patients With Respiratory Failure is Related to Temporal Changes in Gas Exchange and Mechanical Ventilation.

Background: Respiratory failure due to coronavirus disease of 2019 (COVID-19) often presents with worsening gas exchange over a period of days. Once patients require mechanical ventilation (MV), the temporal change in gas exchange and its relation to clinical outcome is poorly described. We investigated whether gas exchange over the first 5 days of MV is associated with mortality and ventilator-free days at 28 days in COVID-19. Methods: In a cohort of 294 COVID-19 patients, we used data during the first 5 days of MV to calculate 4 daily respiratory scores: PaO2/FiO2 (P/F), oxygenation index (OI), ventilatory ratio (VR), and Murray lung injury score. The association between these scores at early (days 1-3) and late (days 4-5) time points with mortality was evaluated using logistic regression, adjusted for demographics. Correlation with ventilator-free days was assessed (Spearman rank-order coefficients). Results: Overall mortality was 47.6%. Nonsurvivors were older (P < .0001), more male (P = .029), with more preexisting cardiopulmonary disease compared to survivors. Mean PaO2 and PaCO2 were similar during this timeframe. However, by days 4 to 5 values for all airway pressures and FiO2 had diverged, trending lower in survivors and higher in nonsurvivors. The most substantial between-group difference was the temporal change in OI, improving 15% in survivors and worsening 11% in nonsurvivors (P < .05). The adjusted mortality OR was significant for age (1.819, P = .001), OI at days 4 to 5 (2.26, P = .002), and OI percent change (1.90, P = .02). The number of ventilator-free days correlated significantly with late VR (-0.166, P < .05), early and late OI (-0.216, P < .01; -0.278, P < .01, respectively) and early and late P/F (0.158, P < .05; 0.283, P < .01, respectively). Conclusion: Nonsurvivors of COVID-19 needed increasing intensity of MV to sustain gas exchange over the first 5 days, unlike survivors. Temporal change OI, reflecting both PaO2 and the intensity of MV, is a potential marker of outcome in respiratory failure due to COVID-19.

Time-to-Death Longitudinal Characterization of Clinical Variables and Longitudinal Prediction of Mortality in COVID-19 Patients: A Two-Center Study.

Objectives: To characterize the temporal characteristics of clinical variables with time lock to mortality and build a predictive model of mortality associated with COVID-19 using clinical variables. Design: Retrospective cohort study of the temporal characteristics of clinical variables with time lock to mortality. Setting: Stony Brook University Hospital (New York) and Tongji Hospital. Patients: Patients with confirmed positive for severe acute respiratory syndrome coronavirus-2 using polymerase chain reaction testing. Patients from the Stony Brook University Hospital data were used for training (80%, N = 1,002) and testing (20%, N = 250), and 375 patients from the Tongji Hospital (Wuhan, China) data were used for testing. Intervention: None. Measurements and Main Results: Longitudinal clinical variables were analyzed as a function of days from outcome with time-lock-to-day of death (non-survivors) or discharge (survivors). A predictive model using the significant earliest predictors was constructed. Performance was evaluated using receiver operating characteristics area under the curve (AUC). The predictive model found lactate dehydrogenase, lymphocytes, procalcitonin, D-dimer, C-reactive protein, respiratory rate, and white-blood cells to be early predictors of mortality. The AUC for the zero to 9 days prior to outcome were: 0.99, 0.96, 0.94, 0.90, 0.82, 0.75, 0.73, 0.77, 0.79, and 0.73, respectively (Stony Brook Hospital), and 1.0, 0.86, 0.88, 0.96, 0.91, 0.62, 0.67, 0.50, 0.63, and 0.57, respectively (Tongji Hospital). In comparison, prediction performance using hospital admission data was poor (AUC = 0.59). Temporal fluctuations of most clinical variables, indicative of physiological and biochemical instability, were markedly higher in non-survivors compared to survivors (p < 0.001). Conclusion: This study identified several clinical markers that demonstrated a temporal progression associated with mortality. These variables accurately predicted death within a few days prior to outcome, which provides objective indication that closer monitoring and interventions may be needed to prevent deterioration.

D-Dimer-Driven Anticoagulation Reduces Mortality in Intubated COVID-19 Patients: A Cohort Study With a Propensity-Matched Analysis.

Objective: Examine the possible beneficial effects of early, D-dimer driven anticoagulation in preventing thrombotic complications and improving the overall outcomes of COVID-19 intubated patients. Methods: To address COVID-19 hypercoagulability, we developed a clinical protocol to escalate anticoagulation based on serum D-dimer levels. We retrospectively reviewed all our first 240 intubated patients with COVID-19. Of the 240, 195 were stratified into patients treated based on this protocol (ON-protocol, n = 91) and the control group, patients who received standard thromboprophylaxis (OFF-protocol, n = 104). All patients were admitted to the Stony Brook University Hospital intensive care units (ICUs) between February 7th, 2020 and May 17, 2020 and were otherwise treated in the same manner for all aspects of COVID-19 disease. Results: We found that the overall mortality was significantly lower ON-protocol compared to OFF-protocol (27.47 vs. 58.66%, P < 0.001). Average maximum D-dimer levels were significantly lower in the ON-protocol group (7,553 vs. 12,343 ng/mL), as was serum creatinine (2.2 vs. 2.8 mg/dL). Patients with poorly controlled D-dimer levels had higher rates of kidney dysfunction and mortality. Transfusion requirements and serious bleeding events were similar between groups. To address any possible between-group differences, we performed a propensity-matched analysis of 124 of the subjects (62 matched pairs, ON-protocol and OFF-protocol), which showed similar findings (31 vs. 57% overall mortality in the ON-protocol and OFF-protocol group, respectively). Conclusions: D-dimer-driven anticoagulation appears to be safe in patients with COVID-19 infection and is associated with improved survival. What This Paper Adds: It has been shown that hypercoagulability in patients with severe COVID-19 infection leads to thromboembolic complications and organ dysfunction. Anticoagulation has been variably administered to these patients, but it is unknown whether routine or escalated thromboprophylaxis provides a survival benefit. Our data shows that escalated D-dimer driven anticoagulation is associated with improved organ function and overall survival in intubated COVID-19 ICU patients at our institution. Importantly, we found that timely escalation of this anticoagulation is critical in preventing organ dysfunction and mortality in patients with severe COVID-19 infection.

Outcomes in Hispanics With COVID-19 Are Similar to Those of Caucasian Patients in Suburban New York.

BACKGROUND: Despite reported higher rates and worse outcomes due to COVID-19 in certain racial and ethnic groups, much remains unknown. We explored the association between Hispanic ethnicity and outcomes in COVID-19 patients in Long Island, New York. METHODS: We conducted a retrospective cohort study of 2,039 Hispanic and non-Hispanic Caucasian patients testing positive for SARS-CoV-2 between March 7 and May 23, 2020, at a large suburban academic tertiary care hospital near New York City. We explored the association of ethnicity with need for intensive care unit (ICU), invasive mechanical ventilation (IMV), and mortality. RESULTS: Of all patients, 1,079 (53%) were non-Hispanic Caucasians and 960 (47%) were Hispanic. Hispanic patients presented in higher numbers than expected for our catchment area. Compared with Caucasians, Hispanics were younger (45 years vs. 59 years), had fewer comorbidities (66% with no comorbidities vs. 40%), were less likely to have commercial insurance (35% vs. 59%), or were less likely to come from a nursing home (2% vs. 10%). In univariate comparisons, Hispanics were less likely to be admitted (37% vs. 59%) or to die (3% vs. 10%). Age, shortness of breath, congestive heart failure (CHF), coronary artery disease (CAD), hypoxemia, and presentation from nursing homes were associated with admission. Male sex and hypoxemia were associated with ICU admission. Male sex, chronic obstructive pulmonary disease, and hypoxemia were associated with IMV. Male sex, CHF, CAD, and hypoxemia were associated with mortality. After other factors were adjusted for, Hispanics were less likely to be admitted (odds ratio = 0.62, 95% confidence interval = 0.52 to 0.92) but Hispanic ethnicity was not associated with ICU admission, IMV, or mortality. CONCLUSIONS: Hispanics presented at higher rates than average for our population but outcomes among Hispanic patients with COVID-19 were similar to those of Caucasian patients.

Comparison of COVID-19 infections among healthcare workers and non-healthcare workers.

OBJECTIVES: Healthcare workers face distinct occupational challenges that affect their personal health, especially during a pandemic. In this study we compare the characteristics and outcomes of Covid-19 patients who are and who are not healthcare workers (HCW). METHODS: We retrospectively analyzed a cohort of 2,842 adult patients with known HCW status and a positive SARS-CoV-2 RT-PCR test presenting to a large academic medical center emergency department (ED) in New York State from March 21 2020 through June 2020. Early in the pandemic we instituted a policy to collect data on patient occupation and exposures to suspected Covid-19. The primary outcome was hospital admission. Secondary outcomes were ICU admission, need for invasive mechanical ventilation (IMV), and mortality. We compared baseline characteristics and outcomes of Covid-19 adult patients based on whether they were or were not HCW using univariable and multivariable analyses. RESULTS: Of 2,842 adult patients (mean age 53+/-19 years, 53% male) 193 (6.8%) were HCWs and 2,649 (93.2%) were not HCWs. Compared with non-HCW, HCWs were younger (43 vs 53 years, P<0.001), more likely female (118/193 [61%] vs 1211/2649 [46%], P<0.001), and more likely to have a known Covid-19 exposure (161/193 [83%] vs 946/2649 [36%], P<0.001), but had fewer comorbidities. On presentation to the ED, HCW also had lower frequencies of tachypnea (12/193 [6%] vs 426/2649 [16%], P<0.01), hypoxemia (15/193 [8%] vs 564/2649 [21%], P<0.01), bilateral opacities on imaging (38/193 [20%] vs 1189/2649 [45%], P<0.001), and lymphocytopenia (6/193 [3%] vs 532/2649 [20%], P<0.01) compared to non-HCWs. Direct discharges home from the ED were more frequent in HCW 154/193 (80%) vs 1275/2649 (48%) p<0.001). Hospital admissions (38/193 [20%] vs 1264/2694 [47%], P<0.001), ICU admissions (7/193 [3%] vs 321/2694 [12%], P<0.001), need for IMV (6/193 [3%] vs 321/2694 [12%], P<0.001) and mortality (2/193 [1%] vs 219/2694 [8%], P<0.01) were lower than among non-HCW. After controlling for age, sex, comorbidities, presenting vital signs and radiographic imaging, HCW were less likely to be admitted (OR 0.6, 95%CI 0.3-0.9) than non HCW. CONCLUSIONS: Compared with non HCW, HCW with Covid-19 were younger, had less severe illness, and were less likely to be admitted.

Continued In-Hospital Angiotensin-Converting Enzyme Inhibitor and Angiotensin II Receptor Blocker Use in Hypertensive COVID-19 Patients Is Associated With Positive Clinical Outcome.

BACKGROUND: This study investigated continued and discontinued use of angiotensin-converting enzyme inhibitors (ACEi) or angiotensin II receptor blockers (ARB) during hospitalization of 614 hypertensive laboratory-confirmed COVID-19 patients. METHODS: Demographics, comorbidities, vital signs, laboratory data, and ACEi/ARB usage were analyzed. To account for confounders, patients were substratified by whether they developed hypotension and acute kidney injury (AKI) during the index hospitalization. RESULTS: Mortality (22% vs 17%, P > .05) and intensive care unit (ICU) admission (26% vs 12%, P > .05) rates were not significantly different between non-ACEi/ARB and ACEi/ARB groups. However, patients who continued ACEi/ARBs in the hospital had a markedly lower ICU admission rate (12% vs 26%; P = .001; odds ratio [OR] = 0.347; 95% confidence interval [CI], .187-.643) and mortality rate (6% vs 28%; P = .001; OR = 0.215; 95% CI, .101-.455) compared to patients who discontinued ACEi/ARB. The odds ratio for mortality remained significantly lower after accounting for development of hypotension or AKI. CONCLUSIONS: These findings suggest that continued ACEi/ARB use in hypertensive COVID-19 patients yields better clinical outcomes.

Prediction model and risk scores of ICU admission and mortality in COVID-19.

This study aimed to develop risk scores based on clinical characteristics at presentation to predict intensive care unit (ICU) admission and mortality in COVID-19 patients. 641 hospitalized patients with laboratory-confirmed COVID-19 were selected from 4997 persons under investigation. We performed a retrospective review of medical records of demographics, comorbidities and laboratory tests at the initial presentation. Primary outcomes were ICU admission and death. Logistic regression was used to identify independent clinical variables predicting the two outcomes. The model was validated by splitting the data into 70% for training and 30% for testing. Performance accuracy was evaluated using area under the curve (AUC) of the receiver operating characteristic analysis (ROC). Five significant variables predicting ICU admission were lactate dehydrogenase, procalcitonin, pulse oxygen saturation, smoking history, and lymphocyte count. Seven significant variables predicting mortality were heart failure, procalcitonin, lactate dehydrogenase, chronic obstructive pulmonary disease, pulse oxygen saturation, heart rate, and age. The mortality group uniquely contained cardiopulmonary variables. The risk score model yielded good accuracy with an AUC of 0.74 ([95% CI, 0.63-0.85], p = 0.001) for predicting ICU admission and 0.83 ([95% CI, 0.73-0.92], p<0.001) for predicting mortality for the testing dataset. This study identified key independent clinical variables that predicted ICU admission and mortality associated with COVID-19. This risk score system may prove useful for frontline physicians in clinical decision-making under time-sensitive and resource-constrained environment.

Cohort of Four Thousand Four Hundred Four Persons Under Investigation for COVID-19 in a New York Hospital and Predictors of ICU Care and Ventilation.

Study objective: Most coronavirus disease 2019 (COVID-19) reports have focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive patients. However, at initial presentation, most patients' viral status is unknown. Determination of factors that predict initial and subsequent need for ICU and invasive mechanical ventilation is critical for resource planning and allocation. We describe our experience with 4,404 persons under investigation and explore predictors of ICU care and invasive mechanical ventilation at a New York COVID-19 epicenter. Methods: We conducted a retrospective cohort study of all persons under investigation and presenting to a large academic medical center emergency department (ED) in New York State with symptoms suggestive of COVID-19. The association between patient predictor variables and SARS-CoV-2 status, ICU admission, invasive mechanical ventilation, and mortality was explored with univariate and multivariate analyses. Results: Between March 12 and April 14, 2020, we treated 4,404 persons under investigation for COVID-19 infection, of whom 68% were discharged home, 29% were admitted to a regular floor, and 3% to an ICU. One thousand six hundred fifty-one of 3,369 patients tested have had SARS-CoV-2-positive results to date. Of patients with regular floor admissions, 13% were subsequently upgraded to the ICU after a median of 62 hours (interquartile range 28 to 106 hours). Fifty patients required invasive mechanical ventilation in the ED, 4 required out-of-hospital invasive mechanical ventilation, and another 167 subsequently required invasive mechanical ventilation in a median of 60 hours (interquartile range 26 to 99) hours after admission. Testing positive for SARS-CoV-2 and lower oxygen saturations were associated with need for ICU and invasive mechanical ventilation, and with death. High respiratory rates were associated with the need for ICU care. Conclusion: Persons under investigation for COVID-19 infection contribute significantly to the health care burden beyond those ruling in for SARS-CoV-2. For every 100 admitted persons under investigation, 9 will require ICU stay, invasive mechanical ventilation, or both on arrival and another 12 within 2 to 3 days of hospital admission, especially persons under investigation with lower oxygen saturations and positive SARS-CoV-2 swab results. This information should help hospitals manage the pandemic efficiently.