External Validation of the Augmented Renal Clearance Predictor in Critically Ill COVID-19 Patients.

The ARC predictor is a prediction model for augmented renal clearance (ARC) on the next intensive care unit (ICU) day that showed good performance in a general ICU setting. In this study, we performed a retrospective external validation of the ARC predictor in critically ill coronavirus disease 19 (COVID-19) patients admitted to the ICU of the University Hospitals Leuven from February 2020 to January 2021. All patient-days that had serum creatinine levels available and measured creatinine clearance on the next ICU day were enrolled. The performance of the ARC predictor was evaluated using discrimination, calibration, and decision curves. A total of 120 patients (1064 patient-days) were included, and ARC was found in 57 (47.5%) patients, corresponding to 246 (23.1%) patient-days. The ARC predictor demonstrated good discrimination and calibration (AUROC of 0.86, calibration slope of 1.18, and calibration-in-the-large of 0.14) and a wide clinical-usefulness range. At the default classification threshold of 20% in the original study, the sensitivity and specificity were 72% and 81%, respectively. The ARC predictor is able to accurately predict ARC in critically ill COVID-19 patients. These results support the potential of the ARC predictor to optimize renally cleared drug dosages in this specific ICU population. Investigation of dosing regimen improvement was not included in this study and remains a challenge for future studies.

Development and Validation of a Treatment Benefit Index to Identify Hospitalized Patients With COVID-19 Who May Benefit From Convalescent Plasma.

Importance: Identifying which patients with COVID-19 are likely to benefit from COVID-19 convalescent plasma (CCP) treatment may have a large public health impact. Objective: To develop an index for predicting the expected relative treatment benefit from CCP compared with treatment without CCP for patients hospitalized for COVID-19 using patients' baseline characteristics. Design, Setting, and Participants: This prognostic study used data from the COMPILE study, ie, a meta-analysis of pooled individual patient data from 8 randomized clinical trials (RCTs) evaluating CCP vs control in adults hospitalized for COVID-19 who were not receiving mechanical ventilation at randomization. A combination of baseline characteristics, termed the treatment benefit index (TBI), was developed based on 2287 patients in COMPILE using a proportional odds model, with baseline characteristics selected via cross-validation. The TBI was externally validated on 4 external data sets: the Expanded Access Program (1896 participants), a study conducted under Emergency Use Authorization (210 participants), and 2 RCTs (with 80 and 309 participants). Exposure: Receipt of CCP. Main Outcomes and Measures: World Health Organization (WHO) 11-point ordinal COVID-19 clinical status scale and 2 derivatives of it (ie, WHO score of 7-10, indicating mechanical ventilation to death, and WHO score of 10, indicating death) at day 14 and day 28 after randomization. Day 14 WHO 11-point ordinal scale was used as the primary outcome to develop the TBI. Results: A total of 2287 patients were included in the derivation cohort, with a mean (SD) age of 60.3 (15.2) years and 815 (35.6%) women. The TBI provided a continuous gradation of benefit, and, for clinical utility, it was operationalized into groups of expected large clinical benefit (B1; 629 participants in the derivation cohort [27.5%]), moderate benefit (B2; 953 [41.7%]), and potential harm or no benefit (B3; 705 [30.8%]). Patients with preexisting conditions (diabetes, cardiovascular and pulmonary diseases), with blood type A or AB, and at an early COVID-19 stage (low baseline WHO scores) were expected to benefit most, while those without preexisting conditions and at more advanced stages of COVID-19 could potentially be harmed. In the derivation cohort, odds ratios for worse outcome, where smaller odds ratios indicate larger benefit from CCP, were 0.69 (95% credible interval [CrI], 0.48-1.06) for B1, 0.82 (95% CrI, 0.61-1.11) for B2, and 1.58 (95% CrI, 1.14-2.17) for B3. Testing on 4 external datasets supported the validation of the derived TBIs. Conclusions and Relevance: The findings of this study suggest that the CCP TBI is a simple tool that can quantify the relative benefit from CCP treatment for an individual patient hospitalized with COVID-19 that can be used to guide treatment recommendations. The TBI precision medicine approach could be especially helpful in a pandemic.

Association of Convalescent Plasma Treatment With Clinical Status in Patients Hospitalized With COVID-19: A Meta-analysis.

Importance: COVID-19 convalescent plasma (CCP) is a potentially beneficial treatment for COVID-19 that requires rigorous testing. Objective: To compile individual patient data from randomized clinical trials of CCP and to monitor the data until completion or until accumulated evidence enables reliable conclusions regarding the clinical outcomes associated with CCP. Data Sources: From May to August 2020, a systematic search was performed for trials of CCP in the literature, clinical trial registry sites, and medRxiv. Domain experts at local, national, and international organizations were consulted regularly. Study Selection: Eligible trials enrolled hospitalized patients with confirmed COVID-19, not receiving mechanical ventilation, and randomized them to CCP or control. The administered CCP was required to have measurable antibodies assessed locally. Data Extraction and Synthesis: A minimal data set was submitted regularly via a secure portal, analyzed using a prespecified bayesian statistical plan, and reviewed frequently by a collective data and safety monitoring board. Main Outcomes and Measures: Prespecified coprimary end points-the World Health Organization (WHO) 11-point ordinal scale analyzed using a proportional odds model and a binary indicator of WHO score of 7 or higher capturing the most severe outcomes including mechanical ventilation through death and analyzed using a logistic model-were assessed clinically at 14 days after randomization. Results: Eight international trials collectively enrolled 2369 participants (1138 randomized to control and 1231 randomized to CCP). A total of 2341 participants (median [IQR] age, 60 [50-72] years; 845 women [35.7%]) had primary outcome data as of April 2021. The median (IQR) of the ordinal WHO scale was 3 (3-6); the cumulative OR was 0.94 (95% credible interval [CrI], 0.74-1.19; posterior probability of OR <1 of 71%). A total of 352 patients (15%) had WHO score greater than or equal to 7; the OR was 0.94 (95% CrI, 0.69-1.30; posterior probability of OR <1 of 65%). Adjusted for baseline covariates, the ORs for mortality were 0.88 at day 14 (95% CrI, 0.61-1.26; posterior probability of OR <1 of 77%) and 0.85 at day 28 (95% CrI, 0.62-1.18; posterior probability of OR <1 of 84%). Heterogeneity of treatment effect sizes was observed across an array of baseline characteristics. Conclusions and Relevance: This meta-analysis found no association of CCP with better clinical outcomes for the typical patient. These findings suggest that real-time individual patient data pooling and meta-analysis during a pandemic are feasible, offering a model for future research and providing a rich data resource.

Early high antibody titre convalescent plasma for hospitalised COVID-19 patients: DAWn-plasma.

BACKGROUND: Several randomised clinical trials have studied convalescent plasma for coronavirus disease 2019 (COVID-19) using different protocols, with different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralising antibody titres, at different time-points and severities of illness. METHODS: In the prospective multicentre DAWn-plasma trial, adult patients hospitalised with COVID-19 were randomised to 4 units of open-label convalescent plasma combined with standard of care (intervention group) or standard of care alone (control group). Plasma from donors with neutralising antibody titres (50% neutralisation titre (NT50)) ≥1/320 was the product of choice for the study. RESULTS: Between 2 May 2020 and 26 January 2021, 320 patients were randomised to convalescent plasma and 163 patients to the control group according to a 2:1 allocation scheme. A median (interquartile range) volume of 884 (806-906) mL) convalescent plasma was administered and 80.68% of the units came from donors with neutralising antibody titres (NT50) ≥1/320. Median time from onset of symptoms to randomisation was 7 days. The proportion of patients alive and free of mechanical ventilation on day 15 was not different between both groups (convalescent plasma 83.74% (n=267) versus control 84.05% (n=137)) (OR 0.99, 95% CI 0.59-1.66; p=0.9772). The intervention did not change the natural course of antibody titres. The number of serious or severe adverse events was similar in both study arms and transfusion-related side-effects were reported in 19 out of 320 patients in the intervention group (5.94%). CONCLUSIONS: Transfusion of 4 units of convalescent plasma with high neutralising antibody titres early in hospitalised COVID-19 patients did not result in a significant improvement of clinical status or reduced mortality.

A multicenter randomized trial to assess the efficacy of CONvalescent plasma therapy in patients with Invasive COVID-19 and acute respiratory failure treated with mechanical ventilation: the CONFIDENT trial protocol.

BACKGROUND: The COVID-19 pandemic reached Europe in early 2020. Convalescent plasma is used without a consistent evidence of efficacy. Our hypothesis is that passive immunization with plasma collected from patients having contracted COVID-19 and developed specific neutralizing antibodies may alleviate symptoms and reduce mortality in patients treated with mechanical ventilation for severe respiratory failure during the evolution of SARS-CoV-2 pneumonia. METHODS: We plan to include 500 adult patients, hospitalized in 16 Belgian intensive care units between September 2020 and 2022, diagnosed with SARS-CoV-2 pneumonia, under mechanical ventilation for less than 5 days and a clinical frailty scale less than 6. The study treatment will be compared to standard of care and allocated by randomization in a 1 to 1 ratio without blinding. The main endpoint will be mortality at day 28. We will perform an intention to treat analysis. The number of patients to include is based on an expected mortality rate at day 28 of 40 percent and an expected relative reduction with study intervention of 30 percent with α risk of 5 percent and ß risk of 20 percent. DISCUSSION: This study will assess the efficacy of plasma in the population of mechanically ventilated patients. A stratification on the delay from mechanical ventilation and inclusion will allow to approach the optimal time use. Selecting convalescent plasmas with a high titer of neutralizing antibodies against SARS-CoV-2 will allow a homogeneous study treatment. The inclusion in the study is based on the consent of the patient or his/her legal representative, and the approval of the Investigational Review Board of the University hospital of Liège, Belgium. A data safety monitoring board (DSMB) has been implemented. Interim analyses have been planned at 100, 2002, 300 and 400 inclusions in order to decide whether the trail should be discontinued prematurely for ethical issues. We plan to publish our results in a peer-reviewed journal and to present them at national and international conferences. FUNDING AND REGISTRATION: The trial is funded by the Belgian Health Care Knowledge Center KCE # COV201004 TRIAL REGISTRATION: Clinicaltrials.gov registration number NCT04558476. Registered 14 September 2020-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04558476.

Itraconazole for COVID-19: preclinical studies and a proof-of-concept randomized clinical trial.

BACKGROUND: The antifungal drug itraconazole exerts in vitro activity against SARS-CoV-2 in Vero and human Caco-2 cells. Preclinical and clinical studies are required to investigate if itraconazole is effective for the treatment and/or prevention of COVID-19. METHODS: Due to the initial absence of preclinical models, the effect of itraconazole was explored in a clinical, proof-of-concept, open-label, single-center study, in which hospitalized COVID-19 patients were randomly assigned to standard of care with or without itraconazole. Primary outcome was the cumulative score of the clinical status until day 15 based on the 7-point ordinal scale of the World Health Organization. In parallel, itraconazole was evaluated in a newly established hamster model of acute SARS-CoV-2 infection and transmission, as soon as the model was validated. FINDINGS: In the hamster acute infection model, itraconazole did not reduce viral load in lungs, stools or ileum, despite adequate plasma and lung drug concentrations. In the transmission model, itraconazole failed to prevent viral transmission. The clinical trial was prematurely discontinued after evaluation of the preclinical studies and because an interim analysis showed no signal for a more favorable outcome with itraconazole: mean cumulative score of the clinical status 49 vs 47, ratio of geometric means 1.01 (95% CI 0.85 to 1.19) for itraconazole vs standard of care. INTERPRETATION: Despite in vitro activity, itraconazole was not effective in a preclinical COVID-19 hamster model. This prompted the premature termination of the proof-of-concept clinical study. FUNDING: KU Leuven, Research Foundation - Flanders (FWO), Horizon 2020, Bill and Melinda Gates Foundation.

How the COVID-19 pandemic will change the future of critical care.

Coronavirus disease 19 (COVID-19) has posed unprecedented healthcare system challenges, some of which will lead to transformative change. It is obvious to healthcare workers and policymakers alike that an effective critical care surge response must be nested within the overall care delivery model. The COVID-19 pandemic has highlighted key elements of emergency preparedness. These include having national or regional strategic reserves of personal protective equipment, intensive care unit (ICU) devices, consumables and pharmaceuticals, as well as effective supply chains and efficient utilization protocols. ICUs must also be prepared to accommodate surges of patients and ICU staffing models should allow for fluctuations in demand. Pre-existing ICU triage and end-of-life care principles should be established, implemented and updated. Daily workflow processes should be restructured to include remote connection with multidisciplinary healthcare workers and frequent communication with relatives. The pandemic has also demonstrated the benefits of digital transformation and the value of remote monitoring technologies, such as wireless monitoring. Finally, the pandemic has highlighted the value of pre-existing epidemiological registries and agile randomized controlled platform trials in generating fast, reliable data. The COVID-19 pandemic is a reminder that besides our duty to care, we are committed to improve. By meeting these challenges today, we will be able to provide better care to future patients.

Time between Symptom Onset, Hospitalisation and Recovery or Death: Statistical Analysis of Belgian COVID-19 Patients.

There are different patterns in the COVID-19 outbreak in the general population and amongst nursing home patients. We investigate the time from symptom onset to diagnosis and hospitalization or the length of stay (LoS) in the hospital, and whether there are differences in the population. Sciensano collected information on 14,618 hospitalized patients with COVID-19 admissions from 114 Belgian hospitals between 14 March and 12 June 2020. The distributions of different event times for different patient groups are estimated accounting for interval censoring and right truncation of the time intervals. The time between symptom onset and hospitalization or diagnosis are similar, with median length between symptom onset and hospitalization ranging between 3 and 10.4 days, depending on the age of the patient (longest delay in age group 20-60 years) and whether or not the patient lives in a nursing home (additional 2 days for patients from nursing home). The median LoS in hospital varies between 3 and 10.4 days, with the LoS increasing with age. The hospital LoS for patients that recover is shorter for patients living in a nursing home, but the time to death is longer for these patients. Over the course of the first wave, the LoS has decreased.

The role of organizational characteristics on the outcome of COVID-19 patients admitted to the ICU in Belgium.

BACKGROUND: Several studies have investigated the predictors of in-hospital mortality for COVID-19 patients who need to be admitted to the Intensive Care Unit (ICU). However, no data on the role of organizational issues on patients' outcome are available in this setting. The aim of this study was therefore to assess the role of surge capacity organisation on the outcome of critically ill COVID-19 patients admitted to ICUs in Belgium. METHODS: We conducted a retrospective analysis of in-hospital mortality in Belgian ICU COVID-19 patients via the national surveillance database. Non-survivors at hospital discharge were compared to survivors using multivariable mixed effects logistic regression analysis. Specific analyses including only patients with invasive ventilation were performed. To assess surge capacity, data were merged with administrative information on the type of hospital, the baseline number of recognized ICU beds, the number of supplementary beds specifically created for COVID-19 ICU care and the "ICU overflow" (i.e. a time-varying ratio between the number of occupied ICU beds by confirmed and suspected COVID-19 patients divided by the number of recognized ICU beds reserved for COVID-19 patients; ICU overflow was present when this ratio is ≥ 1.0). FINDINGS: Over a total of 13,612 hospitalised COVID-19 patients with admission and discharge forms registered in the surveillance period (March, 1 to August, 9 2020), 1903 (14.0%) required ICU admission, of whom 1747 had available outcome data. Non-survivors (n = 632, 36.1%) were older and had more frequently various comorbid diseases than survivors. In the multivariable analysis, ICU overflow, together with older age, presence of comorbidities, shorter delay between symptom onset and hospital admission, absence of hydroxychloroquine therapy and use of invasive mechanical ventilation and of ECMO, was independently associated with an increased in-hospital mortality. Similar results were found in in in the subgroup of invasively ventilated patients. In addition, the proportion of supplementary beds specifically created for COVID-19 ICU care to the previously existing total number of ICU beds was associated with increased in-hospital mortality among invasively ventilated patients. The model also indicated a significant between-hospital difference in in-hospital mortality, not explained by the available patients and hospital characteristics. INTERPRETATION: Surge capacity organisation as reflected by ICU overflow or the creation of COVID-19 specific supplementary ICU beds were found to negatively impact ICU patient outcomes. FUNDING: No funding source was available for this study.

A randomized, multicentre, open-label phase II proof-of-concept trial investigating the clinical efficacy and safety of the addition of convalescent plasma to the standard of care in patients hospitalized with COVID-19: the Donated Antibodies Working against nCoV (DAWn-Plasma) trial.

BACKGROUND: The COVID-19 pandemic has imposed an enormous burden on health care systems around the world. In the past, the administration of convalescent plasma of patients having recovered from SARS and severe influenza to patients actively having the disease showed promising effects on mortality and appeared safe. Whether or not this also holds true for the novel SARS-CoV-2 virus is currently unknown. METHODS: DAWn-Plasma is a multicentre nation-wide, randomized, open-label, phase II proof-of-concept clinical trial, evaluating the clinical efficacy and safety of the addition of convalescent plasma to the standard of care in patients hospitalized with COVID-19 in Belgium. Patients hospitalized with a confirmed diagnosis of COVID-19 are eligible when they are symptomatic (i.e. clinical or radiological signs) and have been diagnosed with COVID-19 in the 72 h before study inclusion through a PCR (nasal/nasopharyngeal swab or bronchoalveolar lavage) or a chest-CT scan showing features compatible with COVID-19 in the absence of an alternative diagnosis. Patients are randomized in a 2:1 ratio to either standard of care and convalescent plasma (active treatment group) or standard of care only. The active treatment group receives 2 units of 200 to 250 mL of convalescent plasma within 12 h after randomization, with a second administration of 2 units 24 to 36 h after ending the first administration. The trial aims to include 483 patients and will recruit from 25 centres across Belgium. The primary endpoint is the proportion of patients that require mechanical ventilation or have died at day 15. The main secondary endpoints are clinical status on day 15 and day 30 after randomization, as defined by the WHO Progression 10-point ordinal scale, and safety of the administration of convalescent plasma. DISCUSSION: This trial will either provide support or discourage the use of convalescent plasma as an early intervention for the treatment of hospitalized patients with COVID-19 infection. TRIAL REGISTRATION: ClinicalTrials.gov NCT04429854 . Registered on 12 June 2020 - Retrospectively registered.

Returning to Elective Orthopedic Surgery During the COVID-19 Pandemic: A Multidisciplinary and Pragmatic Strategy for Initial Patient Selection.

OBJECTIVE: The aim of the study was to design an objective, transparent, pragmatic, and flexible workflow to assist with patient selection during the initial phase of return to elective orthopedic surgery during the COVID-19 pandemic with the main purpose of enhancing patient safety. METHODS: A multidisciplinary working group was formed consisting of representatives for orthopedics, epidemiology, ethics, infectious diseases, cardiovascular diseases, and intensive care medicine. Preparation for upcoming meetings consisted of reading up on literature and testing of proposed methodologies on our own waiting lists. RESULTS: A workflow based on 3 domains, that is, required resources, patient fitness, and time sensitivity of the procedure, was considered most useful. All domains function as standalones, in a specific order, and no sum score is used. The domain of required resources demands input from the surgical team, results in a categorical (yes or no) outcome, and generates a list of potential patients who can be scheduled for surgery under these particular circumstances. The (weighted) items for the domain of patient fitness are the same for every patient, are scored on a numerical scale, but are likely to change during the pandemic as more data become available. Time sensitivity of the procedure is again scored on a numerical scale and becomes increasingly important when returning to elective surgery proves to be acceptably safe. After patient selection, an augmented informed consent, screening, and testing according to local guidelines will take place. CONCLUSIONS: A workflow is proposed for patient selection aiming for the safest possible return to elective orthopedic surgery during the COVID-19 pandemic.

Managing ICU surge during the COVID-19 crisis: rapid guidelines.

Given the rapidly changing nature of COVID-19, clinicians and policy makers require urgent review and summary of the literature, and synthesis of evidence-based guidelines to inform practice. The WHO advocates for rapid reviews in these circumstances. The purpose of this rapid guideline is to provide recommendations on the organizational management of intensive care units caring for patients with COVID-19 including: planning a crisis surge response; crisis surge response strategies; triage, supporting families, and staff.