Development and validation of a model to predict ceiling of care in COVID-19 hospitalized patients.

BACKGROUND: Therapeutic ceiling of care is the maximum level of care deemed appropiate to offer to a patient based on their clinical profile and therefore their potential to derive benefit, within the context of the availability of resources. To our knowledge, there are no models to predict ceiling of care decisions in COVID-19 patients or other acute illnesses. We aimed to develop and validate a clinical prediction model to predict ceiling of care decisions using information readily available at the point of hospital admission. METHODS: We studied a cohort of adult COVID-19 patients who were hospitalized in 5 centres of Catalonia between 2020 and 2021. All patients had microbiologically proven SARS-CoV-2 infection at the time of hospitalization. Their therapeutic ceiling of care was assessed at hospital admission. Comorbidities collected at hospital admission, age and sex were considered as potential factors for predicting ceiling of care. A logistic regression model was used to predict the ceiling of care. The final model was validated internally and externally using a cohort obtained from the Leeds Teaching Hospitals NHS Trust. The TRIPOD Checklist for Prediction Model Development and Validation from the EQUATOR Network has been followed to report the model. RESULTS: A total of 5813 patients were included in the development cohort, of whom 31.5% were assigned a ceiling of care at the point of hospital admission. A model including age, COVID-19 wave, chronic kidney disease, dementia, dyslipidaemia, heart failure, metastasis, peripheral vascular disease, chronic obstructive pulmonary disease, and stroke or transient ischaemic attack had excellent discrimination and calibration. Subgroup analysis by sex, age group, and relevant comorbidities showed excellent figures for calibration and discrimination. External validation on the Leeds Teaching Hospitals cohort also showed good performance. CONCLUSIONS: Ceiling of care can be predicted with great accuracy from a patient's clinical information available at the point of hospital admission. Cohorts without information on ceiling of care could use our model to estimate the probability of ceiling of care. In future pandemics, during emergency situations or when dealing with frail patients, where time-sensitive decisions about the use of life-prolonging treatments are required, this model, combined with clinical expertise, could be valuable. However, future work is needed to evaluate the use of this prediction tool outside COVID-19.

Characteristics and Outcomes by Ceiling of Care of Subjects Hospitalized with COVID-19 During Four Waves of the Pandemic in a Metropolitan Area: A Multicenter Cohort Study.

INTRODUCTION: The profiles of patients with COVID-19 have been widely studied, but little is known about differences in baseline characteristics and in outcomes between subjects with a ceiling of care assigned at hospital admission and subjects without a ceiling of care. The aim of this study is to compare, by ceiling of care, clinical features and outcomes of hospitalized subjects during four waves of COVID-19 in a metropolitan area in Catalonia. METHODS: Observational study conducted during the first (March-April 2020), second (October-November 2020), third (January-February 2021), and fourth wave (July-August 2021) of COVID-19 in five centers of Catalonia. All subjects were adults (> 18 years old) hospitalized with a proven SARS-CoV-2 infection and with therapeutic ceiling of care assessed by the attending physician at hospital admission. RESULTS: A total of 5813 subjects were analyzed. Subjects with a ceiling of care were mainly older (difference in median age of 20 years), with more comorbidities (Charlson index 3 points higher) and with fewer clinical signs at baseline than patients without a ceiling of care. Some features of their clinical profiles changed among waves. There were differences in treatments received during hospital admission across waves, but not between subjects with and without a ceiling of care. Subjects with a ceiling of care had a death incidence more than four times the death incidence of subjects a without a ceiling of care (risk ratio (RR) ranging from 3.5 in the first wave to almost 6 in the third and fourth). Incidence of severe pneumonia and complications for subjects with a ceiling of care was around 1.5 times the incidence in subjects without a ceiling of care. DISCUSSION: Analysis of hospitalized subjects with SARS-CoV-2 infection should be stratified according to therapeutic ceiling of care to avoid bias and outcome misestimation.

Clinical Frailty Scale (CFS) indicated frailty is associated with increased in-hospital and 30-day mortality in COVID-19 patients: a systematic review and meta-analysis.

BACKGROUND: The concept of frailty provides an age-independent, easy-to-use tool for risk stratification. We aimed to summarize the evidence on the efficacy of frailty tools in risk assessment in COVID-19 patients. METHODS: The protocol was registered (CRD42021241544). Studies reporting on frailty in COVID-19 patients were eligible. The main outcomes were mortality, length of hospital stay (LOH) and intensive care unit (ICU) admission in frail and non-frail COVID-19 patients. Frailty was also compared in survivors and non-survivors. Five databases were searched up to 24th September 2021. The QUIPS tool was used for the risk of bias assessment. Odds ratios (OR) and weighted mean differences (WMD) were calculated with 95% confidence intervals (CI) using a random effect model. Heterogeneity was assessed using the I2 and χ2 tests. RESULTS: From 3640 records identified, 54 were included in the qualitative and 42 in the quantitative synthesis. Clinical Frailty Scale (CFS) was used in 46 studies, the Hospital Frailty Risk Score (HFRS) by 4, the Multidimensional Prognostic Index (MPI) by 3 and three studies used other scores. We found that patients with frailty (CFS 4-9 or HFRS ≥ 5) have a higher risk of mortality (CFS: OR: 3.12; CI 2.56-3.81; HFRS OR: 1.98; CI 1.89-2.07). Patients with frailty (CFS 4-9) were less likely to be admitted to ICU (OR 0.28, CI 0.12-0.64). Quantitative synthesis for LOH was not feasible. Most studies carried a high risk of bias. CONCLUSIONS: As determined by CFS, frailty is strongly associated with mortality; hence, frailty-based patient management should be included in international COVID-19 treatment guidelines. Future studies investigating the role of frailty assessment on deciding ICU admission are strongly warranted.

Conventional oxygen therapy versus CPAP as a ceiling of care in ward-based patients with COVID-19: a multi-centre cohort evaluation.

BACKGROUND: Continuous positive airway pressure (CPAP) therapy is commonly used for respiratory failure due to severe COVID-19 pneumonitis, including in patients deemed not likely to benefit from invasive mechanical ventilation (nIMV). Little evidence exists demonstrating superiority over conventional oxygen therapy, whilst ward-level delivery of CPAP presents practical challenges. We sought to compare clinical outcomes of oxygen therapy versus CPAP therapy in patients with COVID-19 who were nIMV. METHODS: This retrospective multi-centre cohort evaluation included patients diagnosed with COVID-19 who were nIMV, had a treatment escalation plan of ward-level care and clinical frailty scale ≤ 6. Recruitment occurred during the first two waves of the UK COVID-19 pandemic in 2020; from 1st March to May 31st, and from 1st September to 31st December. Patients given CPAP were compared to patients receiving oxygen therapy that required FiO2 ≥0.4 for more than 12 hours at hospitals not providing ward-level CPAP. Logistic regression modelling was performed to compare 30-day mortality between treatment groups, accounting for important confounders and within-hospital clustering. FINDINGS: Seven hospitals provided data for 479 patients during the UK COVID-19 pandemic in 2020. Overall 30-day mortality was 75.6% in the oxygen group (186/246 patients) and 77.7% in the CPAP group (181/233 patients). A lack of evidence for a treatment effect persisted in the adjusted model (adjusted odds ratio 0.84 95% CI 0.57-1.23, p=0.37). 49.8% of patients receiving CPAP-therapy (118/237) chose to discontinue it. INTERPRETATION: No survival difference was found between using oxygen alone or CPAP to treat patients with severe COVID-19 who were nIMV. A high patient-initiated discontinuation rate for CPAP suggests a significant treatment burden. Further reflection is warranted on the current treatment guidance and widespread application of CPAP in this setting. FUNDING: L Pearmain is supported by the MRC (MR/R00191X/1). TW Felton is supported by the NIHR Manchester Biomedical Research Centre.