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Risk prediction scores are important tools to support clinical decision-making for patients with coronavirus disease (COVID-19). The objective of this paper was to validate the 4C mortality score, originally developed in the United Kingdom, for a Canadian population, and to examine its performance over time. We conducted an external validation study within a registry of COVID-19 positive hospital admissions in the Kitchener-Waterloo and Hamilton regions of southern Ontario between March 4, 2020 and June 13, 2021. We examined the validity of the 4C score to prognosticate in-hospital mortality using the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals calculated via bootstrapping. The study included 959 individuals, of whom 224 (23.4%) died in-hospital. Median age was 72 years and 524 individuals (55%) were male. The AUC of the 4C score was 0.77, 95% confidence interval 0.79–0.87. Overall mortality rates across the pre-defined risk groups were 0% (Low), 8.0% (Intermediate), 27.2% (High), and 54.2% (Very High). Wave 1, 2 and 3 values of the AUC were 0.81 (0.76, 0.86), 0.74 (0.69, 0.80), and 0.76 (0.69, 0.83) respectively. The 4C score is a valid tool to prognosticate mortality from COVID-19 in Canadian hospitals and can be used to prioritize care and resources for patients at greatest risk of death.

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Controversy exists on the optimal age for elective resection of asymptomatic congenital pulmonary airway malformation. Current recommendations vary widely, highlighting the overall lack of consensus. A systematic search of Embase, MEDLINE, CINAL, and CENTRAL was conducted in January 2016. Identified citations were screening independently in duplicate and consensus was required for inclusion. Results were pooled using inverse variance fixed effects meta-analysis. Meta-analysis results indicate no statistically significant differences for complications within the 3-month and 6-month age comparison groups [odds ratio (OR) 4.20, 95% confidence interval (CI) 0.78-22.77, I = 0%; OR 2.39, 95% CI 0.63-9.11, I = 0%, respectively]. Older patients were significantly favoured for 3-month and 6-month age comparison groups for length of hospital stay [mean difference (MD) 4.13, 95% CI 2.31-5.96, I = 0%; MD 3.38, 95% CI 0.44-6.31, I = 0%, respectively]. Borderline statistical significance was observed for chest tube duration in patients ≥6 months of age (MD 1.06, 95% CI 0.02-2.09, I = 0%). No mortalities were recorded. Surgical treatment appears to be safe at all ages, with no mortalities and similar rates of complications between age groups. The included evidence was not sufficient to make a conclusive recommendation on optimal age for elective resection.

Objectives: Risk prediction scores are important tools to support clinical decision-making for patients with coronavirus disease (COVID-19). The objective of this paper was to validate the 4C mortality score, originally developed in the United Kingdom, for a Canadian population. Methods: We conducted an external validation study within a registry of COVID-19 positive emergency department visits and hospital admissions in the Kitchener-Waterloo and Hamilton regions of southern Ontario between March 4 and January 9, 2020. We examined the validity of the 4C score to prognosticate in-hospital mortality using the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals calculated via bootstrapping. Results: The study included 560 individuals, of whom 115 (20.5%) died in-hospital. Median age was 69 years and 281 individuals (51%) were male. The AUC of the 4C score was 0.83, 95% confidence interval 0.79-0.87. Mortality rates across the pre-defined risk groups were 0% (Low), 3.2% (Intermediate), 25.9% (High), and 59.5% (Very High). The AUC was 0.80 (0.76-0.85) among hospital inpatients. Interpretation: The 4C score is a valid tool to prognosticate mortality from COVID-19 in Canadian emergency departments and hospitals.