Development of a repeated-measures predictive model and clinical risk score for mortality in ventilated COVID-19 patients.

PURPOSE: The COVID-19 pandemic has caused intensive care units (ICUs) to reach capacities requiring triage. A tool to predict mortality risk in ventilated patients with COVID-19 could inform decision-making and resource allocation, and allow population-level comparisons across institutions. METHODS: This retrospective cohort study included all mechanically ventilated adults with COVID-19 admitted to three tertiary care ICUs in Toronto, Ontario, between 1 March 2020 and 15 December 2020. Generalized estimating equations were used to identify variables predictive of mortality. The primary outcome was the probability of death at three-day intervals from the time of ICU admission (day 0), with risk re-calculation every three days to day 15; the final risk calculation estimated the probability of death at day 15 and beyond. A numerical algorithm was developed from the final model coefficients. RESULTS: One hundred twenty-seven patients were eligible for inclusion. Median ICU length of stay was 26.9 (interquartile range, 15.4-52.0) days. Overall mortality was 42%. From day 0 to 15, the variables age, temperature, lactate level, ventilation tidal volume, and vasopressor use significantly predicted mortality. Our final clinical risk score had an area under the receiver-operating characteristics curve of 0.9 (95% confidence interval [CI], 0.8 to 0.9). For every ten-point increase in risk score, the relative increase in the odds of death was approximately 4, with an odds ratio of 4.1 (95% CI, 2.9 to 5.9). CONCLUSION: Our dynamic prediction tool for mortality in ventilated patients with COVID-19 has excellent diagnostic properties. Notwithstanding, external validation is required before widespread implementation.

RéSUMé: OBJECTIF: En raison de la pandémie de COVID-19, les unités de soins intensifs (USI) ont atteint des taux d'occupation nécessitant un triage. Un outil pour prédire le risque de mortalité chez les patients sous ventilation atteints de COVID-19 pourrait éclairer la prise de décision et l'attribution des ressources tout en permettant des comparaisons populationnelles entre les établissements. MéTHODE: Cette étude de cohorte rétrospective a inclus tous les adultes atteints de COVID-19 sous ventilation mécanique admis dans trois USI de centres de soins tertiaires à Toronto, en Ontario, entre le 1er mars 2020 et le 15 décembre 2020. Des équations d'estimation généralisées ont été utilisées pour identifier les variables prédictives de mortalité. Le critère d'évaluation principal était la probabilité de décès à des intervalles de trois jours à partir du moment de l'admission à l'USI (jour 0), avec un nouveau calcul du risque tous les trois jours jusqu'au jour 15; le calcul final du risque a estimé la probabilité de décès au jour 15 et au-delà. Un algorithme numérique a été mis au point à partir des coefficients du modèle final. RéSULTATS: Cent vingt-sept patients étaient éligibles à l'inclusion. La durée médiane de séjour à l'USI était de 26,9 jours (écart interquartile, 15,4 à 52,0). La mortalité globale était de 42 %. Du jour 0 au jour 15, les variables que sont l'âge, la température, les taux de lactate, le volume courant de ventilation et l'utilisation de vasopresseurs ont constitué des prédicteurs significatifs de mortalité. Notre score de risque clinique final avait une aire sous la courbe ROC de 0,9 (intervalle de confiance [IC] à 95 %, 0,8 à 0,9). Pour chaque augmentation de dix points du score de risque, l'augmentation relative des risques de décès était d'environ 4, avec un rapport de cotes de 4,1 (IC 95 %, 2,9 à 5,9). CONCLUSION: Notre outil de prédiction dynamique de la mortalité pour les patients ventilés atteints de COVID-19 possède d'excellentes propriétés diagnostiques. Néanmoins, une validation externe est nécessaire avant sa mise en œuvre généralisée.

JAK inhibition reduces SARS-CoV-2 liver infectivity and modulates inflammatory responses to reduce morbidity and mortality.

Using AI, we identified baricitinib as having antiviral and anticytokine efficacy. We now show a 71% (95% CI 0.15 to 0.58) mortality benefit in 83 patients with moderate-severe SARS-CoV-2 pneumonia with few drug-induced adverse events, including a large elderly cohort (median age, 81 years). An additional 48 cases with mild-moderate pneumonia recovered uneventfully. Using organotypic 3D cultures of primary human liver cells, we demonstrate that interferon-α2 increases ACE2 expression and SARS-CoV-2 infectivity in parenchymal cells by greater than fivefold. RNA-seq reveals gene response signatures associated with platelet activation, fully inhibited by baricitinib. Using viral load quantifications and superresolution microscopy, we found that baricitinib exerts activity rapidly through the inhibition of host proteins (numb-associated kinases), uniquely among antivirals. This reveals mechanistic actions of a Janus kinase-1/2 inhibitor targeting viral entry, replication, and the cytokine storm and is associated with beneficial outcomes including in severely ill elderly patients, data that incentivize further randomized controlled trials.

A country level analysis measuring the impact of government actions, country preparedness and socioeconomic factors on COVID-19 mortality and related health outcomes.

BACKGROUND: A country level exploratory analysis was conducted to assess the impact of timing and type of national health policy/actions undertaken towards COVID-19 mortality and related health outcomes. METHODS: Information on COVID-19 policies and health outcomes were extracted from websites and country specific sources. Data collection included the government's action, level of national preparedness, and country specific socioeconomic factors. Data was collected from the top 50 countries ranked by number of cases. Multivariable negative binomial regression was used to identify factors associated with COVID-19 mortality and related health outcomes. FINDINGS: Increasing COVID-19 caseloads were associated with countries with higher obesity (adjusted rate ratio [RR]=1.06; 95%CI: 1.01-1.11), median population age (RR=1.10; 95%CI: 1.05-1.15) and longer time to border closures from the first reported case (RR=1.04; 95%CI: 1.01-1.08). Increased mortality per million was significantly associated with higher obesity prevalence (RR=1.12; 95%CI: 1.06-1.19) and per capita gross domestic product (GDP) (RR=1.03; 95%CI: 1.00-1.06). Reduced income dispersion reduced mortality (RR=0.88; 95%CI: 0.83-0.93) and the number of critical cases (RR=0.92; 95% CI: 0.87-0.97). Rapid border closures, full lockdowns, and wide-spread testing were not associated with COVID-19 mortality per million people. However, full lockdowns (RR=2.47: 95%CI: 1.08-5.64) and reduced country vulnerability to biological threats (i.e. high scores on the global health security scale for risk environment) (RR=1.55; 95%CI: 1.13-2.12) were significantly associated with increased patient recovery rates. INTERPRETATION: In this exploratory analysis, low levels of national preparedness, scale of testing and population characteristics were associated with increased national case load and overall mortality. FUNDING: This study is non-funded.