Factors for success of awake prone positioning in patients with COVID-19-induced acute hypoxemic respiratory failure: analysis of a randomized controlled trial

Acute hypoxemic respiratory failure; COVID-19; IntubationInsuficiencia respiratoria hipoxémica aguda; COVID-19; IntubaciónInsuficiència respiratòria hipoxèmica aguda; COVID-19; IntubacióBackground Awake prone positioning (APP) improves oxygenation in coronavirus disease (COVID-19) patients and, when successful, may decrease the risk of intubation. However, factors associated with APP success remain unknown. In this secondary analysis, we aimed to assess whether APP can reduce intubation rate in patients with COVID-19 and to focus on the factors associated with success. Methods In this multicenter randomized controlled trial, conducted in three high-acuity units, we randomly assigned patients with COVID-19-induced acute hypoxemic respiratory failure (AHRF) requiring high-flow nasal cannula (HFNC) oxygen to APP or standard care. Primary outcome was intubation rate at 28 days. Multivariate analyses were performed to identify the predictors associated to treatment success (survival without intubation). Results Among 430 patients randomized, 216 were assigned to APP and 214 to standard care. The APP group had a lower intubation rate (30% vs 43%, relative risk [RR] 0.70; CI95 0.54–0.90, P = 0.006) and shorter hospital length of stay (11 interquartile range [IQR, 9–14] vs 13 [IQR, 10–17] days, P = 0.001). A respiratory rate ≤ 25 bpm at enrollment, an increase in ROX index > 1.25 after first APP session, APP duration > 8 h/day, and a decrease in lung ultrasound score ≥ 2 within the first 3 days were significantly associated with treatment success for APP. Conclusion In patients with COVID-19-induced AHRF treated by HFNC, APP reduced intubation rate and improved treatment success. A longer APP duration is associated with APP success, while the increase in ROX index and decrease in lung ultrasound score after APP can also help identify patients most likely to benefit

High-Flow Nasal Cannula Failure Odds Is Largely Independent of Duration of Use in COVID-19

Nasal Cannula; COVID-19Cánula nasal; COVID-19Cànula nasal; COVID-1

Endotoxin-induced myocardial dysfunction in senescent rats

INTRODUCTION: Aging is associated with a decline in cardiac contractility and altered immune function. The aim of this study was to determine whether aging alters endotoxin-induced myocardial dysfunction. METHODS: Senescent (24 month) and young adult (3 month) male Wistar rats were treated with intravenous lipopolysaccharide (LPS) (0.5 mg/kg (senescent and young rats) or 5 mg/kg (young rats only)), or saline (senescent and young control groups). Twelve hours after injection, cardiac contractility (isolated perfused hearts), myofilament Ca(2+ )sensitivity (skinned fibers), left ventricular nitric oxide end-oxidation products (NOx and NO(2)) and markers of oxidative stress (thiobarbituric acid reactive species (TBARS) and antioxidant enzymes) were investigated. RESULTS: LPS (0.5 mg/kg) administration resulted in decreased contractility in senescent rats (left ventricular developed pressure (LVDP), 25 ± 4 vs 53 ± 4 mmHg/g heart weight in control; P < 0.05) of amplitude similar to that in young rats with LPS 5 mg/kg (LVDP, 48 ± 7 vs 100 ± 7 mmHg/g heart weight in control; P < 0.05). In contrast to young LPS rats (0.5 and 5 mg/kg LPS), myofilament Ca(2+ )sensitivity was unaltered in senescent LPS hearts. Myocardial NOx and NO(2 )were increased in a similar fashion by LPS in young (both LPS doses) and senescent rats. TBARS and antioxidant enzyme activities were unaltered by sepsis whatever the age of animals. CONCLUSION: Low dose of LPS induced a severe myocardial dysfunction in senescent rats. Ca(2+ )myofilament responsiveness, which is typically reduced in myocardium of young adult septic rats, however, was unaltered in senescent rats. If these results are confirmed in in vivo conditions, they may provide a cellular explanation for the divergent reports on ventricular diastolic function in septic shock. In addition, Ca(2+)-sensitizing agents may not be as effective in aged subjects as in younger subjects

Interest of a "fixed sample size prospective meta-experiment" approach in therapeutic evaluation

L'effectif est une question majeure de la planification d'un essai randomisé et n'est pas trivial à définir. Déterminer la taille de l'échantillon d'un point de vue statistique correspond à maitriser le taux d'erreur de type II sous l'hypothèse d'une certaine différence entre les bras de traitement. Une étude est conventionnellement considérée comme correctement planifiée quand elle assure un taux d'erreur de type II à 20%, voire 10%. C'est pourquoi les comités éthiques exigent que l'hypothèse faite sur le critère de jugement principal, et la valeur prise pour le paramètre de nuisance, soient explicitées dans le protocole. En pratique ces exigences peuvent mener à des stratégies problématiques, comme la substitution du critère de jugement principal, ou bien tout simplement à l'abandon de l'essai car un compromis entre une hypothèse réaliste et le financement ou la durée de l'étude n'est pas possible. De plus, la précision des calculs est relativement illusoire, car ils nécessitent de prendre une valeur donnée pour le paramètre de nuisance, qui se révèle souvent éloignée de ce qui est observé dans l'essai. Le premier travail de cette thèse consistait à considérer un calcul d'effectif standard et à étudier dans quelle mesure les erreurs faites sur le paramètre de nuisance impactait la puissance finale de l'essai. Pour cela une étude de simulation a été conduite. Nos résultats de simulations ont montré que la puissance finale des essais était plus fortement impactée pour un critère de jugement continu que pour un critère binaire. Ces résultats montrent que même avec des calculs d'effectif correctement faits, un nombre substantiel d'essais sont sous-puissants ou surpuissants à cause de l'incertitude sur le paramètre de nuisance. Le second travail de thèse consistait à définir et évaluer une approche alternative au classique essai conçu pour avoir une puissance de 80%. Cette approche alternative est une méta-analyse prospective constituée de base de trois essais indépendants de taille 100 chacun. Les résultats des trois essais sont ensuite combinés dans une méta-analyse à effet aléatoire. Ce modèle permet d'admettre une variation entre les trois effets traitement estimés. Un des avantages de cette méthode est en effet d'apporter une information supplémentaire par rapport à un essai unique, celle de l'éventuelle hétérogénéité des résultats obtenus. Cette approche alternative est ce que nous appellerons une méta-expérience. Une étude de simulation a été menée pour évaluer son efficacité statistique, en comparaison avec l'approche classiquement utilisée. Les résultats montraient qu'une méta-expérience assurait en moyenne la même précision, la même puissance et le même taux d'erreur de type I que l'approche classique.Choosing the sample size is a important stage of a clinical trial. On a statistical level, determining the sample size means to control the type II error rate under the hypothesis of a given difference between thez two treatment arms. A trial is considered to be correctly planned if its type II error rate is equal to 20%, or even 10%. Consequently, ethical committees ask the hypothesis on the main outcome and the assumption on the nuisance parameter to be clearly stated in the protocol. These requirements sometimes lead to different issues, such as the use of surrogate outcomes or even the abandonment of the trial. In the first work of this thesis, we examine the extent to which inaccurate assumptions for nuisance parameters used to calculate sample size can affect the power of a randomized controlled trial. We performed a simulation study. In total, 23%, 0% and 18% of RCTs with continuous, binary and time-to-event outcomes, respectively, were underpowered (i.e., the real power was 90%). Even with proper calculation of sample size, a substantial number of trials are underpowered or overpowered because of imprecise knowledge of nuisance parameters. In the second work of this thesis, we defined and evaluated an alternative design named meta-experiment which circumvents the need for sample size calculation. In a simulation study, we compared a meta-experiment approach to the classical approach to assess treatment efficacy. The meta-experiment approach involves use of meta-analyzed results from 3 randomized trials of fixed sample size, 100 subjects. A prospective meta-analysis of data from trials of fixed sample size provided the same precision, power and type I error rate, on average, as the classical approach. The meta-experiment approach may provide an alternative design which does not require a sample size calculation and addresses the essential need for study replication; results may have greater external validit

Sample Size Calculation: Inaccurate <i>A Priori</i> Assumptions for Nuisance Parameters Can Greatly Affect the Power of a Randomized Controlled Trial

<div><p>We aimed to examine the extent to which inaccurate assumptions for nuisance parameters used to calculate sample size can affect the power of a randomized controlled trial (RCT). In a simulation study, we separately considered an RCT with continuous, dichotomous or time-to-event outcomes, with associated nuisance parameters of standard deviation, success rate in the control group and survival rate in the control group at some time point, respectively. For each type of outcome, we calculated a required sample size <i>N</i> for a hypothesized treatment effect, an assumed nuisance parameter and a nominal power of 80%. We then assumed a nuisance parameter associated with a relative error at the design stage. For each type of outcome, we randomly drew 10,000 relative errors of the associated nuisance parameter (from empirical distributions derived from a previously published review). Then, retro-fitting the sample size formula, we derived, for the pre-calculated sample size <i>N</i>, the real power of the RCT, taking into account the relative error for the nuisance parameter. In total, 23%, 0% and 18% of RCTs with continuous, binary and time-to-event outcomes, respectively, were underpowered (i.e., the real power was < 60%, as compared with the 80% nominal power); 41%, 16% and 6%, respectively, were overpowered (i.e., with real power > 90%). Even with proper calculation of sample size, a substantial number of trials are underpowered or overpowered because of imprecise knowledge of nuisance parameters. Such findings raise questions about how sample size for RCTs should be determined.</p></div

Finding Alternatives to the Dogma of Power Based Sample Size Calculation: Is a Fixed Sample Size Prospective Meta-Experiment a Potential Alternative?

International audienceSample sizes for randomized controlled trials are typically based on power calculations. They require us to specify values for parameters such as the treatment effect, which is often difficult because we lack sufficient prior information. The objective of this paper is to provide an alternative design which circumvents the need for sample size calculation. In a simulation study, we compared a meta-experiment approach to the classical approach to assess treatment efficacy. The meta-experiment approach involves use of meta-analyzed results from 3 randomized trials of fixed sample size, 100 subjects. The classical approach involves a single randomized trial with the sample size calculated on the basis of an a priori-formulated hypothesis. For the sample size calculation in the classical approach, we used observed articles to characterize errors made on the formulated hypothesis. A prospective meta-analysis of data from trials of fixed sample size provided the same precision, power and type I error rate, on average, as the classical approach. The meta-experiment approach may provide an alternative design which does not require a sample size calculation and addresses the essential need for study replication; results may have greater external validity

Real power distributions for 80% intended power and considering a normal distribution for the relative error for the true nuisance parameter.

<p>Real power distributions for 80% intended power and considering a normal distribution for the relative error for the true nuisance parameter.</p

Distribution curves fitted on the relative errors observed for nuisance parameters.

<p>A gamma distribution was fitted for continuous outcomes. Angular transformations were applied before calculating relative errors for dichotomous and time-to-event outcomes, then normal distribution curves were fitted. Dataset of 147 published trials. (a) Relative error between the observed standard deviation compared to the postulated standard deviation for continuous data on for studies. (b) Relative error between the observed rate in the control group compared to the postulated rate in the control group for dichotomous data for 78 studies. (c) Relative error between the observed rate in the control group compared to the postulated rate in the control group for time to event data for 48 studies</p

Parameter of interest and nuisance parameter for the different types of data.

<p>Parameter of interest and nuisance parameter for the different types of data.</p

Methodological review showed that time-to-event outcomes are often inadequately handled in cluster randomized trials

International audienceObjectives: To estimate the prevalence of time-to-event (TTE) outcomes in cluster randomized trials (CRTs) and to examine their statistical management. Study design and setting: We searched PubMed to identify primary reports of CRTs published in six major general medical journals (2013-2018). Nature of outcomes and, for TTE outcomes, statistical methods for sample size, analysis, and measures of intracluster correlation were extracted.Results: A TTE analysis was used in 17% of the CRTs (32/184) either as a primary or secondary outcome analysis, or in a sensitivity analysis. Among the five CRTs with a TTE primary outcome, two accounted for both intracluster correlation and the TTE nature of the outcome in sample size calculation; one reported a measure of intracluster correlation in the analysis. Among the 32 CRTs with a least one TTE analysis, 44% (14/32) accounted for clustering in all TTE analyses. We identified 12 additional CRTs in which there was at least one outcome not analyzed as TTE for which a TTE analysis might have been preferred.Conclusion: TTE outcomes are not uncommon in CRTs but appropriate statistical methods are infrequently used. Our results suggest that further methodological development and explicit recommendations for TTE outcomes in CRTs are needed