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Aims Out-of-hospital cardiac arrest (OHCA) without return of spontaneous circulation (ROSC) despite conventional resuscitation is common and has poor outcomes. Adding extracorporeal membrane oxygenation (ECMO) to cardiopulmonary resuscitation (extracorporeal-CPR) is increasingly used in an attempt to improve outcomes. Methods and results We analysed a prospective registry of 13 191 OHCAs in the Paris region from May 2011 to January 2018. We compared survival at hospital discharge with and without extracorporeal-CPR and identified factors associated with survival in patients given extracorporeal-CPR. Survival was 8% in 525 patients given extracorporeal-CPR and 9% in 12 666 patients given conventional-CPR (P = 0.91). By adjusted multivariate analysis, extracorporeal-CPR was not associated with hospital survival [odds ratio (OR), 1.3; 95% confidence interval (95% CI), 0.8–2.1; P = 0.24]. By conditional logistic regression with matching on a propensity score (including age, sex, occurrence at home, bystander CPR, initial rhythm, collapse-to-CPR time, duration of resuscitation, and ROSC), similar results were found (OR, 0.8; 95% CI, 0.5–1.3; P = 0.41). In the extracorporeal-CPR group, factors associated with hospital survival were initial shockable rhythm (OR, 3.9; 95% CI, 1.5–10.3; P = 0.005), transient ROSC before ECMO (OR, 2.3; 95% CI, 1.1–4.7; P = 0.03), and prehospital ECMO implantation (OR, 2.9; 95% CI, 1.5–5.9; P = 0.002). Conclusions In a population-based registry, 4% of OHCAs were treated with extracorporeal-CPR, which was not associated with increased hospital survival. Early ECMO implantation may improve outcomes. The initial rhythm and ROSC may help select patients for extracorporeal-CPR.

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of "modifiable risk factors", measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details.

Background: Optimal timing for the start of vasopressors (VP) in septic shock has not been widely studied since it is assumed that fluids must be administered in advance. We sought to evaluate whether a very early start of VP, even without completing the initial fluid loading, might impact clinical outcomes in septic shock.Methods: A total of 337 patients with sepsis requiring VP support for at least 6 h were initially selected from a prospectively collected database in a 90-bed mixed-ICU during a 24-month period. They were classified into veryearly (VE-VPs) or delayed vasopressor start (D-VPs) categories according to whether norepinephrine was initiated or not within/before the next hour of the first resuscitative fluid load. Then, VE-VPs (n = 93) patients were 1:1 propensity matched to D-VPs (n = 93) based on age; source of admission (emergency room, general wards, intensive care unit); chronic and acute comorbidities; and lactate, heart rate, systolic, and diastolic pressure at vasopressor start. A riskadjusted Cox proportional hazard model was fitted to assess the association between VE-VPs and day 28 mortality. Finally, a sensitivity analysis was performed also including those patients requiring VP support for less than 6 h. Results: Patients subjected to VE-VPs received significantly less resuscitation fluids at vasopressor starting (0[0-510] vs. 1500[650-2300] mL, p < 0.001) and during the first 8 h of resuscitation (1100[500-1900] vs. 2600[1600-3800] mL, p < 0.001), with no significant increase in acute renal failure and/or renal replacement therapy requirements. VE-VPs was related with significant lower net fluid balances 8 and 24 h after VPs. VE-VPs was also associated with a significant reduction in the risk of death compared to D-VPs (HR 0.31, CI95% 0.17-0.57, p < 0.001) at day 28. Such association was maintained after including patients receiving vasopressors for < 6 h. Conclusion: A very early start of vasopressor support seems to be safe, might limit the amount of fluids to resuscitate septic shock, and could lead to better clinical outcomes.

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A personalized mechanical ventilation approach for patients with adult respiratory distress syndrome (ARDS) based on lung physiology and morphology, ARDS etiology, lung imaging, and biological phenotypes may improve ventilation practice and outcome. However, additional research is warranted before personalized mechanical ventilation strategies can be applied at the bedside. Ventilatory parameters should be titrated based on close monitoring of targeted physiologic variables and individualized goals. Although low tidal volume (VT) is a standard of care, further individualization of VT may necessitate the evaluation of lung volume reserve (e.g., inspiratory capacity). Low driving pressures provide a target for clinicians to adjust VT and possibly to optimize positive end-expiratory pressure (PEEP), while maintaining plateau pressures below safety thresholds. Esophageal pressure monitoring allows estimation of transpulmonary pressure, but its use requires technical skill and correct physiologic interpretation for clinical application at the bedside. Mechanical power considers ventilatory parameters as a whole in the optimization of ventilation setting, but further studies are necessary to assess its clinical relevance. The identification of recruitability in patients with ARDS is essential to titrate and individualize PEEP. To define gas-exchange targets for individual patients, clinicians should consider issues related to oxygen transport and dead space. In this review, we discuss the rationale for personalized approaches to mechanical ventilation for patients with ARDS, the role of lung imaging, phenotype identification, physiologically based individualized approaches to ventilation, and a future research agenda.

Background: Loss of vascular tone is a key pathophysiological feature of septic shock. Combination of gradual diastolic hypotension and tachycardia could reflect more serious vasodilatory conditions. We sought to evaluate the relationships between heart rate (HR) to diastolic arterial pressure (DAP) ratios and clinical outcomes during early phases of septic shock.Methods: Diastolic shock index (DSI) was defined as the ratio between HR and DAP. DSI calculated just before starting vasopressors (Pre-VPs/DSI) in a preliminary cohort of 337 patients with septic shock (January 2015 to February 2017) and at vasopressor start (VPs/DSI) in 424 patients with septic shock included in a recent randomized controlled trial (ANDROMEDA-SHOCK; March 2017 to April 2018) was partitioned into five quantiles to estimate the relative risks (RR) of death with respect to the mean risk of each population (assumed to be 1). Matched HR and DAP subsamples were created to evaluate the effect of the individual components of the DSI on RRs. In addition, time-course of DSI and interaction between DSI and vasopressor dose (DSI*NE.dose) were compared between survivors and non-survivors from both populations, while ROC curves were used to identify variables predicting mortality. Finally, as exploratory observation, effect of early start of vasopressors was evaluated at each Pre-VPs/DSI quintile from the preliminary cohort.Results: Risk of death progressively increased at gradual increments of Pre-VPs/DSI or VPs/DSI (One-way ANOVA, p < 0.001). Progressive DAP decrease or HR increase was associated with higher mortality risks only when DSI concomitantly increased. Areas under the ROC curve for Pre-VPs/DSI, SOFA and initial lactate were similar, while mean arterial pressure and systolic shock index showed poor performances to predict mortality. Time-course of DSI and DSI*NE. dose was significantly higher in non-survivors from both populations (repeated-measures ANOVA, p < 0.001). Very early start of vasopressors exhibited an apparent benefit at higher Pre-VPs/DSI quintile.Conclusions: DSI at pre-vasopressor and vasopressor start points might represent a very early identifier of patients at high risk of death. Isolated DAP or HR values do not clearly identify such risk. Usefulness of DSI to trigger or to direct therapeutic interventions in early resuscitation of septic shock need to be addressed in future studies.

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