Background: Whether respiratory physiology of COVID-19-induced respiratory failure is different from acute respiratory distress syndrome (ARDS) of other etiologies is unclear. We conducted a single-center study to describe respiratory mechanics and response to positive end-expiratory pressure (PEEP) in COVID-19 ARDS and to compare COVID-19 patients to matched-control subjects with ARDS from other causes. Methods: Thirty consecutive COVID-19 patients admitted to an intensive care unit in Rome, Italy, and fulfilling moderate-to-severe ARDS criteria were enrolled within 24 h from endotracheal intubation. Gas exchange, respiratory mechanics, and ventilatory ratio were measured at PEEP of 15 and 5 cmH₂O. A single-breath derecruitment maneuver was performed to assess recruitability. After 1:1 matching based on PaO₂/FiO₂, FiO₂, PEEP, and tidal volume, COVID-19 patients were compared to subjects affected by ARDS of other etiologies who underwent the same procedures in a previous study. Results: Thirty COVID-19 patients were successfully matched with 30 ARDS from other etiologies. At low PEEP, median [25th–75th percentiles] PaO₂/FiO₂ in the two groups was 119 mmHg [101–142] and 116 mmHg [87–154]. Average compliance (41 ml/cmH₂O [32–52] vs. 36 ml/cmH₂O [27–42], p = 0.045) and ventilatory ratio (2.1 [1.7–2.3] vs. 1.6 [1.4–2.1], p = 0.032) were slightly higher in COVID-19 patients. Inter-individual variability (ratio of standard deviation to mean) of compliance was 36% in COVID-19 patients and 31% in other ARDS. In COVID-19 patients, PaO₂/FiO₂ was linearly correlated with respiratory system compliance (r = 0.52 p = 0.003). High PEEP improved PaO₂/FiO₂ in both cohorts, but more remarkably in COVID-19 patients (p = 0.005). Recruitability was not different between cohorts (p = 0.39) and was highly inter-individually variable (72% in COVID-19 patients and 64% in ARDS from other causes). In COVID-19 patients, recruitability was independent from oxygenation and respiratory mechanics changes due to PEEP. Conclusions: Early after establishment of mechanical ventilation, COVID-19 patients follow ARDS physiology, with compliance reduction related to the degree of hypoxemia, and inter-individually variable respiratory mechanics and recruitability. Physiological differences between ARDS from COVID-19 and other causes appear small.

Introduction: The aim of this study was to evaluate the incidence and determinants of AKI in a large cohort of cardiac arrest patients.Methods: We reviewed all patients admitted, for at least 48 hours, to our Dept. of Intensive Care after CA between January 2008 and October 2012. AKI was defined as oligo-anuria (daily urine output <0.5 ml/kg/h) and/or an increase in serum creatinine (≥0.3 mg/dl from admission value within 48 hours or a 1.5 time from baseline level). Demographics, comorbidities, CA details, and ICU interventions were recorded. Neurological outcome was assessed at 3 months using the Cerebral Performance Category scale (CPC 1–2 = favorable outcome; 3–5 = poor outcome).Results: A total of 199 patients were included, 85 (43%) of whom developed AKI during the ICU stay. Independent predictors of AKI development were older age, chronic renal disease, higher dose of epinephrine, in-hospital CA, presence of shock during the ICU stay, a low creatinine clearance (CrCl) on admission and a high cumulative fluid balance at 48 hours. Patients with AKI had higher hospital mortality (55/85 vs. 57/114, p = 0.04), but AKI was not an independent predictor of poor 3-month neurological outcome.Conclusions: AKI occurred in more than 40% of patients after CA. These patients had more severe hemodynamic impairment and needed more aggressive ICU therapy; however the development of AKI did not influence neurological recovery.

Bedside functional hemodynamic assessment has gained in popularity in the last years to overcome the limitations of static or dynamic indexes in predicting fluid responsiveness. The aim of this systematic review and metanalysis of studies is to investigate the reliability of the functional hemodynamic tests (FHTs) used to assess fluid responsiveness in adult patients in the intensive care unit (ICU) and operating room (OR). MEDLINE, EMBASE, and Cochrane databases were screened for relevant articles using a FHT, with the exception of the passive leg raising. The QUADAS-2 scale was used to assess the risk of bias of the included studies. In-between study heterogeneity was assessed through the I2 indicator. Bias assessment graphs were plotted, and Egger’s regression analysis was used to evaluate the publication bias. The metanalysis determined the pooled area under the receiving operating characteristic (ROC) curve, sensitivity, specificity, and threshold for two FHTs: the end-expiratory occlusion test (EEOT) and the mini-fluid challenge (FC). After text selection, 21 studies met the inclusion criteria, 7 performed in the OR, and 14 in the ICU between 2005 and 2018. The search included 805 patients and 870 FCs with a median (IQR) of 39 (25–50) patients and 41 (30–52) FCs per study. The median fluid responsiveness was 54% (45–59). Ten studies (47.6%) adopted a gray zone analysis of the ROC curve, and a median (IQR) of 20% (15–51) of the enrolled patients was included in the gray zone. The pooled area under the ROC curve for the end-expiratory occlusion test (EEOT) was 0.96 (95%CI 0.92–1.00). The pooled sensitivity and specificity were 0.86 (95%CI 0.74–0.94) and 0.91 (95%CI 0.85–0.95), respectively, with a best threshold of 5% (4.0–8.0%). The pooled area under the ROC curve for the mini-FC was 0.91 (95%CI 0.85–0.97). The pooled sensitivity and specificity were 0.82 (95%CI 0.76–0.88) and 0.83 (95%CI 0.77–0.89), respectively, with a best threshold of 5% (3.0–7.0%). The EEOT and the mini-FC reliably predict fluid responsiveness in the ICU and OR. Other FHTs have been tested insofar in heterogeneous clinical settings and, despite promising results, warrant further investigations.

Elevated lactate concentration has been associated with increased mortality after out-of-hospital cardiac arrest (CA). We investigated the variables associated with high blood lactate concentrations and explored the relationship between blood lactate and neurological outcome in this setting. This was a retrospective analysis of an institutional database that included all adult (> 18 years) patients admitted to a multidisciplinary Department of Intensive Care between January 2009 and January 2013 after resuscitation from CA. Blood lactate concentrations were collected at hospital admission and 6, 12, 24 and 48 h thereafter. Neurological outcome was evaluated 3 months post-CA using the Cerebral Performance Category (CPC) score: a CPC of 3–5 was used to define a poor outcome. Of the 236 patients included, 162 (69%) had a poor outcome. On admission, median lactate concentrations (5.3[2.9–9.0] vs. 2.5[1.5–5.5], p < 0.001) and cardiovascular sequential organ failure assessment (cSOFA) score (3[0–4] vs. 0[0–3], p = 0.003) were higher in patients with poor than in those with favourable outcomes. Lactate concentrations were higher in patients with poor outcomes at all time points. Lactate concentrations were similar in patients with out-of-hospital and in-hospital CA at all time points. After adjustment, high admission lactate was independently associated with a poor neurological outcome (OR 1.18, 95% CI 1.08–1.30; p < 0.001). In multivariable analysis, use of vasopressors and high PaO2 on admission, longer time to return of spontaneous circulation and altered renal function were associated with high admission lactate concentrations. High lactate concentrations on admission were an independent predictor of poor neurological recovery post-CA, but the time course was not related to outcome. Prolonged resuscitation, use of vasopressors, high PaO2 and altered renal function were predictors of high lactate concentrations.