Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort.

BACKGROUND: Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster. METHODS: Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3. RESULTS: Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3. CONCLUSIONS: During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis.

Effects of intubation timing in patients with COVID-19 throughout the four waves of the pandemic: a matched analysis.

BACKGROUND: The primary aim of our study was to investigate the association between intubation timing and hospital mortality in critically ill patients with coronavirus disease 2019 (COVID-19)-associated respiratory failure. We also analysed both the impact of such timing throughout the first four pandemic waves and the influence of prior noninvasive respiratory support on outcomes. METHODS: This is a secondary analysis of a multicentre, observational and prospective cohort study that included all consecutive patients undergoing invasive mechanical ventilation due to COVID-19 from across 58 Spanish intensive care units (ICUs) participating in the CIBERESUCICOVID project. The study period was between 29 February 2020 and 31 August 2021. Early intubation was defined as that occurring within the first 24 h of ICU admission. Propensity score matching was used to achieve a balance across baseline variables between the early intubation cohort and those patients who were intubated after the first 24 h of ICU admission. Differences in outcomes between early and delayed intubation were also assessed. We performed sensitivity analyses to consider a different time-point (48 h from ICU admission) for early and delayed intubation. RESULTS: Of the 2725 patients who received invasive mechanical ventilation, a total of 614 matched patients were included in the analysis (307 for each group). In the unmatched population, there were no differences in mortality between the early and delayed groups. After propensity score matching, patients with delayed intubation presented higher hospital mortality (27.3% versus 37.1%; p=0.01), ICU mortality (25.7% versus 36.1%; p=0.007) and 90-day mortality (30.9% versus 40.2%; p=0.02) compared with the early intubation group. Very similar findings were observed when we used a 48-h time-point for early or delayed intubation. The use of early intubation decreased after the first wave of the pandemic (72%, 49%, 46% and 45% in the first, second, third and fourth waves, respectively; first versus second, third and fourth waves p<0.001). In both the main and sensitivity analyses, hospital mortality was lower in patients receiving high-flow nasal cannula (HFNC) (n=294) who were intubated earlier. The subgroup of patients undergoing noninvasive ventilation (n=214) before intubation showed higher mortality when delayed intubation was set as that occurring after 48 h from ICU admission, but not when after 24 h. CONCLUSIONS: In patients with COVID-19 requiring invasive mechanical ventilation, delayed intubation was associated with a higher risk of hospital mortality. The use of early intubation significantly decreased throughout the course of the pandemic. Benefits of such an approach occurred more notably in patients who had received HFNC.

A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study.

BACKGROUND: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. METHODS: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. RESULTS: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. CONCLUSIONS: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.

Early acute kidney injury is associated with in-hospital adverse outcomes in critically ill burn patients: an observational study.

BACKGROUND: There are no studies in large series of burn patients on the relationship between acute kidney injury (AKI) and adverse outcomes using the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. METHODS: We retrospectively analysed data from a cohort of burn patients admitted to the intensive care unit (ICU) with the diagnosis of burn injury. The diagnosis of AKI over the first 7 days after injury was made according to the KDIGO guidelines. The primary outcome was ICU mortality. We used estimative models using univariable and multivariable logistic regression analyses. RESULTS: A total of 960 patients were studied and AKI was diagnosed in 50.5%. In multivariable analysis, AKI was associated, as compared with patients without AKI, with ICU mortality {adjusted odds ratio [aOR] 2.135 [95% confidence interval (CI) 1.384-3.293]} and secondary outcomes [kidney replacement therapy, aOR 4.030 (95% CI 1.838-8.835); infection, aOR 1.437 (95% CI 1.107-1.866); hospital mortality, aOR 1.652 (95% CI 1.139-2.697)]. AKI stage 1 was associated with a higher ICU [aOR 1.869 (95% CI 1.183-2.954)] and hospital mortality [aOR 1.552 (95% CI 1.050-2.296)] and infection [aOR 1.383 (95% CI 1.049-1.823)]. AKI meeting the urine output (UO) criterion alone was not associated with increased mortality. Ignoring the UO criterion would have missed 50 (10.3%) cases with AKI. CONCLUSION: The KDIGO guidelines are useful to diagnose AKI in burn patients. Even the mild form of AKI is independently associated with increased mortality. Considering the UO criterion is important to more accurately assess the incidence of AKI, but AKI meeting the UO criterion alone is not associated with increased mortality.

Non-invasive oxygenation support in acutely hypoxemic COVID-19 patients admitted to the ICU: a multicenter observational retrospective study.

BACKGROUND: Non-invasive oxygenation strategies have a prominent role in the treatment of acute hypoxemic respiratory failure during the coronavirus disease 2019 (COVID-19). While the efficacy of these therapies has been studied in hospitalized patients with COVID-19, the clinical outcomes associated with oxygen masks, high-flow oxygen therapy by nasal cannula and non-invasive mechanical ventilation in critically ill intensive care unit (ICU) patients remain unclear. METHODS: In this retrospective study, we used the best of nine covariate balancing algorithms on all baseline covariates in critically ill COVID-19 patients supported with > 10 L of supplemental oxygen at one of the 26 participating ICUs in Catalonia, Spain, between March 14 and April 15, 2020. RESULTS: Of the 1093 non-invasively oxygenated patients at ICU admission treated with one of the three stand-alone non-invasive oxygenation strategies, 897 (82%) required endotracheal intubation and 310 (28%) died during the ICU stay. High-flow oxygen therapy by nasal cannula (n = 439) and non-invasive mechanical ventilation (n = 101) were associated with a lower rate of endotracheal intubation (70% and 88%, respectively) than oxygen masks (n = 553 and 91% intubated), p < 0.001. Compared to oxygen masks, high-flow oxygen therapy by nasal cannula was associated with lower ICU mortality (hazard ratio 0.75 [95% CI 0.58-0.98), and the hazard ratio for ICU mortality was 1.21 [95% CI 0.80-1.83] for non-invasive mechanical ventilation. CONCLUSION: In critically ill COVID-19 ICU patients and, in the absence of conclusive data, high-flow oxygen therapy by nasal cannula may be the approach of choice as the primary non-invasive oxygenation support strategy.

Impact of time to intubation on mortality and pulmonary sequelae in critically ill patients with COVID-19: a prospective cohort study.

QUESTION: We evaluated whether the time between first respiratory support and intubation of patients receiving invasive mechanical ventilation (IMV) due to COVID-19 was associated with mortality or pulmonary sequelae. MATERIALS AND METHODS: Prospective cohort of critical COVID-19 patients on IMV. Patients were classified as early intubation if they were intubated within the first 48 h from the first respiratory support or delayed intubation if they were intubated later. Surviving patients were evaluated after hospital discharge. RESULTS: We included 205 patients (140 with early IMV and 65 with delayed IMV). The median [p25;p75] age was 63 [56.0; 70.0] years, and 74.1% were male. The survival analysis showed a significant increase in the risk of mortality in the delayed group with an adjusted hazard ratio (HR) of 2.45 (95% CI 1.29-4.65). The continuous predictor time to IMV showed a nonlinear association with the risk of in-hospital mortality. A multivariate mortality model showed that delay of IMV was a factor associated with mortality (HR of 2.40; 95% CI 1.42-4.1). During follow-up, patients in the delayed group showed a worse DLCO (mean difference of - 10.77 (95% CI - 18.40 to - 3.15), with a greater number of affected lobes (+ 1.51 [95% CI 0.89-2.13]) and a greater TSS (+ 4.35 [95% CI 2.41-6.27]) in the chest CT scan. CONCLUSIONS: Among critically ill patients with COVID-19 who required IMV, the delay in intubation from the first respiratory support was associated with an increase in hospital mortality and worse pulmonary sequelae during follow-up.

Weaning Outcomes in Patients with Brain Injury.

BACKGROUND: Despite the need for specific weaning strategies in neurological patients, evidence is generally insufficient or lacking. We aimed to describe the evolution over time of weaning and extubation practices in patients with acute brain injury compared with patients who are mechanically ventilated (MV) due to other reasons. METHODS: We performed a secondary analysis of three prospective, observational, multicenter international studies conducted in 2004, 2010, and 2016 in adults who had need of invasive MV for more than 12 h. We collected data on baseline characteristics, variables related to management ventilator settings, and complications while patients were ventilated or until day 28. RESULTS: Among the 20,929 patients enrolled, we included 12,618 (60%) who started the weaning from MV, of whom 1722 (14%) were patients with acute brain injury. In the acutely brain-injured cohort, 538 patients (31%) did not undergo planned extubation, defined as the need for a tracheostomy without an attempt of extubation, accidental extubation, and death. Among the 1184 planned extubated patients with acute brain injury, 202 required reintubation (17%). Patients with acute brain injury had a higher odds for unplanned extubation (odds ratio [OR] 1.35, confidence interval for 95% [CI 95%] 1.19-1.54; p < 0.001), a higher odds of failure after the first attempt of weaning (spontaneous breathing trial or gradual reduction of ventilatory support; OR 1.14 [CI 95% 1.01-1.30; p = 0.03]), and a higher odds for reintubation (OR 1.41 [CI 95% 1.20-1.66; p < 0.001]) than patients without brain injury. Patients with hemorrhagic stroke had the highest odds for unplanned extubation (OR 1.47 [CI 95% 1.22-1.77; p < 0.001]), of failed extubation after the first attempt of weaning (OR 1.28 [CI 95% 1.06-1.55; p = 0.009]), and for reintubation (OR 1.49 [CI 95% 1.17-1.88; p < 0.001]). In relation to weaning evolution over time in patients with acute brain injury, the risk for unplanned extubation showed a downward trend; the risk for reintubation was not associated to time; and there was a significant increase in the percentage of patients who underwent extubation after the first attempt of weaning from MV. CONCLUSIONS: Patients with acute brain injury, compared with patients without brain injury, present higher odds of undergoing unplanned extubated after weaning was started, lower odds of being extubated after the first attempt, and a higher risk of reintubation.

Evolution Over Time of Ventilatory Management and Outcome of Patients With Neurologic Disease.

OBJECTIVES: To describe the changes in ventilator management over time in patients with neurologic disease at ICU admission and to estimate factors associated with 28-day hospital mortality. DESIGN: Secondary analysis of three prospective, observational, multicenter studies. SETTING: Cohort studies conducted in 2004, 2010, and 2016. PATIENTS: Adult patients who received mechanical ventilation for more than 12 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among the 20,929 patients enrolled, we included 4,152 (20%) mechanically ventilated patients due to different neurologic diseases. Hemorrhagic stroke and brain trauma were the most common pathologies associated with the need for mechanical ventilation. Although volume-cycled ventilation remained the preferred ventilation mode, there was a significant (p < 0.001) increment in the use of pressure support ventilation. The proportion of patients receiving a protective lung ventilation strategy was increased over time: 47% in 2004, 63% in 2010, and 65% in 2016 (p < 0.001), as well as the duration of protective ventilation strategies: 406 days per 1,000 mechanical ventilation days in 2004, 523 days per 1,000 mechanical ventilation days in 2010, and 585 days per 1,000 mechanical ventilation days in 2016 (p < 0.001). There were no differences in the length of stay in the ICU, mortality in the ICU, and mortality in hospital from 2004 to 2016. Independent risk factors for 28-day mortality were age greater than 75 years, Simplified Acute Physiology Score II greater than 50, the occurrence of organ dysfunction within first 48 hours after brain injury, and specific neurologic diseases such as hemorrhagic stroke, ischemic stroke, and brain trauma. CONCLUSIONS: More lung-protective ventilatory strategies have been implemented over years in neurologic patients with no effect on pulmonary complications or on survival. We found several prognostic factors on mortality such as advanced age, the severity of the disease, organ dysfunctions, and the etiology of neurologic disease.

Metabolomic diferences between COVID-19 and H1N1 influenza induced ARDS.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a type of respiratory failure characterized by lung inflammation and pulmonary edema. Coronavirus disease 2019 (COVID-19) is associated with ARDS in the more severe cases. This study aimed to compare the specificity of the metabolic alterations induced by COVID-19 or Influenza A pneumonia (IAP) in ARDS. METHODS: Eighteen patients with ARDS due to COVID-19 and twenty patients with ARDS due to IAP, admitted to the intensive care unit. ARDS was defined as in the American-European Consensus Conference. As compared with patients with COVID-19, patients with IAP were younger and received more often noradrenaline to maintain a mean arterial pressure > 65 mm Hg. Serum samples were analyzed by Nuclear Magnetic Resonance Spectroscopy. Multivariate Statistical Analyses were used to identify metabolic differences between groups. Metabolic pathway analysis was performed to identify the most relevant pathways involved in ARDS development. RESULTS: ARDS due to COVID-19 or to IAP induces a different regulation of amino acids metabolism, lipid metabolism, glycolysis, and anaplerotic metabolism. COVID-19 causes a significant energy supply deficit that induces supplementary energy-generating pathways. In contrast, IAP patients suffer more marked inflammatory and oxidative stress responses. The classificatory model discriminated against the cause of pneumonia with a success rate of 100%. CONCLUSIONS: Our findings support the concept that ARDS is associated with a characteristic metabolomic profile that may discriminate patients with ARDS of different etiologies, being a potential biomarker for the diagnosis, prognosis, and management of this condition.

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients.

BACKGROUND: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. METHODS: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. RESULTS: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). CONCLUSIONS: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation.

Machine learning predicts mortality based on analysis of ventilation parameters of critically ill patients: multi-centre validation.

BACKGROUND: Mechanical Ventilation (MV) is a complex and central treatment process in the care of critically ill patients. It influences acid-base balance and can also cause prognostically relevant biotrauma by generating forces and liberating reactive oxygen species, negatively affecting outcomes. In this work we evaluate the use of a Recurrent Neural Network (RNN) modelling to predict outcomes of mechanically ventilated patients, using standard mechanical ventilation parameters. METHODS: We performed our analysis on VENTILA dataset, an observational, prospective, international, multi-centre study, performed to investigate the effect of baseline characteristics and management changes over time on the all-cause mortality rate in mechanically ventilated patients in ICU. Our cohort includes 12,596 adult patients older than 18, associated with 12,755 distinct admissions in ICUs across 37 countries and receiving invasive and non-invasive mechanical ventilation. We carry out four different analysis. Initially we select typical mechanical ventilation parameters and evaluate the machine learning model on both, the overall cohort and a subgroup of patients admitted with respiratory disorders. Furthermore, we carry out sensitivity analysis to evaluate whether inclusion of variables related to the function of other organs, improve the predictive performance of the model for both the overall cohort as well as the subgroup of patients with respiratory disorders. RESULTS: Predictive performance of RNN-based model was higher with Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.72 (± 0.01) and Average Precision (AP) of 0.57 (± 0.01) in comparison to RF and LR for the overall patient dataset. Higher predictive performance was recorded in the subgroup of patients admitted with respiratory disorders with AUC of 0.75 (± 0.02) and AP of 0.65 (± 0.03). Inclusion of function of other organs further improved the performance to AUC of 0.79 (± 0.01) and AP 0.68 (± 0.02) for the overall patient dataset and AUC of 0.79 (± 0.01) and AP 0.72 (± 0.02) for the subgroup with respiratory disorders. CONCLUSION: The RNN-based model demonstrated better performance than RF and LR in patients in mechanical ventilation and its subgroup admitted with respiratory disorders. Clinical studies are needed to evaluate whether it impacts decision-making and patient outcomes. TRIAL REGISTRATION: NCT02731898 ( https://clinicaltrials.gov/ct2/show/NCT02731898 ), prospectively registered on April 8, 2016.

Invasive Mechanical Ventilation in Chronic Obstructive Pulmonary Disease Exacerbations.

Chronic obstructive pulmonary disease (COPD) continues to be an important cause of morbidity, mortality, and health care costs worldwide. Although there exist some heterogeneity between patients, the course of COPD is characterized by recurrent acute exacerbations, which are among the most common causes of medical admission to hospital. Patients with frequent exacerbations have accelerated lung function decline, worse quality of life, and greater mortality. Therefore, interest is growing in assessing the effectiveness of interventions used to treat exacerbations. The present review summarizes the current evidence regarding the use of ventilatory management to treat COPD and the implementation of novel cost-effective strategies, such as high-flow oxygenation or extracorporeal carbon dioxide removal to improve clinical outcomes and functional recovery in this disease and to reduce the associated costs.

Prediction and Outcome of Intensive Care Unit-Acquired Paresis.

BACKGROUND: Intensive care unit-acquired paresis (ICUAP) is associated with poor outcomes. Our objective was to evaluate predictors for ICUAP and the short-term outcomes associated with this condition. METHODS: A secondary analysis of a prospective study including 4157 mechanically ventilated adults in 494 intensive care units from 39 countries. After sedative interruption, patients were screened for ICUAP daily, which was defined as the presence of symmetric and flaccid quadriparesis associated with decreased or absent deep tendon reflexes. A multinomial logistic regression was used to create a predictive model for ICUAP. Propensity score matching was used to estimate the relationship between ICUAP and short-term outcomes (ie, weaning failure and intensive care unit [ICU] mortality). RESULTS: Overall, 114 (3%) patients had ICUAP. Variables associated with ICUAP were duration of mechanical ventilation (relative risk ratio [RRR] per day, 1.10; 95% confidence interval [CI] 1.08-1.12), steroid therapy (RRR 1.8; 95% CI, 1.2-2.8), insulin therapy (RRR 1.8; 95% CI 1.2-2.7), sepsis (RRR 1.9; 95% CI: 1.2 to 2.9), acute renal failure (RRR 2.2; 95% CI 1.5-3.3), and hematological failure (RRR 1.9; 95% CI: 1.2-2.9). Coefficients were used to generate a weighted scoring system to predict ICUAP. ICUAP was significantly associated with both weaning failure (paired rate difference of 22.1%; 95% CI 9.8-31.6%) and ICU mortality (paired rate difference 10.5%; 95% CI 0.1-24.0%). CONCLUSIONS: Intensive care unit-acquired paresis is relatively uncommon but is significantly associated with weaning failure and ICU mortality. We constructed a weighted scoring system, with good discrimination, to predict ICUAP in mechanically ventilated patients at the time of awakening.

Predictors of diffuse alveolar damage in patients with acute respiratory distress syndrome: a retrospective analysis of clinical autopsies.

BACKGROUND: Although diffuse alveolar damage (DAD) is considered the typical histological pattern of acute respiratory distress syndrome (ARDS), only half of patients exhibit this morphological hallmark. Patients with DAD may have higher mortality than those without DAD. Therefore, we aimed to identify the factors associated with DAD in patients with ARDS. METHODS: We analyzed autopsy samples of 356 patients who had ARDS at the time of death. DAD was assessed by two pathologists, and ARDS criteria were evaluated by two intensivists. Criteria for severe ARDS included the degree of hypoxemia and the ancillary variables of the current Berlin definition assessed within 48 h before death: radiographic severity, high positive end-expiratory pressure (PEEP) level, and physiological variables (i.e., altered respiratory system compliance and large anatomic dead space). RESULTS: After multivariable analysis, high PEEP levels, physiological variables, and opacities involving only three quadrants on chest radiographs were not associated with DAD. The four markers independently associated with DAD were (1) duration of evolution (OR 3.29 [1.95-5.55] for patients with ARDS ≥ 3 days, p < 0.001), (2) degree of hypoxemia (OR 3.92 [1.48-10.3] for moderate ARDS and 6.18 [2.34-16.3] for severe ARDS, p < 0.01 for both), (3) increased dynamic driving pressure (OR 1.06 [1.04-1.09], p = 0.007), and (4) radiographic severity (OR 2.91 [1.47-5.75] for patients with diffuse opacities involving the four quadrants, p = 0.002). DAD was found in two-thirds of patients with a ratio of partial pressure of arterial oxygen to fraction of inspired oxygen ≤ 100 mmHg and opacities involving the four quadrants. CONCLUSIONS: In addition to severe hypoxemia, diffuse opacities involving the four quadrants were a strong marker of DAD.

Discontinuation of ventilatory support: new solutions to old dilemmas.

PURPOSE OF REVIEW: Weaning from mechanical ventilation implies two separate but closely related aspects of care, the discontinuation of mechanical ventilation and removal of artificial airway, which implies routine clinical dilemmas. Extubation delay and extubation failure are associated with poor clinical outcomes. We sought to summarize recent evidence on weaning. RECENT FINDINGS: Tolerance to an unassisted breathing does not require routine use of weaning predictors and can be addressed using weaning protocols or by implementing automatic weaning methods. Spontaneous breathing trial can be performed on low levels of pressure support, continuous positive airway pressure, or T-piece. Echocardiographic tools may help to prevent the failure of extubation. Noninvasive ventilation can prevent respiratory failure after extubation, when used in hypercapnic patients. Recently, sedation protocols and early mobilization in ventilated critically ill patients may decrease weaning period and duration of mechanical ventilation, and prevent extubation failure and complications such as ICU-acquired weakness. New techniques have been performed to identify patients with high risk for extubation failure. SUMMARY: There is an interesting body of clinical research in the discontinuation of mechanical ventilation. Recent randomized controlled studies provide high-level evidence for the best approaches to weaning, especially in patients who fail the first spontaneous breathing trial or targeted populations.

Management and outcome of mechanically ventilated patients after cardiac arrest.

INTRODUCTION: The aim of this study was to describe and compare the changes in ventilator management and complications over time, as well as variables associated with 28-day hospital mortality in patients receiving mechanical ventilation (MV) after cardiac arrest. METHODS: We performed a secondary analysis of three prospective, observational multicenter studies conducted in 1998, 2004 and 2010 in 927 ICUs from 40 countries. We screened 18,302 patients receiving MV for more than 12 hours during a one-month-period. We included 812 patients receiving MV after cardiac arrest. We collected data on demographics, daily ventilator settings, complications during ventilation and outcomes. Multivariate logistic regression analysis was performed to calculate odds ratios, determining which variables within 24 hours of hospital admission were associated with 28-day hospital mortality and occurrence of acute respiratory distress syndrome (ARDS) and pneumonia acquired during ICU stay at 48 hours after admission. RESULTS: Among 812 patients, 100 were included from 1998, 239 from 2004 and 473 from 2010. Ventilatory management changed over time, with decreased tidal volumes (VT) (1998: mean 8.9 (standard deviation (SD) 2) ml/kg actual body weight (ABW), 2010: 6.7 (SD 2) ml/kg ABW; 2004: 9 (SD 2.3) ml/kg predicted body weight (PBW), 2010: 7.95 (SD 1.7) ml/kg PBW) and increased positive end-expiratory pressure (PEEP) (1998: mean 3.5 (SD 3), 2010: 6.5 (SD 3); P <0.001). Patients included from 2010 had more sepsis, cardiovascular dysfunction and neurological failure, but 28-day hospital mortality was similar over time (52% in 1998, 57% in 2004 and 52% in 2010). Variables independently associated with 28-day hospital mortality were: older age, PaO2 <60 mmHg, cardiovascular dysfunction and less use of sedative agents. Higher VT, and plateau pressure with lower PEEP were associated with occurrence of ARDS and pneumonia acquired during ICU stay. CONCLUSIONS: Protective mechanical ventilation with lower VT and higher PEEP is more commonly used after cardiac arrest. The incidence of pulmonary complications decreased, while other non-respiratory organ failures increased with time. The application of protective mechanical ventilation and the prevention of single and multiple organ failure may be considered to improve outcome in patients after cardiac arrest.

Comparison of the Berlin definition for acute respiratory distress syndrome with autopsy.

RATIONALE: A revised definition of clinical criteria for acute respiratory distress syndrome (ARDS), the Berlin definition, was recently established to classify patients according to their severity. OBJECTIVE: To evaluate the accuracy of these clinical criteria using diffuse alveolar damage (DAD) at autopsy as the reference standard. METHODS: All patients who died and had a clinical autopsy in our intensive care unit over a 20-year period (1991-2010) were included. Patients with clinical criteria for ARDS were identified from the medical charts and were classified as mild, moderate, or severe according to the Berlin definition using PaO2/FiO2 oxygenation criteria. Microscopic analysis from each pulmonary lobe was performed by two pathologists. MEASUREMENTS AND MAIN RESULTS: Among 712 autopsies analyzed, 356 patients had clinical criteria for ARDS at time of death, classified as mild (n = 49, 14%), moderate (n = 141, 40%), and severe (n = 166, 46%). Sensitivity was 89% and specificity 63% to identify ARDS using the Berlin definition. DAD was found in 159 of 356 (45%) patients with clinical criteria for ARDS (in 12, 40, and 58% of patients with mild, moderate, and severe ARDS, respectively). DAD was more frequent in patients who met clinical criteria for ARDS during more than 72 hours and was found in 69% of those with severe ARDS for 72 hours or longer. CONCLUSIONS: Histopathological findings were correlated to severity and duration of ARDS. Using clinical criteria the revised Berlin definition for ARDS allowed the identification of severe ARDS of more than 72 hours as a homogeneous group of patients characterized by a high proportion of DAD.