The PANDORA Study: Prevalence and Outcome of Acute Hypoxemic Respiratory Failure in the Pre-COVID-19 Era.

OBJECTIVES: To establish the epidemiological characteristics, ventilator management, and outcomes in patients with acute hypoxemic respiratory failure (AHRF), with or without acute respiratory distress syndrome (ARDS), in the era of lung-protective mechanical ventilation (MV). DESIGN: A 6-month prospective, epidemiological, observational study. SETTING: A network of 22 multidisciplinary ICUs in Spain. PATIENTS: Consecutive mechanically ventilated patients with AHRF (defined as Pao2/Fio2 ≤ 300 mm Hg on positive end-expiratory pressure [PEEP] ≥ 5 cm H2O and Fio2 ≥ 0.3) and followed-up until hospital discharge. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Primary outcomes were prevalence of AHRF and ICU mortality. Secondary outcomes included prevalence of ARDS, ventilatory management, and use of adjunctive therapies. During the study period, 9,803 patients were admitted: 4,456 (45.5%) received MV, 1,271 (13%) met AHRF criteria (1,241 were included into the study: 333 [26.8%] met Berlin ARDS criteria and 908 [73.2%] did not). At baseline, tidal volume was 6.9 ± 1.1 mL/kg predicted body weight, PEEP 8.4 ± 3.1 cm H2O, Fio2 0.63 ± 0.22, and plateau pressure 21.5 ± 5.4 cm H2O. ARDS patients received higher Fio2 and PEEP than non-ARDS (0.75 ± 0.22 vs 0.59 ± 0.20 cm H2O and 10.3 ± 3.4 vs 7.7 ± 2.6 cm H2O, respectively [p < 0.0001]). Adjunctive therapies were rarely used in non-ARDS patients. Patients without ARDS had higher ventilator-free days than ARDS (12.2 ± 11.6 vs 9.3 ± 9.7 d; p < 0.001). All-cause ICU mortality was similar in AHRF with or without ARDS (34.8% [95% CI, 29.7-40.2] vs 35.5% [95% CI, 32.3-38.7]; p = 0.837). CONCLUSIONS: AHRF without ARDS is a very common syndrome in the ICU with a high mortality that requires specific studies into its epidemiology and ventilatory management. We found that the prevalence of ARDS was much lower than reported in recent observational studies.

Low-density lipoprotein cholesterol levels are associated with poor clinical outcomes in COVID-19.

BACKGROUND AND AIMS: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the sole causative agent of coronavirus infectious disease-19 (COVID-19). METHODS AND RESULTS: We performed a retrospective single-center study of consecutively admitted patients between March 1st and May 15th, 2020, with a definitive diagnosis of SARS-CoV-2 infection. The primary end-point was to evaluate the association of lipid markers with 30-days all-cause mortality in COVID-19. A total of 654 patients were enrolled, with an estimated 30-day mortality of 22.8% (149 patients). Non-survivors had lower total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-c) levels during the entire course of the disease. Both showed a significant inverse correlation with inflammatory markers and a positive correlation with lymphocyte count. In a multivariate analysis, LDL-c ≤ 69 mg/dl (hazard ratio [HR] 1.94; 95% confidence interval [CI] 1.14-3.31), C-reactive protein >88 mg/dl (HR 2.44; 95% CI, 1.41-4.23) and lymphopenia <1000 (HR 2.68; 95% CI, 1.91-3.78) at admission were independently associated with 30-day mortality. This association was maintained 7 days after admission. Survivors presented with complete normalization of their lipid profiles on short-term follow-up. CONCLUSION: Hypolipidemia in SARS-CoV-2 infection may be secondary to an immune-inflammatory response, with complete recovery in survivors. Low LDL-c serum levels are independently associated with higher 30-day mortality in COVID-19 patients.

MR- proADM to detect specific types of organ failure in infection.

BACKGROUND: Following the SEPSIS-3 consensus, detection of organ failure as assessed by the SOFA (Sequential Organ Failure Assessment) score, is mandatory to detect sepsis. Calculating SOFA outside of the Intensive Care Unit (ICU) is challenging. The alternative in this scenario, the quick SOFA, is very specific but less sensible. Biomarkers could help to detect the presence of organ failure secondary to infection either in ICU and non-ICU settings. MATERIALS AND METHODS: We evaluated the ability of four biomarkers (C-Reactive protein (CRP), lactate, mid-regional proadrenomedullin (MR-proADM) and procalcitonin (PCT)) to detect each kind of organ failure considered in the SOFA in 213 patients with infection, sepsis or septic shock, by using multivariate regression analysis and calculation of the area under the receiver operating curve (AUROC). RESULTS: In the multivariate analysis, MR-proADM was an independent predictor of five different failures (respiratory, coagulation, cardiovascular, neurological and renal). In turn, lactate predicted three (coagulation, cardiovascular and neurological) and PCT two (cardiovascular and renal). CRP did not predict any of the individual components of SOFA. The highest AUROCs were those of MR-proADM and PCT to detect cardiovascular (AUROC, CI95%): MR-proADM (0.82 [0.76-0.88]), PCT (0.81 [0.75-0.87] (P < .05) and renal failure: MR-proADM (0.87 [0.82-0.92]), PCT (0.81 [0.75-0.86]), (P < .05). None of the biomarkers tested was able to detect hepatic failure. CONCLUSIONS: In patients with infection, MR-proADM was the biomarker detecting the largest number of SOFA score components, with the exception of hepatic failure.

Transcriptomic depression of immunological synapse as a signature of ventilator-associated pneumonia.

BACKGROUND: Ventilator-associated pneumonia (VAP) is one of the most commonly encountered intensive care unit (ICU) acquired infections worldwide. The objective of the study was to identify the immune alteration occurring in patients suffering from VAP at the transcriptomic level and explore its potential use for clinical diagnoses of this disease. METHODS: We performed a prospective observational study in five medical ICUs. Immunological gene expression profiles in the blood of VAP patients were compared with those of controls by using whole transcriptome microarrays and droplet digital polymerase chain reaction (ddPCR) in the first 24 hours following diagnosis. RESULTS: VAP patients showed significantly lower expression levels of HLA-DOA, HLA-DMA, HLA-DMB, ICOS, ICOSLG, IL2RA, CD1, CD3, CD28 and CD40LG. The molecules coded by these genes participate of the immunological synapse. CD1C, CD40LG and ICOS showed the highest values of area under the receiver operating characteristic curve (AUROC) with a good balance between sensibility and specificity. CONCLUSIONS: Patients with VAP show a transcriptomic depression of genes participating of the immunological synapse. It takes a commonplace event, namely VAP, and highlights a quite significant underlying immune suppressive state. In effect this small study will change how we regard VAP, and proposes that we regard it as an infection in an immune compromised host, and that immunity has a central role for ICU acquired infections. This may in time change clinical practice, as it has profound implications for the role of protocolised care, or bundles, in the prevention of VAP. Quantifying the expression in blood of this genes using ddPCR could be a useful approach for the diagnosis of VAP.

A vascular endothelial growth factor receptor gene variant is associated with susceptibility to acute respiratory distress syndrome.

BACKGROUND: The acute respiratory distress syndrome (ARDS) is one of the main causes of mortality in adults admitted to intensive care units. Previous studies have demonstrated the existence of genetic variants involved in the susceptibility and outcomes of this syndrome. We aimed to identify novel genes implicated in sepsis-induced ARDS susceptibility. METHODS: We first performed a prioritization of candidate genes by integrating our own genomic data from a transcriptomic study in an animal model of ARDS and from the only published genome-wide association study of ARDS study in humans. Then, we selected single nucleotide polymorphisms (SNPs) from prioritized genes to conduct a case-control discovery association study in patients with sepsis-induced ARDS (n = 225) and population-based controls (n = 899). Finally, we validated our findings in an independent sample of 661 sepsis-induced ARDS cases and 234 at-risk controls. RESULTS: Three candidate genes were prioritized: dynein cytoplasmic-2 heavy chain-1, fms-related tyrosine kinase 1 (FLT1), and integrin alpha-1. Of those, a SNP from FLT1 gene (rs9513106) was associated with ARDS in the discovery study, with an odds ratio (OR) for the C allele of 0.76, 95% confidence interval (CI) 0.58-0.98 (p = 0.037). This result was replicated in an independent study (OR = 0.78, 95% CI = 0.62-0.98, p = 0.039), showing consistent direction of effects in a meta-analysis (OR = 0.77, 95% CI = 0.65-0.92, p = 0.003). CONCLUSIONS: We identified FLT1 as a novel ARDS susceptibility gene and demonstrated that integration of genomic data can be a valid procedure to identify novel susceptibility genes. These results contribute to previous firm associations and functional evidences implicating FLT1 gene in other complex traits that are mechanistically linked, through the key role of endothelium, to the pathophysiology of ARDS.

A Quantile Analysis of Plateau and Driving Pressures: Effects on Mortality in Patients With Acute Respiratory Distress Syndrome Receiving Lung-Protective Ventilation.

OBJECTIVES: The driving pressure (plateau pressure minus positive end-expiratory pressure) has been suggested as the major determinant for the beneficial effects of lung-protective ventilation. We tested whether driving pressure was superior to the variables that define it in predicting outcome in patients with acute respiratory distress syndrome. DESIGN: A secondary analysis of existing data from previously reported observational studies. SETTING: A network of ICUs. PATIENTS: We studied 778 patients with moderate to severe acute respiratory distress syndrome. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We assessed the risk of hospital death based on quantiles of tidal volume, positive end-expiratory pressure, plateau pressure, and driving pressure evaluated at 24 hours after acute respiratory distress syndrome diagnosis while ventilated with standardized lung-protective ventilation. We derived our model using individual data from 478 acute respiratory distress syndrome patients and assessed its replicability in a separate cohort of 300 acute respiratory distress syndrome patients. Tidal volume and positive end-expiratory pressure had no impact on mortality. We identified a plateau pressure cut-off value of 29 cm H2O, above which an ordinal increment was accompanied by an increment of risk of death. We identified a driving pressure cut-off value of 19 cm H2O where an ordinal increment was accompanied by an increment of risk of death. When we cross tabulated patients with plateau pressure less than 30 and plateau pressure greater than or equal to 30 with those with driving pressure less than 19 and driving pressure greater than or equal to 19, plateau pressure provided a slightly better prediction of outcome than driving pressure in both the derivation and validation cohorts (p < 0.0000001). CONCLUSIONS: Plateau pressure was slightly better than driving pressure in predicting hospital death in patients managed with lung-protective ventilation evaluated on standardized ventilator settings 24 hours after acute respiratory distress syndrome onset.

Superior accuracy of mid-regional proadrenomedullin for mortality prediction in sepsis with varying levels of illness severity.

BACKGROUND: The use of novel sepsis biomarkers has increased in recent years. However, their prognostic value with respect to illness severity has not been explored. In this work, we examined the ability of mid-regional proadrenomedullin (MR-proADM) in predicting mortality in sepsis patients with different degrees of organ failure, compared to that of procalcitonin, C-reactive protein and lactate. METHODS: This was a two-centre prospective observational cohort, enrolling severe sepsis or septic shock patients admitted to the ICU. Plasma biomarkers were measured during the first 12 h of admission. The association between biomarkers and 28-day mortality was assessed by Cox regression analysis and Kaplan-Meier curves. Patients were divided into three groups as evaluated by the Sequential Organ Failure Assessment (SOFA) score. The accuracy of the biomarkers for mortality was determined by area under the receiver operating characteristic curve (AUROC) analysis. RESULTS: A total of 326 patients with severe sepsis (21.7%) or septic shock (79.3%) were enrolled with a 28-day mortality rate of 31.0%. Only MR-proADM and lactate were associated with mortality in the multivariate analysis: hazard ratio 8.5 versus 3.4 (p < 0.001). MR-proADM showed the best AUROC for mortality prediction at 28 days in the analysis over the entire cohort (AUROC [95% CI] 0.79 [0.74-0.84]) (p < 0.001). When patients were stratified by the degree of organ failure, MR-proADM was the only biomarker to predict mortality in all severity groups (SOFA ≤ 6, SOFA = 7-12, and SOFA ≥ 13), AUROC [95% CI] of 0.75 [0.61-0.88], 0.74 [0.66-0.83] and 0.73 [0.59-0.86], respectively (p < 0.05). All patients with MR-proADM concentrations ≤0.88 nmol/L survived up to 28 days. In patients with SOFA ≤ 6, the addition of MR-proADM to the SOFA score increased the ability of SOFA to identify non-survivors, AUROC [95% CI] 0.70 [0.58-0.82] and 0.77 [0.66-0.88], respectively (p < 0.05 for both). CONCLUSIONS: The performance of prognostic biomarkers in sepsis is highly influenced by disease severity. MR-proADM accuracy to predict mortality is not affected by the degree of organ failure. Thus, it is a good candidate in the early identification of sepsis patients with moderate disease severity but at risk of mortality.

The original sins of clinical trials with intravenous immunoglobulins in sepsis.

Intravenous immunoglobulins (IVIGs) have not yet demonstrated robust evidence in the benefit for treatment of sepsis. In spite of multiple clinical trials performed with IVIG in sepsis, it remains an experimental therapy for this severe condition. Nonetheless, these trials do not address a number of potential confounding factors, concerning both the patient and the IVIG preparations, which could greatly affect the final result. To name a few, endogenous levels of immunoglobulin isotypes and subclasses are not assessed prior to treatment. The presence/absence of patient antibodies against the microorganism(s) causing sepsis is not evaluated. The accuracy of antibiotic prescription is not included as an adjusting variable. The degree of patient immunosuppression (previous or induced by sepsis) is not documented. In turn, the concentration and antimicrobial specificities of the antibodies contained in the batches of IVIG are not assessed. Neither the pharmacokinetics of IVIG nor its potential immunomodulatory effects are evaluated. In addition, the concept of 'window of opportunity' for IVIG administration following diagnosis of sepsis is not considered. In conclusion, addressing these factors could help to individualise treatment with IVIG for sepsis, which could enhance the opportunities of this drug to show benefits in terms of survival in this severe condition.

IgM levels in plasma predict outcome in severe pandemic influenza.

BACKGROUND: Little is known on the participation of immunoglobulin isotypes and subclasses in the pathogenesis of the severe disease caused by the pandemic influenza virus (influenza A(H1N1)pdm09). OBJECTIVES: (1) To evaluate the association between plasma levels of IgG1, IgG2, IgG3, IgG4, IgA, IgM, IgE and outcome in patients with severe pandemic influenza. (2) To evaluate the association between immunoglobulin and cytokine levels in these patients. STUDY DESIGN: 40 critically ill patients with community acquired pneumonia and influenza A(H1N1)pdm09 infection were recruited from November 2010 to February 2011. Plasma samples were collected during the first 24h following admission to the ICU. Immunoglobulins and 17 major cytokines were profiled in plasma. RESULTS: 15 patients died (37.5%). When the association between clinical variables and prognosis was assessed, prior immunosuppression, APACHE II score, levels of IgG2 and levels of IgM were associated with outcome in a univariate Cox regression analysis. Kaplan Meier analysis showed that patients with levels of IgG2 and IgM < 59 and<58 mg/dl respectively died earlier. Multivariate Cox regression analysis showed that APACHE II score and levels of IgM were the best predictors of outcome, being levels of IgM a protective factor against mortality. IgM was the immunoglobulin showing the largest number of negative correlations with cytokine levels. CONCLUSIONS: Our results support a central role of IgM in preventing uncontrolled inflammatory response and mortality in severe pandemic influenza. Early assessment of IgM could contribute to guide clinical decisions in these patients.