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.

[The Bayes factor in the analysis of mechanical power in patients with severe respiratory failure due to SARS-CoV-2]. / El método del factor de Bayes en el análisis de la energía mecánica en pacientes con insuficiencia respiratoria grave por SARS-CoV-2.

Objective: To specify the degree of probative force of the statistical hypotheses in relation to mortality at 28 days and the threshold value of 17 J/min mechanical power (MP) in patients with respiratory failure secondary to SARS-CoV-2. Design: Cohort study, longitudinal, analytical. Setting: Intensive care unit of a third level hospital in Spain. Patients: Patients admitted for SARS-CoV-2 infection with admission to the ICU between March 2020 and March 2022. Interventions: Bayesian analysis with the beta binomial model. Main variables of interest: Bayes factor, mechanical power. Results: A total of 253 patients were analyzed. Baseline respiratory rate (BF10: 3.83 × 106), peak pressure value (BF10: 3.72 × 1013) and neumothorax (BF10: 17,663) were the values most likely to be different between the two groups of patients compared. In the group of patients with MP < 17 J/min, a BF10 of 12.71 and a BF01 of 0.07 were established with an 95%CI of 0.27-0.58. For the group of patients with MP ≥ 17 J/min the BF10 was 36,100 and the BF01 of 2.77e-05 with an 95%CI of 0.42-0.72. Conclusions: A MP ≥ 17 J/min value is associated with extreme evidence with 28-day mortality in patients requiring MV due to respiratory failure secondary to SARS-CoV-2 disease.

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.

Duration of the first prone positioning maneuver and its association with 90-day mortality in patients with acute respiratory failure due to COVID-19: A retrospective study of time terciles.

OBJECTIVE: To investigate the association between the duration of the first prone positioning maneuver (PPM) and 90-day mortality in patients with C-ARDS. DESIGN: Retrospective, observational, and analytical study. SETTING: COVID-19 ICU of a tertiary hospital. PATIENTS: Adults over 18 years old, with a confirmed diagnosis of SARS-CoV-2 disease requiring PPM. INTERVENTIONS: Multivariable analysis of 90-day survival. MAIN VARIABLES OF INTEREST: Duration of the first PPM, number of PPM sessions, 90-day mortality. RESULTS: 271 patients undergoing PPM were analyzed: first tertile (n = 111), second tertile (n = 95) and third tertile (n = 65). The results indicated that the median duration of PDP was 14 h (95% CI: 10-16 h) in the first tertile, 19 h (95% CI: 18-20 h) in the second tertile and 22 h (95% CI: 21-24 h) in the third tertile. Comparison of survival curves using the Logrank test did not reach statistical significance (p = 0.11). Cox Regression analysis showed an association between the number of pronation sessions (patients receiving between 2 and 5 sessions (HR = 2.19; 95% CI: 1.07-4.49); and those receiving more than 5 sessions (HR = 6.05; 95% CI: 2.78-13.16) and 90-day mortality. CONCLUSIONS: while the duration of PDP does not appear to significantly influence 90-day mortality, the number of pronation sessions is identified as a significant factor associated with an increased risk of mortality.

[Analysis of characteristics of elderly patients admitted to an intensive care unit during six waves of the SARS-CoV-2 pandemic: Implications for medical care]. / Análisis de las características de los pacientes mayores que ingresaron en una unidad de cuidados intensivos durante las 6 olas de la pandemia por SARS-CoV-2: implicaciones para la atención médica.

OBJECTIVE: To analyze the characteristics of seriously ill elderly patients during the six waves of the COVID-19 pandemic. METHOD: Retrospective, observational and analytical study of patients over 70 years of age admitted to the ICU (March-2020 to March-2022). Patients were categorized into three groups based on age: 70-74 years; 75-79 years; and >80 years. A descriptive and comparative analysis of the sample was initially performed; and a 28-, 60- and 90-day survival analysis using the Kaplan-Meier method. Multivariate survival analysis was performed by fitting a Cox model. RESULTS: Of 301 patients, the lowest number of admissions occurred during the first wave (20 (6%)), compared to the wave with the highest number of admissions: the sixth wave (76 (25%)). The survival curves at 28 days, 60 days and 90 days showed a higher probability of survival in the younger age groups (P<.01 and P=.01, respectively). Troponin at admission (per unit, ng/l) showed a significant association with 28- and 60-day mortality (HR: 1.00; 95% CI: 1.00-1.01; P<.05). Taking the 1st wave of the pandemic as a reference, admission in the 3rd wave behaved as a protective factor against mortality at 28 and 60 days of follow-up (HR: 0.18; 95% CI: 0.02-0.64; P<.05; HR: 0.13; 95% CI: 0.02-0.64; P<.05, respectively). CONCLUSIONS: The time of admission and biomarkers, such as troponin, constitute prognostic markers independent of age in the elderly population.

The Bayes factor in the analysis of mechanical power in patients with severe respiratory failure due to SARS-CoV-2.

OBJECTIVE: To specify the degree of probative force of the statistical hypotheses in relation to mortality at 28 days and the threshold value of 17 J/min mechanical power (MP) in patients with respiratory failure secondary to SARS-CoV-2. DESIGN: Cohort study, longitudinal, analytical. SETTING: Intensive care unit of a third level hospital in Spain. PATIENTS: Patients admitted for SARS-CoV-2 infection with admission to the ICU between March 2020 and March 2022. INTERVENTIONS: Bayesian analysis with the beta binomial model. MAIN VARIABLES OF INTEREST: Bayes factor, mechanical power. RESULTS: A total of 253 patients were analyzed. Baseline respiratory rate (BF10: 3.83 × 106), peak pressure value (BF10: 3.72 × 1013) and neumothorax (BF10: 17,663) were the values most likely to be different between the two groups of patients compared. In the group of patients with MP < 17 J/min, a BF10 of 12.71 and a BF01 of 0.07 were established with an 95%CI of 0.27-0.58. For the group of patients with MP ≥ 17 J/min the BF10 was 36,100 and the BF01 of 2.77e-05 with an 95%CI of 0.42-0.72. CONCLUSIONS: A MP ≥ 17 J/min value is associated with extreme evidence with 28-day mortality in patients requiring MV due to respiratory failure secondary to SARS-CoV-2 disease.

[Retrospective study of the effect of vaccination against SARS-CoV-2 in seriously ill patients admitted to an intensive care unit]. / Estudio retrospectivo del efecto de la vacunación frente al SARS-CoV-2 en enfermos graves que ingresan en una unidad de cuidados intensivos.

BACKGROUND AND OBJECTIVE: Our study aims to compare the clinical and epidemiological characteristics, length of stay in the ICU, and mortality rates of COVID-19 patients admitted to the ICU who are fully vaccinated, partially vaccinated, or unvaccinated. PATIENTS AND METHODS: Retrospective cohort study (March 2020-March 2022). Patients were classified into unvaccinated, fully vaccinated, and partially vaccinated groups. We initially performed a descriptive analysis of the sample, a multivariable survival analysis adjusting for a Cox regression model, and a 90-day survival analysis using the Kaplan-Meier method for the death time variable. RESULTS: A total of 894 patients were analyzed: 179 with full vaccination, 32 with incomplete vaccination, and 683 were unvaccinated. Vaccinated patients had a lower incidence (10% vs. 21% and 18%) of severe ARDS. The survival curve did not show any differences in the probability of surviving for 90 days among the studied groups (p = 0.898). In the Cox regression analysis, only the need for mechanical ventilation during admission and the value of LDH (per unit of measurement) in the first 24 hours of admission were significantly associated with mortality at 90 days (HR: 5.78; 95% CI: 1.36-24.48); p = 0.01 and HR: 1.01; 95% CI: 1.00-1.02; p = 0.03, respectively. CONCLUSIONS: Patients with severe SARS-CoV-2 disease who are vaccinated against COVID-19 have a lower incidence of severe ARDS and mechanical ventilation than unvaccinated patients.

Key Factors Associated With Pulmonary Sequelae in the Follow-Up of Critically Ill COVID-19 Patients.

INTRODUCTION: Critical COVID-19 survivors have a high risk of respiratory sequelae. Therefore, we aimed to identify key factors associated with altered lung function and CT scan abnormalities at a follow-up visit in a cohort of critical COVID-19 survivors. METHODS: Multicenter ambispective observational study in 52 Spanish intensive care units. Up to 1327 PCR-confirmed critical COVID-19 patients had sociodemographic, anthropometric, comorbidity and lifestyle characteristics collected at hospital admission; clinical and biological parameters throughout hospital stay; and, lung function and CT scan at a follow-up visit. RESULTS: The median [p25-p75] time from discharge to follow-up was 3.57 [2.77-4.92] months. Median age was 60 [53-67] years, 27.8% women. The mean (SD) percentage of predicted diffusing lung capacity for carbon monoxide (DLCO) at follow-up was 72.02 (18.33)% predicted, with 66% of patients having DLCO<80% and 24% having DLCO<60%. CT scan showed persistent pulmonary infiltrates, fibrotic lesions, and emphysema in 33%, 25% and 6% of patients, respectively. Key variables associated with DLCO<60% were chronic lung disease (CLD) (OR: 1.86 (1.18-2.92)), duration of invasive mechanical ventilation (IMV) (OR: 1.56 (1.37-1.77)), age (OR [per-1-SD] (95%CI): 1.39 (1.18-1.63)), urea (OR: 1.16 (0.97-1.39)) and estimated glomerular filtration rate at ICU admission (OR: 0.88 (0.73-1.06)). Bacterial pneumonia (1.62 (1.11-2.35)) and duration of ventilation (NIMV (1.23 (1.06-1.42), IMV (1.21 (1.01-1.45)) and prone positioning (1.17 (0.98-1.39)) were associated with fibrotic lesions. CONCLUSION: Age and CLD, reflecting patients' baseline vulnerability, and markers of COVID-19 severity, such as duration of IMV and renal failure, were key factors associated with impaired DLCO and CT abnormalities.

Prognostic implications of comorbidity patterns in critically ill COVID-19 patients: A multicenter, observational study.

Background: The clinical heterogeneity of COVID-19 suggests the existence of different phenotypes with prognostic implications. We aimed to analyze comorbidity patterns in critically ill COVID-19 patients and assess their impact on in-hospital outcomes, response to treatment and sequelae. Methods: Multicenter prospective/retrospective observational study in intensive care units of 55 Spanish hospitals. 5866 PCR-confirmed COVID-19 patients had comorbidities recorded at hospital admission; clinical and biological parameters, in-hospital procedures and complications throughout the stay; and, clinical complications, persistent symptoms and sequelae at 3 and 6 months. Findings: Latent class analysis identified 3 phenotypes using training and test subcohorts: low-morbidity (n=3385; 58%), younger and with few comorbidities; high-morbidity (n=2074; 35%), with high comorbid burden; and renal-morbidity (n=407; 7%), with chronic kidney disease (CKD), high comorbidity burden and the worst oxygenation profile. Renal-morbidity and high-morbidity had more in-hospital complications and higher mortality risk than low-morbidity (adjusted HR (95% CI): 1.57 (1.34-1.84) and 1.16 (1.05-1.28), respectively). Corticosteroids, but not tocilizumab, were associated with lower mortality risk (HR (95% CI) 0.76 (0.63-0.93)), especially in renal-morbidity and high-morbidity. Renal-morbidity and high-morbidity showed the worst lung function throughout the follow-up, with renal-morbidity having the highest risk of infectious complications (6%), emergency visits (29%) or hospital readmissions (14%) at 6 months (p<0.01). Interpretation: Comorbidity-based phenotypes were identified and associated with different expression of in-hospital complications, mortality, treatment response, and sequelae, with CKD playing a major role. This could help clinicians in day-to-day decision making including the management of post-discharge COVID-19 sequelae. Funding: ISCIII, UNESPA, CIBERES, FEDER, ESF.

ICU-Acquired Pneumonia Is Associated with Poor Health Post-COVID-19 Syndrome.

BACKGROUND: Some patients previously presenting with COVID-19 have been reported to develop persistent COVID-19 symptoms. While this information has been adequately recognised and extensively published with respect to non-critically ill patients, less is known about the incidence and factors associated with the characteristics of persistent COVID-19. On the other hand, these patients very often have intensive care unit-acquired pneumonia (ICUAP). A second infectious hit after COVID increases the length of ICU stay and mechanical ventilation and could have an influence on poor health post-COVID 19 syndrome in ICU-discharged patients. METHODS: This prospective, multicentre, and observational study was carrid out across 40 selected ICUs in Spain. Consecutive patients with COVID-19 requiring ICU admission were recruited and evaluated three months after hospital discharge. RESULTS: A total of 1255 ICU patients were scheduled to be followed up at 3 months; however, the final cohort comprised 991 (78.9%) patients. A total of 315 patients developed ICUAP (97% of them had ventilated ICUAP). Patients requiring invasive mechanical ventilation had more persistent post-COVID-19 symptoms than those who did not require mechanical ventilation. Female sex, duration of ICU stay, development of ICUAP, and ARDS were independent factors for persistent poor health post-COVID-19. CONCLUSIONS: Persistent post-COVID-19 symptoms occurred in more than two-thirds of patients. Female sex, duration of ICU stay, development of ICUAP, and ARDS all comprised independent factors for persistent poor health post-COVID-19. Prevention of ICUAP could have beneficial effects in poor health post-COVID-19.

Choice of fluids in the perioperative period of kidney transplantation. / Elección de fluidos en el periodo perioperatorio del trasplante renal.

Normal saline has traditionally been the resuscitation fluid of choice in the perioperative period of kidney transplantation over balanced potassium solutions. However, the problems arising from hyperchloraemia triggered by the infusion of normal saline have led to studies being conducted that compare this solution with balanced solutions. From this narrative review it can be concluded that the use of balanced crystalloids containing potassium in the perioperative period of kidney transplantation can be considered safe. These solutions do not affect serum potassium levels any more than normal saline, whilst maintaining a better acid-base balance in these patients.