Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2022 critically ill patients with COVID-19 in Spain.

BACKGROUND: The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. METHODS: Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 ICUs in Spain. The objective was to utilize an unsupervised clustering analysis to derive clinical COVID-19 phenotypes and to analyze patient's factors associated with mortality risk. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves. RESULTS: The database included a total of 2022 patients (mean age 64 [IQR 5-71] years, 1423 (70.4%) male, median APACHE II score (13 [IQR 10-17]) and SOFA score (5 [IQR 3-7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the A (mild) phenotype (537; 26.7%) included older age (< 65 years), fewer abnormal laboratory values and less development of complications, B (moderate) phenotype (623, 30.8%) had similar characteristics of A phenotype but were more likely to present shock. The C (severe) phenotype was the most common (857; 42.5%) and was characterized by the interplay of older age (> 65 years), high severity of illness and a higher likelihood of development shock. Crude ICU mortality was 20.3%, 25% and 45.4% for A, B and C phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications. CONCLUSION: The presented machine learning model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a "one-size-fits-all" model in practice.

Applicability of an unsupervised cluster model developed on first wave COVID-19 patients in second/third wave critically ill patients.

OBJECTIVE: To validate the unsupervised cluster model (USCM) developed during the first pandemic wave in a cohort of critically ill patients from the second and third pandemic waves. DESIGN: Observational, retrospective, multicentre study. SETTING: Intensive Care Unit (ICU). PATIENTS: Adult patients admitted with COVID-19 and respiratory failure during the second and third pandemic waves. INTERVENTIONS: None. MAIN VARIABLES OF INTEREST: Collected data included demographic and clinical characteristics, comorbidities, laboratory tests and ICU outcomes. To validate our original USCM, we assigned a phenotype to each patient of the validation cohort. The performance of the classification was determined by Silhouette coefficient (SC) and general linear modelling. In a post-hoc analysis we developed and validated a USCM specific to the validation set. The model's performance was measured using accuracy test and area under curve (AUC) ROC. RESULTS: A total of 2330 patients (mean age 63 [53-82] years, 1643 (70.5%) male, median APACHE II score (12 [9-16]) and SOFA score (4 [3-6]) were included. The ICU mortality was 27.2%. The USCM classified patients into 3 clinical phenotypes: A (n = 1206 patients, 51.8%); B (n = 618 patients, 26.5%), and C (n = 506 patients, 21.7%). The characteristics of patients within each phenotype were significantly different from the original population. The SC was -0.007 and the inclusion of phenotype classification in a regression model did not improve the model performance (0.79 and 0.78 ROC for original and validation model). The post-hoc model performed better than the validation model (SC -0.08). CONCLUSION: Models developed using machine learning techniques during the first pandemic wave cannot be applied with adequate performance to patients admitted in subsequent waves without prior validation.

Detection of SARS-CoV-2 RNA in serum is associated with increased mortality risk in hospitalized COVID-19 patients.

COVID-19 has overloaded national health services worldwide. Thus, early identification of patients at risk of poor outcomes is critical. Our objective was to analyse SARS-CoV-2 RNA detection in serum as a severity biomarker in COVID-19. Retrospective observational study including 193 patients admitted for COVID-19. Detection of SARS-CoV-2 RNA in serum (viremia) was performed with samples collected at 48-72 h of admission by two techniques from Roche and Thermo Fischer Scientific (TFS). Main outcome variables were mortality and need for ICU admission during hospitalization for COVID-19. Viremia was detected in 50-60% of patients depending on technique. The correlation of Ct in serum between both techniques was good (intraclass correlation coefficient: 0.612; p < 0.001). Patients with viremia were older (p = 0.006), had poorer baseline oxygenation (PaO2/FiO2; p < 0.001), more severe lymphopenia (p < 0.001) and higher LDH (p < 0.001), IL-6 (p = 0.021), C-reactive protein (CRP; p = 0.022) and procalcitonin (p = 0.002) serum levels. We defined "relevant viremia" when detection Ct was < 34 with Roche and < 31 for TFS. These thresholds had 95% sensitivity and 35% specificity. Relevant viremia predicted death during hospitalization (OR 9.2 [3.8-22.6] for Roche, OR 10.3 [3.6-29.3] for TFS; p < 0.001). Cox regression models, adjusted by age, sex and Charlson index, identified increased LDH serum levels and relevant viremia (HR = 9.87 [4.13-23.57] for TFS viremia and HR = 7.09 [3.3-14.82] for Roche viremia) as the best markers to predict mortality. Viremia assessment at admission is the most useful biomarker for predicting mortality in COVID-19 patients. Viremia is highly reproducible with two different techniques (TFS and Roche), has a good consistency with other severity biomarkers for COVID-19 and better predictive accuracy.

Valoración ética de la craneoplastia con vendaje compresivo como forma de limitación de tratamientos de soporte vital / Valoração ética da cranioplastia com curativo compressivo como forma de limitação de tratamentos de suporte vital / Ethical value of cranioplasty with oppressive binder as a way of limiting life support treatments

Este artículo analiza, desde una postura crítica, la utilización de la craneoplastia de compresión con vendaje como método de limitación de tratamiento de soporte vital (LTSV). Con esta técnica activa, algunos autores han propuesto provocar la muerte encefálica, posibilitando la donación de órganos. Al contrastar este procedimiento con las recomendaciones del documento de consenso sobre el tratamiento al final de la vida del paciente crítico, elaborado por el grupo de bioética de la SEMICYUC, se comprueba que los medios y fines de esta técnica no encajan con las actuaciones propias de la LTSV, que se basan en la retirada de medios de soporte vital o en su no inicio, al considerar dichos medios desproporcionados o extraordinarios en algunos casos, evitando así la obstinación terapéutica. La definición de LTSV permite clarificar los límites en los que, de un modo éticamente correcto y consensuado, las actuaciones al final de la vida se circunscriben a los fines de la medicina, evitando la sospecha de que dichas actuaciones puedan ser malinterpretadas como justificación para una obtención de órganos abusiva. El artículo concluye que la provocación directa de la muerte encefálica mediante la técnica de craneoplastia con vendaje no parece cumplir los criterios propios de la LTSV.

This article analyzes, from a critical perspective, the use of cranioplasty with oppressive binder as a method to limit life support treatment (LLST). Some authors have proposed that this active technique provokes encephalic death, allowing organ donation. Contrasting this procedure with the recommendations of the consent document about treatment of critical patients at the end of life, elaborated by the bioethics group of SEMICYUC, it is shown that the means and ends of this technique do not match with the proper actions of LLST, based on the withdrawal of life support means or in not starting them, considering such means disproportionate or extraordinary in some cases, thus avoiding the therapeutic obstinacy. The definition of LLST allows to clarify the limits in which, in a way ethically fair and with a consensus, the acts at the end of life are included in the medical goals, avoiding the suspicion that these acts may be misinterpreted as justifying an abusive extraction of organs. This article concludes that the direct provocation of encephalic death by the technique of cranioplasty with binder does not appear to fulfill the criteria proper of LLST.

Este artigo analisa, a partir de uma postura crítica, a utilização da cranioplastia de compressão com curativo como método de limitação de tratamento de suporte vital (LTSV). Com esta técnica ativa, alguns autores têm proposto provocar a morte encefálica, possibilitando a doação de órgãos. Ao contrastar este procedimento com as recomendações do documento de consenso sobre o tratamento do final de vida do paciente crítico, elaborado pelo grupo de bioética da SEMICYUC, se comprova que os meios e fins desta técnica não encaixam com as atuações próprias da LTSV, que se baseiam na retirada de meios de suporte vital ou em seu não início, ao considerar os ditos meios desproporcionados ou extraordinários em alguns casos, evitando assim a obstinação terapêutica. A definição de LTSV permite esclarecer os limites nos quais, de um modo eticamente correto e aceito, as atuações ao final da vida se circunscrevem às finalidades da medicina, evitando a suspeita de que ditas atuações podem ser mal interpretadas como justificativa para uma obtenção de órgãos abusiva. O artigo conclui que a provocação direta da morte encefálica mediante a técnica da cranioplastia com curativo não parece cumprir os critérios próprios da LTSV.