Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort.

Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates. Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy ≥10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups. Initially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016). In this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk

Pancreatitis aguda desde la perspectiva de la medicina intensiva y crítica: Antibioterapia profiláctica, argumentos a favor

La pancreatitis aguda necrosante es una forma grave de pancreatitis aguda, cuyo tratamiento temprano consiste en la combinación de tratamiento médico intensivo y prevención de la infección con profilaxis antibiótica, ya que la infección de la necrosis aumenta la mortalidad de forma significativa. El mecanismo principal de infección bacteriana es la translocación del colon. La infección de la necrosis pancreática se desarrolla en el 29% de casos y suele presentarse a partir de la tercera semana. Los microorganismos aislados con más frecuencia son: bacilos gramnegativos (BGN): 75%, cocos grampositivos (CGP): 53%, Candida: 8%, anaerobios: 8% y mixtos: 54 %. El diagnóstico se realiza mediante cultivo o tinción de Gram del material aspirado mediante la punción aspiración con aguja fina de la zona pancreática sospechosa de infección clínica, guiada por ecografía o tomografía axial computarizada (TAC). El beneficio del tratamiento antibiótico temprano está basado en una creciente evidencia científica, lo que obliga a modificar el tratamiento en estos enfermos, mediante el inicio inmediato de la antibioterapia contínua durante 14 días o hasta que persistan las complicaciones. Esto hace posible retardar la intervención quirúrgica y hacerla en condiciones óptimas. Los fármacos de elección para el tratamiento y profilaxis de las infecciones pancreáticas son el imipenem y las quinolonas en combinación con el metronidazol, aunque recientemente se ha demostrado que el imipenem es superior a las quinolonas. Retardan la intervención quirúrgica y permiten hacerla en condiciones óptimas. Sin embargo, para determinar exactamente la elección del antibiótico, son necesarios estudios prospectivos, controlados, aleatorios y ciegos

Respuesta al soporte nutricional de una población de pacientes críticos: diferencias entre pacientes médicos y quirúrgicos Nutritional support response in critically ill patients: differences between medical and surgical patients

Objetivo: Evaluación de la respuesta nutricional de un grupo de pacientes críticos, así como el análisis de las diferencias en la respuesta al soporte nutricional, entre pacientes médicos y quirúrgicos. Métodos: Estudio retrospectivo durante un año, incluyendo los pacientes críticos con nutrición artificial durante 7 días. Se realizaron tres controles bioquímicos nutricionales a lo largo de la primera semana, que incluían albúmina, prealbúmina, transferrina, colesterol y electrolitos. Se recogieron, además: índice de riesgo nutricional, edad, sexo, peso, talla, APACHE, retraso del inicio del soporte nutricional, vía de acceso, aporte calórico teórico y real, enfermo médico o quirúrgico, estancia, duración de catéter venoso central, sonda urinaria y/o ventilación mecánica, incidencia y densidad de incidencia de infecciones nosocomiales. Resultados: 63 pacientes estudiados, 30 médicos (47%) y 33 quirúrgicos/traumáticos (53%) siendo la utilización de NE superior en médicos (16/30, 53% vs 5/33, 15%), la de NP en quirúrgicos (25/33, 76%) y la mixta similar en ambos (5 médicos y 3 quirúrgicos) (p = 0,001). No hubo diferencias entre pacientes médicos y quirúrgicos en: aporte calórico y nitrogenado teóricos ni reales, APACHE, retraso en inicio de nutrición, valores de fósforo, magnesio y glucosa, mortalidad e incidencia de infecciones nosocomiales. Tampoco en días de estancia y ventilación mecánica, aunque tendieron a ser menores en pacientes quirúrgicos. Los parámetros bioquímicos iniciales de ambos grupos mostraron diferencias, siendo peores en los enfermos quirúrgicos. Estos presentaron, en el periodo de estudio, un mantenimiento de la albúmina y mejoras del resto de los parámetros, mientras que los médicos mostraron una caída de la albúmina y transferrina, un mantenimiento de la prealbúmina y discreta mejoría del colesterol. Conclusiones: Hemos observado un mayor uso de la NP en pacientes quirúrgicos, que presentan peores valores bioquímicos nutricionales iniciales, que responden mejor al soporte nutricional y que presentan una tendencia a una menor estancia y una menor duración de ventilación mecánica frente a los pacientes médicos. No hemos observado diferencias en mortalidad ni en infección nosocomial.Objective: To assess the nutritional response of a group of critically ill patients, as well as the differences in the response to nutritional support between medical and surgical patients. Methods: One-year long retrospective study including critically ill patients on artificial nutrition for 7 days. Throughout the first week, three nutritional biochemical controls were done that included albumin, prealbumin, transferrin, cholesterol, and electrolytes. Other data gathered were: nutritional risk index, age, gender, weight, height, APACHE, delay of onset of nutritional support, access route, predicted and real caloric intake, medical or surgical patient, hospital stay, duration of the central venous catheter, urinary tube, and/or mechanical ventilation, incidence and density of incidence of nosocomial infections. Results: Sixty-three patients were studied, 30 (47%) medical and 33 (53%) surgical/trauma patients, with a usage of EN higher among medical patients (16/30, 53% vs. 5/33, 15%), PN higher among surgical patients (25/33, 76%), and mixed nutrition similar in both groups (5 medical and 3 surgical patients) (p = 0.001). There were no differences between medical and surgical patients regarding: both predicted and real caloric and nitrogenous intake, APACHE, delay of onset of nutrition, phosphorus, magnesium or glucose levels, mortality and incidence of nosocomial infections. There were no differences either in hospital stay or use of mechanical ventilation, although these tended to be lower in surgical patients. The baseline biochemical parameters did not show differences between both groups, although they were worse among surgical patients. These patients presented during the study period steady albumin levels with improvement in the remaining parameters, whereas medical patients showed a decrease in albumin and transferrin levels, steady prealbumin levels, and slightly improvement in cholesterol levels. Conclusions: We have observed higher usage of PN among surgical patients, which showed worse baseline nutritional biochemical parameters and responded better to nutritional support and having a trend towards shorter hospital stay and lower mechanical ventilation use than medical patients. We have not observed differences regarding the mortality or nosocomial infection

Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort

BACKGROUND Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates. METHODS Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy ≥10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups. RESULTS Initially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016). CONCLUSION In this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk

Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort

Background Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates. Methods Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy >= 10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups. Results Initially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016). Conclusion In this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk

Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort.

BACKGROUND Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates. METHODS Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy ≥10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups. RESULTS Initially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016). CONCLUSION In this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk

Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients

Background: Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care. Methods: We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary out- come the increase or decrease in patients’ Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort. Results: The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model (0.86 vs . 0.69, P < 0.01 [paired t -test with 95% confidence interval]). Conclusions: The XGBoost model predicted the change in SOFA score in critically ill COVID-19 patients admitted to the ICU and can guide clinical decision support systems (CDSSs) aimed at optimizing available resources

Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort

Background: Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is wide‑ spread. While the risks and benefts of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefts of diferent respiratory sup‑ port strategies, employed in intensive care units during the frst months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates. Methods: Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclas‑ sifed into standard oxygen therapy ≥10 L/min (SOT), high-fow oxygen therapy (HFNC), noninvasive positive-pressur

Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients

Background: Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care. Methods: We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary outcome the increase or decrease in patients’ Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort. Results: The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model (0.86 vs. 0.69, P &lt; 0.01 [paired t-test with 95% confidence interval]). Conclusions: The XGBoost model predicted the change in SOFA score in critically ill COVID-19 patients admitted to the ICU and can guide clinical decision support systems (CDSSs) aimed at optimizing available resources