Higher Simplified Acute Physiology Score Research Articles

Patient characteristics associated with posttraumatic stress symptoms in intensive care unit survivors during a one-year follow-up: A multicenter study

BackgroundIntensive care unit (ICU) patients are at risk of suffering from posttraumatic stress symptoms (PTSS) after ICU survival. ObjectivesTo describe the prevalence of high levels of PTSS the first year after ICU admission. Further, to identify specific combinations of patient characteristics (latent classes based on pre-ICU data, demographics, and clinical characteristics), and to investigate possible associations among these classes and PTSS at 3, 6, and 12 months after ICU admission. MethodsSelf-reported PTSS were measured with Impact of Event Scale-Revised (IES-R). PTSS and possible predictive factors (pre-ICU data, demographics, and clinical characteristics) were analyzed using descriptive statistics, latent class analysis, and linear mixed model for repeated measures. ResultsHigh PTSS levels (IES-R ≥ 33) were reported by 14.9 % (95 % confidence interval [CI] [10.0; 21.1]), 16.7 % (95 % CI [11.5; 23.1]), and 18.4 % (95 % CI [12.9; 25.0]) of patients (sample 1, n = 174) at 3, 6, and 12 months, respectively. Three latent classes were identified (sample 2, n = 417). PTSS were significantly associated with class 2 (male with longer hospital stay) at 6 months and class 3 (age≥70, lower level of education, higher Simplified Acute Physiology Score, being mechanically ventilated) at all three measurement times. ConclusionsThe prevalence of high levels of PTSS is the greatest 12 months after ICU admission. Health professionals can use this information to be aware of specific groups of ICU patients reporting PTSS during the first year and follow up on these.

Construction and evaluation of short-term and long-term mortality risk prediction model for patients with sepsis based on MIMIC-IV database.

Given the high incidence and mortality rate of sepsis, early identification of high-risk patients and timely intervention are crucial. However, existing mortality risk prediction models still have shortcomings in terms of operation, applicability, and evaluation on long-term prognosis. This study aims to investigate the risk factors for death in patients with sepsis, and to construct the prediction model of short-term and long-term mortality risk. Patients meeting sepsis 3.0 diagnostic criteria were selected from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and randomly divided into a modeling group and a validation group at a ratio of 7꞉3. Baseline data of patients were analyzed. Univariate Cox regression analysis and full subset regression were used to determine the risk factors of death in patients with sepsis and to screen out the variables to construct the prediction model. The time-dependent area under the curve (AUC), calibration curve, and decision curve were used to evaluate the differentiation, calibration, and clinical practicability of the model. A total of 14 240 patients with sepsis were included in our study. The 28-day and 1-year mortality were 21.45% (3 054 cases) and 36.50% (5 198 cases), respectively. Advanced age, female, high sepsis-related organ failure assessment (SOFA) score, high simplified acute physiology score II (SAPS II), rapid heart rate, rapid respiratory rate, septic shock, congestive heart failure, chronic obstructive pulmonary disease, liver disease, kidney disease, diabetes, malignant tumor, high white blood cell count (WBC), long prothrombin time (PT), and high serum creatinine (SCr) levels were all risk factors for sepsis death (all P<0.05). Eight variables, including PT, respiratory rate, body temperature, malignant tumor, liver disease, septic shock, SAPS II, and age were used to construct the model. The AUCs for 28-day and 1-year survival were 0.717 (95% CI 0.710 to 0.724) and 0.716 (95% CI 0.707 to 0.725), respectively. The calibration curve and decision curve showed that the model had good calibration degree and clinical application value. The short-term and long-term mortality risk prediction models of patients with sepsis based on the MIMIC-IV database have good recognition ability and certain clinical reference significance for prognostic risk assessment and intervention treatment of patients.

Machine learning-based prediction of in-hospital mortality for critically ill patients with sepsis-associated acute kidney injury

Objectives This study aims to develop and validate a prediction model in-hospital mortality in critically ill patients with sepsis-associated acute kidney injury (SA-AKI) based on machine learning algorithms. Methods Patients who met the criteria for inclusion were identified in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and divided according to the validation (n = 2440) and development (n = 9756, 80%) queues. Ensemble stepwise feature selection method was used to screen for effective features. The prediction models of short-term mortality were developed by seven machine learning algorithms. Ten-fold cross-validation was used to verify the performance of the algorithm in the development queue. The area under the receiver operating characteristic curve (ROC-AUC) was used to evaluate the differentiation accuracy and performance of the prediction model in the validation queue. The best-performing model was interpreted by Shapley additive explanations (SHAP). Results A total of 12,196 patients were enrolled in this study. Eleven variables were finally chosen to develop the prediction model. The AUC of the random forest (RF) model was the highest value both in the Ten-fold cross-validation and evaluation (AUC: 0.798, 95% CI: 0.774–0.821). According to the SHAP plots, old age, low Glasgow Coma Scale (GCS) score, high AKI stage, reduced urine output, high Simplified Acute Physiology Score (SAPS II), high respiratory rate, low temperature, low absolute lymphocyte count, high creatinine level, dysnatremia, and low body mass index (BMI) increased the risk of poor prognosis. Conclusions The RF model developed in this study is a good predictor of in-hospital mortality for patients with SA-AKI in the intensive care unit (ICU), which may have potential applications in mortality prediction.

Association between chronic obstructive pulmonary disease and 28-day mortality in patients with sepsis: a retrospective study based on the MIMIC-III database

BackgroundSepsis is a common cause of mortality in critically ill patients, and chronic obstructive pulmonary disease (COPD) is one of the most common comorbidities in septic patients. However, the impact of COPD on patients with sepsis remained unclear. Therefore, the purpose of this study aimed to assess the effect of COPD on the prognosis of septic patients based on Medical Information Mart for Intensive Care (MIMIC-III) database.MethodsIn this retrospective study based on the (MIMIC)-III database version 1.4 (v1.4), we collected clinical data and 28-day all-cause mortality from patients with sepsis in intensive care unit (ICU) and these patients met the diagnostic criteria of Sepsis 3 on ICU admission between 2008 and 2012. International Classification of Diseases (ICD-9) (4660, 490, 4910, 4911, 49120, 49121, 4918, 4919, 4920, 4928, 494, 4940, 4941, 496) was used to identified COPD. We applied Kaplan–Meier analysis to compare difference of 28-day all-cause mortality between septic patients with and without COPD. Cox proportional-hazards model was applied to explore the risk factor associated with 28-day all-cause mortality in patients with sepsis.ResultsSix thousand two hundred fifty seven patients with sepsis were included in this study, including 955 (15.3%) patients with COPD and 5302 patients without COPD (84.7%). Compared with patients without COPD, patients with COPD were older (median: 73.5 [64.4, 82.0] vs 65.8 [52.9, 79.1], P < 0.001), had higher simplified acute physiology score II (SAPSII) (median: 40.0 [33.0, 49.0] vs 38.0 [29.0,47.0], P < 0.001) and greater proportion of mechanical ventilatory support (MV) (55.0% vs 48.9%, P = 0.001). In our study, septic patients with COPD had higher 28-day all-cause mortality (23.6% vs 16.4%, P < 0.001) than patients without COPD. After adjusting for covariates, the results showed that COPD was an independent risk factor for the 28-day all-cause mortality of patients with sepsis (HR 1.30, 95%CI: 1.12–1.50, P = 0.001).ConclusionsCOPD was an independent risk factor of 28-day all-cause mortality in septic patients. Clinically, septic patients with COPD should be given additional care.

Relationship between Nonhepatic Serum Ammonia Levels and Sepsis-Associated Encephalopathy: A Retrospective Cohort Study.

Nonhepatic hyperammonemia often occurs in patients with sepsis. Ammonia plays an essential role in the occurrence of hepatic encephalopathy. However, the relationship between nonhepatic serum ammonia levels and sepsis-associated encephalopathy (SAE) remains unclear. Thus, we aimed to evaluate the association between serum ammonia levels and patients with SAE. Data of critically ill adults with sepsis who were admitted to the intensive care unit were retrieved from the Medical Information Mart for Intensive Care IV (MIMIC IV) between 2008 and 2019 and retrospectively analyzed. Data of patients with sepsis patients and serum ammonia not related to acute or chronic liver disease were not included. Data from 720 patients with sepsis were included. SAE was found to have a high incidence (64.6%). After adjusting for other risk factors, a serum ammonia level of ≥45 μmol/L (odds ratio (OR): 3.508, 95% confidence interval (CI): 2.336-5.269, p < 0.001) was found to be an independent risk factor for patients with SAE; moreover, as the serum ammonia level increased, the hospital mortality of SAE gradually increased in a certain range (serum ammonia <150 μmol/L). Serum ammonia levels of ≥45 μmol/L were associated with higher Simplified Acute Physiology Score II and Sequential Organ Failure Assessment (SOFA) scores in patients with SAE. Besides, our study found that patients with SAE used opioid analgesics (OR:3.433, 95% CI: 1.360-8.669, p = 0.009) and the SOFA scores of patients with SAE (OR: 1.126, 95% CI: 1.062-1.194, p < 0.001) were significantly higher than those without SAE. Nonhepatic serum ammonia levels of ≥45 μmol/L evidently increased the incidence of SAE. Serum ammonia levels should be closely monitored in patients with sepsis.

Analysis of Nursing Staff Management for a Semi-intensive Pulmonology Unit During the COVID-19 Pandemic Using the Nursing Activities Score.

During the COVID-19 pandemic, a shortage of intensive care unit beds was encountered across Europe. Opening a semi-intensive pulmonary ward freed up intensive care unit beds. This study aimed to determine the appropriate nurse staffing level for a semi-intensive pulmonology unit (SIPU) for patients with COVID-19 and to identify factors associated with an increase in nursing workload in this type of unit. This was a retrospective study of the SIPU of the Erasme university clinics in Belgium. Nursing staff was determined with the Nursing Activities Score (NAS) during the second wave of COVID-19 in Belgium. During the study period, 59 patients were admitted to the SIPU, and a total of 416 NAS scores were encoded. The mean (±SD) NAS was 70.3% (±16.6%). Total NAS varied significantly depending on the reason for admission: respiratory distress (mean [SD] NAS, 71.6% [±13.9%]) or critical illness-related weakness (65.1% ± 10.9%). The items encoded were significantly different depending on the reason for admission. In multivariate analysis, body mass index > 30 (odds ratio [OR], 1.77; 95% confidence interval [CI], 1.07-3.30) and higher Simplified Acute Physiology Score II score (OR, 1.05; 95 CI, 1.02-1.11) were associated with higher NAS. Patients admitted via the emergency department (OR, 2.45; 95% CI, 1.15-5.22) had higher NAS. Patients on noninvasive ventilation (OR, 13.65; 95% CI, 3.76-49.5) and oxygen therapy (OR, 4.29; 95% CI, 1.27-14.48) had higher NAS. High peripheral venous oxygen saturation (OR, 0.86; 95% CI, 0.78-0.94) was a predictor of lower workload. A ratio of 2 nurses to 3 patients is necessary for SIPU care of patients with COVID-19. Factors associated with higher workload were high Simplified Acute Physiology Score II score, body mass index > 30, admission via emergency room, patients on oxygen, and noninvasive ventilation.

Development of acute lung injury or acute respiratory distress syndrome after subarachnoid hemorrhage, predictive factors, and impact on prognosis

Acute lung injury or acute respiratory distress syndrome (ALI/ARDS) is a common complication after aneurysmal subarachnoid hemorrhage (aSAH), and is associated with worse neurologic outcomes and longer hospitalization. However, the effect of ALI/ARDS in SAH has not been well elucidated. The purpose of this study was to determine the incidence of ALI/ARDS in a cohort of patients with SAH and to determine the risk factors for ALI/ARDS and their impact on patient prognosis. We performed a retrospective analysis of 167 consecutive patients with aSAH enrolled. ALI/ARDS patients were rigorously adjudicated using North American-European Consensus Conference definition. Regression analyses were used to test the risk factors for ALI/ARDS in patients with SAH. A total of 167 patients fulfilled the inclusion criteria, and 27% patients (45 of 167) developed ALI. Among all 45 ALI patients, 33 (20%, 33 of 167) patients met criteria for ARDS. On multivariate analysis, elderly patients, lower glasgow coma scale (GCS), higher Hunt-Hess grade, higher simplified acute physiology score (SAPS) II score, pre-existing pneumonia, gastric aspiration, hypoxemia, and tachypnea were the strongest risk factor for ALI/ARDS. Patients with ALI/ARDS showed worse clinical outcomes measured at 30 days. Development of ALI/ARDS was associated with a statistically significant increasing the odds of tracheostomy and hospital complications, and increasing duration of mechanical ventilation, intensive care unit (ICU) length and hospitalization stay. Development of ALI/ARDS is a severe complication of SAH and is associated with a poor clinical outcome, and further studies should focus on both prevention and management strategies specific to SAH-associated ALI/ARDS.

Clinical characteristics and outcomes of critically ill coronavirus disease 2019 patients in Malaysia during the first wave: A multi-center observational study (COVIDICU-MY).

Coronavirus disease 2019 (COVID-19) emerged with a wide range of clinical presentations; Malaysia was not spared from its impact. This study describes the clinical characteristics of COVID-19 patients admitted to intensive care unit, their clinical course, management, and hospital outcomes. COVIDICU-MY is a retrospective analysis of COVID-19 patients from 19 intensive care units (ICU) across Malaysia from 1 March 2020 to 31 May 2020. We collected epidemiological history, demographics, clinical comorbidities, laboratory investigations, respiratory and hemodynamic values, management, length of stay and survival status. We compared these variables between survival and non-survival groups. A total of 170 critically ill patients were included, with 77% above 50 years of age [median age 60, IQR (51-66)] and 75.3% male. Hypertension, diabetes mellitus, hyperlipidemia, chronic cardiac disease, and chronic kidney disease were most common among patients. A high Simplified Acute Physiology Score (SAPS) II score [median 45, IQR (34-49)] and Sequential Organ Failure Assessment (SOFA) score [median 8, IQR (6-11)] were associated with mortality. Patients were profoundly hypoxic with a median lowest PaO2/FiO2 ratio of 150 (IQR 99-220) at admission. 91 patients (53.5%) required intubation on their first day of admission, out of which 38 died (73.1% of the hospital non-survivors). Our sample had more patients with moderate Acute Respiratory Distress Syndrome (ARDS), 58 patients (43.9%), compared to severe ARDS, 33 patients (25%); with both ARDS classification groups contributing to 25 patients (54.4%) and 11 patients (23.9%) of the non-survival group, respectively. Cumulative fluid balance over 24 h was higher in the non-survival group with significant differences on Day 3 (1,953 vs. 622 ml, p < 0.05) and Day 7 of ICU (3,485 vs. 830 ml, p < 0.05). Patients with high serum creatinine, urea, lactate dehydrogenase, aspartate aminotransferase and d-dimer, and low lymphocyte count throughout the stay also had a higher risk of mortality. The hospital mortality rate was 30.6% in our sample. We report high mortality amongst critically ill patients in intensive care units in Malaysia, at 30.6%, during the March to May 2020 period. High admission SAPS II and SOFA, and severe hypoxemia and high cumulative fluid balance were associated with mortality. Higher creatinine, urea, lactate dehydrogenase, aspartate aminotransferase and d-dimer, and lymphopenia were observed in the non-survival group.

Morbimortality and Six-Month Survival Among Elderly Patients Treated With Noninvasive Mechanical Ventilation in an Intermediate Care Unit: A Retrospective Evaluation.

Noninvasive mechanical ventilation (NIMV) has been established as a successful therapeutic option for patients with acute respiratory failure (ARF) with a specific etiology. This study evaluated the morbimortality of patients with ARF treated with NIMV in a medical intermediate care unit (UCINT) to identify factors associated with higher in-hospital mortality, six-month mortality, and three- and six-month hospital readmission rates. This retrospective cohort study included elderly patients admitted for ARF and treated with NIMV in the UCINTbetween 2015 and 2019. In the sample of 102 patients, the median age was84.2(±5.5) years, and 57% were women. In total, 28% were on long-term oxygen therapy, and 68% had a do-not-resuscitate order. At admission, the median Charlson comorbidity index and Barthel index of activities of daily living were 7[6; 8]and 30[20; 57,5],respectively. The simplified acute physiology score IIwas 39.1±10.7, and 92% of patients had type 2 ARF. Median days on NIMV and days in UCINT were 10[6; 16]and 6[3; 10], respectively. The main conditions requiring UCINT admission for NIMV were heart failure, pneumonia, and exacerbation of the chronic obstructive pulmonary disease. The NIMV failure rate was 7%. At discharge, the average Barthel index was 35[10; 55]. The in-hospital mortality rate was 23%. Older age, higher simplified acute physiology score II, higher Charlson comorbidity index, and higher number of days on NIMV were associated with higher in-hospital mortality. Long-term oxygen therapy was associated with higher three-month mortality. A higher Barthel index at the time of hospital discharge was associated with a higher six-month readmission rate. NIMV can be used successfully in elderly patients and less studied ARF etiologies, such as pneumonia.

Critically ill COVID-19 patients in northeast Brazil: mortality predictors during the first and second waves including SAPS 3.

BackgroundThe Simplified Acute Physiology Score (SAPS) 3 is a reliable score to predict mortality. This study aims to investigate the predictive values of SAPS 3 and other clinical parameters for death in critically ill coronavirus disease 2019 (COVID-19) patients.MethodsThis is a prospective study in a tertiary hospital for patients who required intensive care due to COVID-19 infection in northeast Brazil. Two distinct groups were constructed according to the epidemiological data: first wave and second wave. The severity of patients admitted was estimated using the SAPS 3 score.ResultsA total of 767 patients were included: 290 were enrolled in the first wave and 477 in the second wave. Patients in the first wave had more comorbidities, were put on mechanical ventilation and required dialysis and vasopressors more frequently (p<0.05). During the second wave, non-invasive ventilation was more often required (p<0.05). In both periods, older patients and higher SAPS 3 scores on admission were associated with death (p<0.05). Non-invasive ventilation use showed a negative association with death only in the second wave period. In the first wave, the SAPS 3 score was more useful (area under the curve [AUC] 0.897) in predicting death in critically ill COVID-19 patients than in the second wave (AUC 0.810).ConclusionThe SAPS 3 showed very reliable predictive values for death during the waves of the COVID-19 pandemic, mostly together with kidney and pulmonary dysfunction.

Critical Influenza and COVID-19-A Comparative Nationwide Case-Control Study.

IMPORTANCE:Refined knowledge of risk factors for critical influenza and COVID-19 may lead to improved understanding of pathophysiology and better pandemic preparedness.OBJECTIVES:To compare risk-factor profiles of patients admitted to intensive care with critical influenza and COVID-19.DESIGN, SETTING, AND PATIENTS:A nationwide retrospective matched case-control study, including all adults admitted to an ICU in Sweden with influenza or COVID-19 between 2014 and September 2020 and a matched control population (ratio 1:5, patients:controls).MEASUREMENTS AND MAIN RESULTS:Admission to an ICU. The study included 1,873 influenza and 2,567 COVID-19 ICU patients, and 9,365 and 12,835 controls, respectively, matched on sex, age, and geographical region. Influenza patients were older and less likely male, and carried a larger burden of comorbidity and a higher Simplified Acute Physiology Score III score, whereas short-term mortalities were similar when compared to COVID-19 patients. The risk-factor profiles at ICU admission were largely comparable including socioeconomic, psychiatric, and several somatic variables. Hypertension was a strong risk factor in critical COVID-19 patients compared with influenza. Nonglucocorticoid immunosuppressive therapy was associated with critical influenza but not COVID-19. Premorbid medication with statins and renin-angiotensin-aldosterone system inhibitors reduced the risk for both conditions, the opposite was a seen for glucocorticoid medication. Notably, medication with betablockers, oral anticoagulation, and platelet inhibitors reduced the risk of critical COVID-19 but not influenza.CONCLUSIONS:The risk-factor profiles for critical influenza and COVID-19 were largely comparable; however, some important differences were noted. Hypertension was a stronger risk factor for developing critical COVID-19, whereas the use of betablockers, oral anticoagulants, and platelet inhibitors all reduced the risk of ICU admission for COVID-19 but not influenza. Findings possibly reflected differences in pathophysiological mechanisms between these conditions.

High rate of Clostridioides difficile colonization in patients admitted to intensive care: A prospective cohort study

Here, we evaluated the frequency of C. difficile colonization and its impact on clinical outcomes in patients admitted to intensive care units in Brazil. From ninety-two patients screened 16 (17.3%) were colonized by C. difficile. Colonized patients had higher Simplified Acute Physiology Score III (SAPS III), however there was no association between C. difficile colonization with diarrhea or mortality. The C. difficile strains sequenced belonged to clade 1 and presented high vancomycin-resistant rates.

Corticosteroids as risk factor for COVID-19-associated pulmonary aspergillosis in intensive care patients

PurposeCorticosteroids, in particular dexamethasone, are one of the primary treatment options for critically ill COVID-19 patients. However, there are a growing number of cases that involve COVID-19-associated pulmonary aspergillosis (CAPA), and it is unclear whether dexamethasone represents a risk factor for CAPA. Our aim was to investigate a possible association of the recommended dexamethasone therapy with a risk of CAPA.MethodsWe performed a study based on a cohort of COVID-19 patients treated in 2020 in our 13 intensive care units at Charité Universitätsmedizin Berlin. We used ECMM/ISHM criteria for the CAPA diagnosis and performed univariate and multivariable analyses of clinical parameters to identify risk factors that could result in a diagnosis of CAPA.ResultsAltogether, among the n = 522 intensive care patients analyzed, n = 47 (9%) patients developed CAPA. CAPA patients had a higher simplified acute physiology score (SAPS) (64 vs. 53, p < 0.001) and higher levels of IL-6 (1,005 vs. 461, p < 0.008). They more often had severe acute respiratory distress syndrome (ARDS) (60% vs. 41%, p = 0.024), renal replacement therapy (60% vs. 41%, p = 0.024), and they were more likely to die (64% vs. 48%, p = 0.049). The multivariable analysis showed dexamethasone (OR 3.110, CI95 1.112–8.697) and SAPS (OR 1.063, CI95 1.028–1.098) to be independent risk factors for CAPA.ConclusionIn our study, dexamethasone therapy as recommended for COVID-19 was associated with a significant three times increase in the risk of CAPA.Trial registrationRegistration number DRKS00024578, Date of registration March 3rd, 2021.

Prognostic value of hyperlactatemia in infected patients admitted to intensive care units: a multicenter study.

To evaluate the influence of patient characteristics on hyperlactatemia in an infected population admitted to intensive care units and the influence of hyperlactatemia severity on hospital mortality. A post hoc analysis of hyperlactatemia in the INFAUCI study, a national prospective, observational, multicenter study, was conducted in 14 Portuguese intensive care units. Infected patients admitted to intensive care units with a lactate measurement in the first 12 hours of admission were selected. Sepsis was identified according to the Sepsis-2 definition accepted at the time of data collection. The severity of hyperlactatemia was classified as mild (2 - 3.9mmol/L), moderate (4.0 - 9.9mmol/L) or severe (> 10mmol/L). In a total of 1,640 patients infected on admission, hyperlactatemia occurred in 934 patients (57%), classified as mild, moderate and severe in 57.0%, 34.4% and 8.7% of patients, respectively. The presence of hyperlactatemia and a higher degree of hyperlactatemia were both associated with a higher Simplified Acute Physiology Score II, a higher Charlson Comorbidity Index and the presence of septic shock. The lactate Receiver Operating Characteristic curve for hospital mortality had an area under the curve of 0.64 (95%CI 0.61 - 0.72), which increased to 0.71 (95%CI 0.68 - 0.74) when combined with Sequential Organ Failure Assessment score. In-hospital mortality with other covariates adjusted by Simplified Acute Physiology Score II was associated with moderate and severe hyperlactatemia, with odds ratio of 1.95 (95%CI 1.4 - 2.7; p < 0.001) and 4.54 (95%CI 2.4 - 8.5; p < 0.001), respectively. Blood lactate levels correlate independently with in-hospital mortality for moderate and severe degrees of hyperlactatemia.

Prognostic value of hyperlactatemia in infected patients admitted to intensive care units: a multicenter study

Objective:To evaluate the influence of patient characteristics on hyperlactatemia in an infected population admitted to intensive care units and the influence of hyperlactatemia severity on hospital mortality.Methods:A post hoc analysis of hyperlactatemia in the INFAUCI study, a national prospective, observational, multicenter study, was conducted in 14 Portuguese intensive care units. Infected patients admitted to intensive care units with a lactate measurement in the first 12 hours of admission were selected. Sepsis was identified according to the Sepsis-2 definition accepted at the time of data collection. The severity of hyperlactatemia was classified as mild (2 - 3.9mmol/L), moderate (4.0 - 9.9mmol/L) or severe (> 10mmol/L).Results:In a total of 1,640 patients infected on admission, hyperlactatemia occurred in 934 patients (57%), classified as mild, moderate and severe in 57.0%, 34.4% and 8.7% of patients, respectively. The presence of hyperlactatemia and a higher degree of hyperlactatemia were both associated with a higher Simplified Acute Physiology Score II, a higher Charlson Comorbidity Index and the presence of septic shock. The lactate Receiver Operating Characteristic curve for hospital mortality had an area under the curve of 0.64 (95%CI 0.61 - 0.72), which increased to 0.71 (95%CI 0.68 - 0.74) when combined with Sequential Organ Failure Assessment score. In-hospital mortality with other covariates adjusted by Simplified Acute Physiology Score II was associated with moderate and severe hyperlactatemia, with odds ratio of 1.95 (95%CI 1.4 - 2.7; p < 0.001) and 4.54 (95%CI 2.4 - 8.5; p < 0.001), respectively.Conclusion:Blood lactate levels correlate independently with in-hospital mortality for moderate and severe degrees of hyperlactatemia.

Clinical characteristics and outcomes of COVID-19 patients admitted to the intensive care unit during the first year of the pandemic in Brazil: a single center retrospective cohort study.

ABSTRACTObjective:To describe clinical characteristics, resource use, outcomes, and to identify predictors of in-hospital mortality of patients with COVID-19 admitted to the intensive care unit.Methods:Retrospective single-center cohort study conducted at a private hospital in São Paulo (SP), Brazil. All consecutive adult (≥18 years) patients admitted to the intensive care unit, between March 4, 2020 and February 28, 2021 were included in this study. Patients were categorized between survivors and non-survivors according to hospital discharge.Results:During the study period, 1,296 patients [median (interquartile range) age: 66 (53-77) years] with COVID-19 were admitted to the intensive care unit. Out of those, 170 (13.6%) died at hospital (non-survivors) and 1,078 (86.4%) were discharged (survivors). Compared to survivors, non-survivors were older [80 (70-88) versus 63 (50-74) years; p<0.001], had a higher Simplified Acute Physiology Score 3 [59 (54-66) versus 47 (42-53) points; p<0.001], and presented comorbidities more frequently. During the intensive care unit stay, 56.6% of patients received noninvasive ventilation, 32.9% received mechanical ventilation, 31.3% used high flow nasal cannula, 11.7% received renal replacement therapy, and 1.5% used extracorporeal membrane oxygenation. Independent predictors of in-hospital mortality included age, Sequential Organ Failure Assessment score, Charlson Comorbidity Index, need for mechanical ventilation, high flow nasal cannula, renal replacement therapy, and extracorporeal membrane oxygenation support.Conclusion:Patients with severe COVID-19 admitted to the intensive care unit exhibited a considerable morbidity and mortality, demanding substantial organ support, and prolonged intensive care unit and hospital stay.

Incidence, prognosis, and risk factors of sepsis-induced cardiomyopathy.

BACKGROUNDAt present, large-scale studies on the clinical characteristics of sepsis-induced cardiomyopathy (SIC) are lacking. AIMTo investigate the clinical characteristics of SIC.METHODSBased on the analysis of the MIMIC-III public database, we performed a large-scale retrospective study involving sepsis patients who were admitted to the intensive care unit (ICU) and had no concomitant cardiac disease. We used propensity score matching analysis and multivariate logistic regression to ensure the robustness of the results. The primary outcome was hospital mortality, and the secondary outcomes included the number of patients who received mechanical ventilation or renal replacement therapy during their hospital stay, the number of patients administered with vasopressors, the length of ICU stay, and the length of hospital stay.RESULTSIn the present study, after screening 38605 patients, 3530 patients with sepsis were included. A total of 997 patients met the SIC diagnostic criteria, and the incidence of SIC was 28.20% (95% confidence interval [CI]: 26.80%-29.70%). Compared to patients in the non-SIC group, patients in the SIC group were of older age and had a higher Simplified Acute Physiology Score (SAPS)-I score, SAPS-II score, and Elixhauser comorbidity index (ECI). A total of 367 (36.8%) of 997 patients in the SIC group and 818 (32.3%) of 2533 patients in the non-SIC group died in the hospital, which resulted in a significant between-group difference (odds ratios = 1.22, 95%CI: 1.05-1.42; P = 0.011). For the secondary outcomes, more patients in the SIC group received mechanical ventilation and vasopressors. Multivariate logistic regression analysis showed that age, male sex, ECI, hemoglobin level, diabetes, and mechanical ventilation use on the first day of ICU admission were risk factors for SIC.CONCLUSIONCompared with non-SIC patients, hospital mortality is higher in SIC patients.

Clinical Benefit of Extubation in Patients on Venoarterial Extracorporeal Membrane Oxygenation.

Although patients on venoarterial extracorporeal membrane oxygenation for refractory cardiogenic shock are usually supported with mechanical ventilation, it is not clear whether sedation cessation and extubation might improve outcomes. Retrospective cohort study with propensity score overlap weighting analysis. Three ICUs in a 1,500-bed tertiary university hospital. From an overall cohort of 641 patients with venoarterial-extracorporeal membrane oxygenation support, the primary analysis was performed in 344 patients who had been successfully decannulated in order to reduce immortal time bias. Seventy-five patients (22%) were extubated during extracorporeal membrane oxygenation support and were subsequently decannulated alive. Forty-nine percent received noninvasive ventilation, and 25% had emergency reintubation for respiratory, neurologic, or hemodynamic reasons. Higher Simplified Acute Physiology Score II at admission (odds ratio, 0.97; 95% CI [0.95-0.99]; p = 0.008) was associated with a lower probability of extubation, whereas cannulation in cardiac surgery ICU (odds ratio, 3.14; 95% CI [1.21-8.14]; p = 0.018) was associated with an increased probability. Baseline characteristics were well balanced after propensity score overlap weighting. The number of ICU-free days within 30 days of extracorporeal membrane oxygenation decannulation was significantly higher among extubated patients compared with nonextubated patients (22 d [11-26 d] vs 18 d [7-25 d], respectively; p = 0.036). There were no differences in other outcomes including ventilator-associated pneumonia (odds ratio, 0.96; 95% CI [0.51-1.82]; p = 0.90) and all-cause mortality within 30 days of extracorporeal membrane oxygenation decannulation (5% vs 17%; hazard ratio, 0.54; 95% CI [0.19-1.59]; p = 0.27).As a secondary analysis, outcomes were compared in the overall cohort of 641 venoarterial extracorporeal membrane oxygenation-supported patients. Results were consistent with the primary analysis as extubated patients had a higher number of ICU-free days (18 d [0-24 d] vs 0 d [0-18 d], respectively; < 0.001) and a lower risk of death within 30 days of extracorporeal membrane oxygenation cannulation (hazard ratio, 0.45; 95% CI [0.29-0.71]; p = 0.001). Extubation during venoarterial-extracorporeal membrane oxygenation support is safe, feasible, and associated with greater ICU-free days.

Surviving cardiac arrest: What happens after admission to the intensive care unit?

Patients successfully resuscitated from cardiac arrest (CA) are admitted to the intensive care unit (ICU) for post-resuscitation care. These patients' prognosis remains dismal, with only a minority surviving to hospital discharge. Understanding the clinical factors involved in the management of these patients is essential to improve their prognosis. To characterize the population admitted after successful reanimation from CA, and to analyze the factors associated with their outcomes. We performed a retrospective descriptive study of patients admitted to an ICU after CA over a five-year period from January 2014 to December 2018. Demographic factors, CA characteristics, early management, mortality and neurologic outcomes were analyzed. A total of 187 patients, median age 67 years, were admitted after CA, of whom 39% suffered out-of-hospital CA; 87% had an initial non-shockable rhythm and the most frequent presumed cause was cardiac (31%). In-hospital mortality was 63%. Significant neurologic dysfunction (cerebral performance category 3 or 4) was seen in 31% of survivors at hospital discharge. Non-immediate initiation of basic life support (BLS), higher Simplified Acute Physiology Score II score and longer relative duration of vasopressor support were independent predictors of in-hospital mortality, while shockable rhythms were associated with improved survival. Higher Glasgow coma scale at ICU discharge and shorter length of ICU stay were predictors of better neurologic outcome. This study highlights the positive prognostic impact of shockable rhythms, and confirms the importance of immediate initiation of BLS and prompt defibrillation, supporting the need for better training both outside and inside hospitals.

Delta Shock Index During Emergency Department Stay Is Associated With in Hospital Mortality in Critically Ill Patients.

Background: Delta shock index (SI; i.e., change in SI over time) has been shown to predict mortality and need for surgical intervention among trauma patients at the emergency department (ED). However, the usefulness of delta SI for prognosis assessment in non-traumatic critically ill patients at the ED remains unknown. The aim of this study was to analyze the association between delta SI during ED management and in-hospital outcomes in patients admitted to the intensive care unit (ICU).Method: This was a retrospective study conducted in two tertiary medical centers in Taiwan from January 1, 2016, to December 31, 2017. All adult non-traumatic patients who visited the ED and who were subsequently admitted to the ICU were included. We calculated delta SI by subtracting SI at ICU admission from SI at ED triage, and we analyzed its association with in-hospital outcomes. SI was defined as the ratio of heart rate to systolic blood pressure (SBP). The primary outcome was in-hospital mortality, and the secondary outcomes were hospital length of stay (HLOS) and early mortality. Early mortality was defined as mortality within 48 h of ICU admission.Result: During the study period, 11,268 patients met the criteria and were included. Their mean age was 64.5 ± 15.9 years old. Overall, 5,830 (51.6%) patients had positive delta SI. Factors associated with a positive delta SI were multiple comorbidities (51.2% vs. 46.3%, p < 0.001) and high Simplified Acute Physiology Score [39 (29–51) vs. 37 (28–47), p < 0.001). Patients with positive delta SI were more likely to have tachycardia, hypotension, and higher SI at ICU admission. In the regression analysis, high delta SI was associated with in-hospital mortality [aOR (95% CI): 1.21 (1.03–1.42)] and early mortality [aOR (95% CI): 1.26 (1.07–1.48)], but not for HLOS [difference (95% CI): 0.34 (−0.48 to 1.17)]. In the subgroup analysis, high delta SI had higher odds ratios for both mortality and early mortality in elderly [aOR (95% CI): 1.59 (1.11–2.29)] and septic patients [aOR (95% CI): 1.54 (1.13–2.11)]. It also showed a higher odds ratio for early mortality in patients with triage SBP <100 mmHg [aOR (95% CI): 2.14 (1.21–3.77)] and patients with triage SI ≥ 0.9 [aOR (95% CI): 1.62 (1.01–2.60)].Conclusion: High delta SI during ED stay is correlated with in-hospital mortality and early mortality in patients admitted to the ICU via ED. Prompt resuscitation should be performed, especially for those with old age, sepsis, triage SBP <100 mmHg, or triage SI ≥ 0.9.