Patterns of Multiple Organ Dysfunction and Renal Recovery in Critically Ill Children and Young Adults Receiving Continuous Renal Replacement Therapy.

OBJECTIVES: Acute kidney injury requiring dialysis (AKI-D) commonly occurs in the setting of multiple organ dysfunction syndrome (MODS). Continuous renal replacement therapy (CRRT) is the modality of choice for AKI-D. Mid-term outcomes of pediatric AKI-D supported with CRRT are unknown. We aimed to describe the pattern and impact of organ dysfunction on renal outcomes in critically ill children and young adults with AKI-D. DESIGN: Retrospective cohort. SETTING: Two large quarternary care pediatric hospitals. PATIENTS: Patients 26 y old or younger who received CRRT from 2014 to 2020, excluding patients with chronic kidney disease. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Organ dysfunction was assessed using the Pediatric Logistic Organ Dysfunction-2 (PELOD-2) score. MODS was defined as greater than or equal to two organ dysfunctions. The primary outcome was major adverse kidney events at 30 days (MAKE30) (decrease in estimated glomerular filtration rate greater than or equal to 25% from baseline, need for renal replacement therapy, and death). Three hundred seventy-three patients, 50% female, with a median age of 84 mo (interquartile range [IQR] 16-172) were analyzed. PELOD-2 increased from 6 (IQR 3-9) to 9 (IQR 7-12) between ICU admission and CRRT initiation. Ninety-seven percent of patients developed MODS at CRRT start and 266 patients (71%) had MAKE30. Acute kidney injury (adjusted odds ratio [aOR] 3.55 [IQR 2.13-5.90]), neurologic (aOR 2.07 [IQR 1.15-3.74]), hematologic/oncologic dysfunction (aOR 2.27 [IQR 1.32-3.91]) at CRRT start, and progressive MODS (aOR 1.11 [IQR 1.03-1.19]) were independently associated with MAKE30. CONCLUSIONS: Ninety percent of critically ill children and young adults with AKI-D develop MODS by the start of CRRT. Lack of renal recovery is associated with specific extrarenal organ dysfunction and progressive multiple organ dysfunction. Currently available extrarenal organ support strategies, such as therapeutic plasma exchange lung-protective ventilation, and other modifiable risk factors, should be incorporated into clinical trial design when investigating renal recovery.

Hepatic function markers as prognostic factors in patients with acute kidney injury undergoing continuous renal replacement therapy.

Acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT), secondary to cardiovascular disease and sepsis, is associated with high in-hospital mortality. Although studies have examined cardiovascular disease and sepsis in AKI, the association between AKI and hepatic functional impairment remains unclear. We hypothesized that hepatic function markers would predict mortality in patients undergoing CRRT. We included 1,899 CRRT patients from a multi-centre database. In Phase 1, participants were classified according to the total bilirubin (T-Bil) levels on the day of, and 3 days after, CRRT initiation: T-Bil < 1.2, 1.2 ≤ T-Bil < 2, and T-Bil ≥ 2 mg/dL. In Phase 2, propensity score matching (PSM) was performed to examine the effect of a T-Bil cutoff of 1.2 mg/dL (supported by the Sequential Organ Failure Assessment score); creating two groups based on a T-Bil cutoff of 1.2 mg/dL 3 days after CRRT initiation. The primary endpoint was total mortality 90 days after CRRT initiation, which was 34.7% (n = 571). In Phase 1, the T-Bil, aspartate transaminase (AST), alanine transaminase (ALT), and AST/ALT (De Ritis ratio) levels at CRRT initiation were not associated with the prognosis, while T-Bil, AST, and the De Ritis ratio 3 days after CRRT initiation were independent factors. In Phase 2, T-Bil ≥1.2 mg/dL on day 3 was a significant independent prognostic factor, even after PSM [hazard ratio: 2.41 (95% CI; 1.84-3.17), p < 0.001]. T-Bil ≥1.2 mg/dL 3 days after CRRT initiation predicted 90-day mortality. Changes in hepatic function markers in acute renal failure may enable stratification of high-risk patients.

Usefulness of the qSOFA score for predicting hospital mortality in cancer patients.

BACKGROUND: The quick Sequential Sepsis-related Organ Failure Assessment (qSOFA) is a score that has been proposed to quickly identify patients at higher risk of death. OBJECTIVE: To describe the usefulness of the qSOFA score to predict in-hospital mortality in cancer patients. MATERIAL AND METHODS: Cross-sectional study carried out between January 2021 and December 2022. Hospital mortality was the dependent variable. The area under the ROC curve (AUC) was calculated to determine the discriminative ability of qSOFA to predict in-hospital mortality. RESULTS: A total of 587 cancer patients were included. A qSOFA score higher than 1 obtained a sensitivity of 57.2%, specificity of 78.5%, a positive predictive value of 55.4% and negative predictive value of 79.7%. The AUC of qSOFA for predicting in-hospital mortality was 0.70. In-hospital mortality of patients with qSOFA scores of 2 and 3 points was 52.7 and 64.4%, respectively. In-hospital mortality was 31.9% (187/587). CONCLUSION: qSOFA showed acceptable discriminative ability for predicting in-hospital mortality in cancer patients.

ANTECEDENTES: El quick Sequential Sepsis-related Organ Failure Assessment (qSOFA) es una puntuación propuesta para identificar de forma rápida a pacientes con mayor probabilidad de morir. OBJETIVO: Describir la utilidad de la puntuación qSOFA para predecir mortalidad hospitalaria en pacientes con cáncer. MATERIAL Y MÉTODOS: Estudio transversal realizado entre enero de 2021 y diciembre de 2022. La mortalidad hospitalaria fue la variable dependiente. Se calculó el área bajo la curva ROC (ABC) para determinar la capacidad discriminativa de qSOFA para predecir mortalidad hospitalaria. RESULTADOS: Se incluyeron 587 pacientes con cáncer. La puntuación qSOFA < 1 obtuvo una sensibilidad de 57.2 %, una especificidad de 78.5 %, un valor predictivo positivo de 55.4 % y un valor predictivo negativo de 79.7 %. El ABC de qSOFA para predecir mortalidad hospitalaria fue de 0.70. La mortalidad hospitalaria de los pacientes con qSOFA de 2 y 3 puntos fue de 52.7 y 64.4 %, respectivamente. La mortalidad hospitalaria fue de 31.9 % (187/587). CONCLUSIÓN: qSOFA mostró capacidad discriminativa aceptable para predecir mortalidad hospitalaria en pacientes con cáncer.

Construction and evaluation of short-term and long-term mortality risk prediction model for patients with sepsis based on MIMIC-IV database. / 基于MIMIC-IVæž„å»ºåŠè¯„ä¼°è„“æ¯’ç—‡æ‚£è€ è¿‘æœŸå’Œè¿œæœŸæ­»äº¡é£Žé™©é¢„æµ‹æ¨¡åž‹.

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Diastolic/systolic blood pressure ratio for predicting febrile children with sepsis and progress to septic shock in the emergency department.

OBJECTIVE: Given the scarcity of studies analyzing the clinical predictors of pediatric septic cases that would progress to septic shock, this study aimed to determine strong predictors for pediatric emergency department (PED) patients with sepsis at risk for septic shock and mortality. METHODS: We conducted chart reviews of patients with ≥ 2 age-adjusted quick Sequential Organ Failure Assessment score (qSOFA) criteria to recognize patients with an infectious disease in two tertiary PEDs between January 1, 2021, and April 30, 2022. The age range of included patients was 1 month to 18 years. The primary outcome was development of septic shock within 48 h of PED attendance. The secondary outcome was sepsis-related 28-day mortality. Initial important variables in the PED and hemodynamics with the highest and lowest values during the first 24 h of admission were also analyzed. RESULTS: Overall, 417 patients were admitted because of sepsis and met the eligibility criteria for the study. Forty-nine cases progressed to septic shock within 48 h after admission and 368 were discharged without progression. General demographics, laboratory data, and hemodynamics were analyzed by multivariate analysis. Only the minimum diastolic blood pressure/systolic blood pressure ratio (D/S ratio) during the first 24 h after admission remained as an independent predictor of progression to septic shock and 28-day mortality. The best cutoff values of the D/S ratio for predicting septic shock and 28-day mortality were 0.52 and 0.47, respectively. CONCLUSIONS: The D/S ratio is a practical bedside scoring system in the PED and had good discriminative ability in predicting the progression of septic shock and in-hospital mortality in PED patients. Further validation is essential in other settings.

SOFA in sepsis: with or without GCS.

PURPOSE: Sepsis is a global public health burden. The sequential organ failure assessment (SOFA) is the most commonly used scoring system for diagnosing sepsis and assessing severity. Due to the widespread use of endotracheal intubation and sedative medications in sepsis, the accuracy of the Glasgow Coma Score (GCS) is the lowest in SOFA. We designed this multicenter, cross-sectional study to investigate the predictive efficiency of SOFA with or without GCS on ICU mortality in patients with sepsis. METHODS: First, 3048 patients with sepsis admitted to Peking Union Medical College Hospital (PUMCH) were enrolled in this survey. The data were collected from June 8, 2013 to October 12, 2022. Second, 18,108 patients with sepsis in the eICU database were enrolled. Third, 2397 septic patients with respiratory system ≥ 3 points in SOFA in the eICU database were included. We investigated the predictive efficiency of SOFA with or without GCS on ICU mortality in patients with sepsis in various ICUs of PUMCH, and then we validated the results in the eICU database. MAIN RESULTS: In data of ICUs in PUMCH, the predictive efficiency of SOFA without GCS (AUROC [95% CI], 24 h, 0.724 [0.688, 0.760], 48 h, 0.734 [0.699, 0.769], 72 h, 0.748 [0.713, 0.783], 168 h, 0.781 [0.747, 0.815]) was higher than that of SOFA with GCS (AUROC [95% CI], 24 h, 0.708 [0.672, 0.744], 48 h, 0.721 [0.685, 0.757], 72 h, 0.735 [0.700, 0.757], 168 h, 0.770 [0.736, 0.804]) on ICU mortality in patients with sepsis, and the difference was statistically significant (P value, 24 h, 0.001, 48 h, 0.003, 72 h, 0.004, 168 h, 0.005). In septic patients with respiratory system ≥ 3 points in SOFA in the eICU database, although the difference was not statistically significant (P value, 24 h, 0.148, 48 h, 0.178, 72 h, 0.132, 168 h, 0.790), SOFA without GCS (AUROC [95% CI], 24 h, 0.601 [0.576, 0.626], 48 h, 0.625 [0.601, 0.649], 72 h, 0.639 [0.615, 0.663], 168 h, 0.653 [0.629, 0.677]) had a higher predictive efficiency on ICU mortality than SOFA with GCS (AUROC [95% CI], 24 h, 0.591 [0.566, 0.616], 48 h, 0.616 [0.592, 0.640], 72 h, 0.628 [0.604, 0.652], 168 h, 0.651 [0.627, 0.675]). CONCLUSIONS: In severe sepsis, it is realistic and feasible to discontinue the routine GCS for SOFA in patients with a respiratory system ≥ 3 points, and even better predict ICU mortality.

Automated Calculator for the Pediatric Sequential Organ Failure Assessment Score: Development and External Validation in a Single-Center 7-Year Cohort, 2015-2021.

OBJECTIVES: The pediatric Sequential Organ Failure Assessment (pSOFA) score summarizes severity of organ dysfunction and can be used to predict in-hospital mortality. Manual calculation of the pSOFA score is time-consuming and prone to human error. An automated method that is open-source, flexible, and scalable for calculating the pSOFA score directly from electronic health record data is desirable. DESIGN: Single-center, retrospective cohort study. SETTING: Quaternary 40-bed PICU. PATIENTS: All patients admitted to the PICU between 2015 and 2021 with ICU stay of at least 24 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used 77 records to evaluate the automated score. The automated algorithm had an overall accuracy of 97%. The algorithm calculated the respiratory component of two cases incorrectly. An expert human annotator had an initial accuracy of 75% at the patient level and 95% at the component level. An untrained human annotator with general clinical research experience had an overall accuracy of 16% and component-wise accuracy of 67%. Weighted kappa for agreement between the automated method and the expert annotator's initial score was 0.92 (95% CI, 0.88-0.95), and between the untrained human annotator and the automated score was 0.50 (95% CI, 0.36-0.61). Data from 9146 patients (in-hospital mortality 3.6%) were included to validate externally the discriminability of the automated pSOFA score. The admission-day pSOFA score had an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.77-0.82). CONCLUSIONS: The developed automated algorithm calculates pSOFA score with high accuracy and is more accurate than a trained expert rater and nontrained data abstracter. pSOFA's performance for predicting in-hospital mortality was lower in our cohort than it was for the originally derived score.

Dynamic Prediction of Mortality Using Longitudinally Measured Pediatric Sequential Organ Failure Assessment Scores: A Joint Modeling Approach.

OBJECTIVES: The pediatric Sequential Organ Failure Assessment (pSOFA) score was designed to track illness severity and predict mortality in critically ill children. Most commonly, pSOFA at a point in time is used to assess a static patient condition. However, this approach has a significant drawback because it fails to consider any changes in a patients' condition during their PICU stay and, especially, their response to initial critical care treatment. We aimed to evaluate the performance of longitudinal pSOFA scores for predicting mortality. DESIGN: Single-center, retrospective cohort study. SETTING: Quaternary 40-bed PICU. PATIENTS: All patients admitted to the PICU between 2015 and 2021 with at least 24 hours of ICU stay. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We calculated daily pSOFA scores up to 30 days, or until death or discharge from the PICU, if earlier. We used the joint longitudinal and time-to-event data model for the dynamic prediction of 30-day in-hospital mortality. The dataset, which included 9146 patients with a 30-day in-hospital mortality of 2.6%, was divided randomly into training (75%) and validation (25%) subsets, and subjected to 40 repeated stratified cross-validations. We used dynamic area under the curve (AUC) to evaluate the discriminative performance of the model. Compared with the admission-day pSOFA score, AUC for predicting mortality between days 5 and 30 was improved on average by 6.4% (95% CI, 6.3-6.6%) using longitudinal pSOFA scores from the first 3 days and 9.2% (95% CI, 9.0-9.5%) using scores from the first 5 days. CONCLUSIONS: Compared with admission-day pSOFA score, longitudinal pSOFA scores improved the accuracy of mortality prediction in PICU patients at a single center. The pSOFA score has the potential to be used dynamically for the evaluation of patient conditions.

SOFA score performs worse than age for predicting mortality in patients with COVID-19.

The use of the Sequential Organ Failure Assessment (SOFA) score, originally developed to describe disease morbidity, is commonly used to predict in-hospital mortality. During the COVID-19 pandemic, many protocols for crisis standards of care used the SOFA score to select patients to be deprioritized due to a low likelihood of survival. A prior study found that age outperformed the SOFA score for mortality prediction in patients with COVID-19, but was limited to a small cohort of intensive care unit (ICU) patients and did not address whether their findings were unique to patients with COVID-19. Moreover, it is not known how well these measures perform across races. In this retrospective study, we compare the performance of age and SOFA score in predicting in-hospital mortality across two cohorts: a cohort of 2,648 consecutive adult patients diagnosed with COVID-19 who were admitted to a large academic health system in the northeastern United States over a 4-month period in 2020 and a cohort of 75,601 patients admitted to one of 335 ICUs in the eICU database between 2014 and 2015. We used age and the maximum SOFA score as predictor variables in separate univariate logistic regression models for in-hospital mortality and calculated area under the receiver operator characteristic curves (AU-ROCs) and area under precision-recall curves (AU-PRCs) for each predictor in both cohorts. Among the COVID-19 cohort, age (AU-ROC 0.795, 95% CI 0.762, 0.828) had a significantly better discrimination than SOFA score (AU-ROC 0.679, 95% CI 0.638, 0.721) for mortality prediction. Conversely, age (AU-ROC 0.628 95% CI 0.608, 0.628) underperformed compared to SOFA score (AU-ROC 0.735, 95% CI 0.726, 0.745) in non-COVID-19 ICU patients in the eICU database. There was no difference between Black and White COVID-19 patients in performance of either age or SOFA Score. Our findings bring into question the utility of SOFA score-based resource allocation in COVID-19 crisis standards of care.

Sepsis death risk factor score based on systemic inflammatory response syndrome, quick sequential organ failure assessment, and comorbidities.

OBJECTIVE: In this study, we aimed to evaluate the death risk factors of patients included in the sepsis protocol bundle, using clinical data from qSOFA, SIRS, and comorbidities, as well as development of a mortality risk score. DESIGN: This retrospective cohort study was conducted between 2016 and 2021. SETTING: Two university hospitals in Brazil. PARTICIPANTS: Patients with sepsis. INTERVENTIONS: Several clinical and laboratory data were collected focused on SIRS, qSOFA, and comorbidities. MAIN VARIABLE OF INTEREST: In-hospital mortality was the primary outcome variable. A mortality risk score was developed after logistic regression analysis. RESULTS: A total of 1,808 patients were included with a death rate of 36%. Ten variables remained independent factors related to death in multivariate analysis: temperature ≥38 °C (odds ratio [OR] = 0.65), previous sepsis (OR = 1.42), qSOFA ≥ 2 (OR = 1.43), leukocytes >12,000 or <4,000 cells/mm3 (OR = 1.61), encephalic vascular accident (OR = 1.88), age >60 years (OR = 1.93), cancer (OR = 2.2), length of hospital stay before sepsis >7 days (OR = 2.22,), dialysis (OR = 2.51), and cirrhosis (OR = 3.97). Considering the equation of the binary regression logistic analysis, the score presented an area under curve of 0.668, is not a potential model for death prediction. CONCLUSIONS: Several risk factors are independently associated with mortality, allowing the development of a prediction score based on qSOFA, SIRS, and comorbidities data, however, the performance of this score is low.

A comparison of Simplified Acute Physiology Score II and Sepsis-related Organ Failure Assessment Score for prediction of mortality after Intensive Care Unit cardiac arrest.

BACKGROUND: This study investigates the predictive value and suitable cutoff values of the Sepsis-related Organ Failure Assessment Score (SOFA) and Simplified Acute Physiology Score II (SAPS-II) to predict mortality during or after Intensive Care Unit Cardiac Arrest (ICU-CA). METHODS: In this secondary analysis the ICU database of a German university hospital with five ICU was screened for all ICU-CA between 2016-2019. SOFA and SAPS-II were used for prediction of mortality during ICU-CA, hospital-stay and one-year-mortality. Receiver operating characteristic curves (ROC), area under the ROC (AUROC) and its confidence intervals were calculated. If the AUROC was significant and considered "acceptable," cutoff values were determined for SOFA and SAPS-II by Youden Index. Odds ratios and sensitivity, specificity, positive and negative predictive values were calculated for the cutoff values. RESULTS: A total of 114 (78 male; mean age: 72.8±12.5 years) ICU-CA were observed out of 14,264 ICU-admissions (incidence: 0.8%; 95% CI: 0.7-1.0%). 29.8% (N.=34; 95% CI: 21.6-39.1%) died during ICU-CA. SOFA and SAPS-II were not predictive for mortality during ICU-CA (P>0.05). Hospital-mortality was 78.1% (N.=89; 95% CI: 69.3-85.3%). SAPS-II (recorded within 24 hours before and after ICU-CA) indicated a better discrimination between survival and death during hospital stay than SOFA (AUROC: 0.81 [95% CI: 0.70-0.92] vs. 0.70 [95% CI: 0.58-0.83]). A SAPS-II-cutoff-value of 43.5 seems to be suitable for prognosis of hospital mortality after ICU-CA (specificity: 87.5%, sensitivity: 65.6%; SAPS-II>43.5: 87.5% died in hospital; SAPS-II<43.5: 65.6% survived; odds ratio:13.4 [95% CI: 3.25-54.9]). Also for 1-year-mortality (89.5%; 95% CI: 82.3-94.4) SAPS-II showed a better discrimination between survival and death than SOFA: AUROC: 0.78 (95% CI: 0.65-0.91) vs. 0.69 (95% CI: 0.52-0.87) with a cutoff value of the SAPS-II of 40.5 (specificity: 91.7%, sensitivity: 64.3%; SAPS-II>40.5: 96.4% died; SAPS-II<40.5: 42.3% survived; odd ratio: 19.8 [95% CI: 2.3-168.7]). CONCLUSIONS: Compared to SOFA, SAPS-II seems to be more suitable for prediction of hospital and 1-year-mortality after ICU-CA.

Value of modified qSOFA, glucose and lactate in predicting prognosis in children with sepsis in the PICU.

The purpose was to investigate how well age-adjusted modified quick Sequential Organ Failure Assessment (qSOFA) scores paired with blood glucose and lactate levels predict the outcomes of septicemic children in the pediatric intensive care unit (PICU). One hundred children who were diagnosed with sepsis and septic shock in the PICU of Henan Children's Hospital were eligible, and other 20 patients in the same hospital at different times were selected as a validation set. Respiratory rate (RR), heart rate (HR), capillary refill time (CRT), and Alert, Voice, Pain, Unresponsive (AVPU) scale were included in the age-adjusted modified qSOFA scoring criteria for scoring. The primary outcome was 28-day all-cause mortality. The predictive values were evaluated by the ROC curve. In the sepsis group, 50 patients were male, and 50 patients were female. The 28-day all-cause mortality rate was 52%. Fifty-one patients with age-adjusted modified qSOFA scores >1. The serum lactate level was 2.4 mmol/L, and the blood glucose level was 9.3 mmol/L. The AUCs for the age-adjusted modified qSOFA score, serum lactate and blood glucose levels for the prediction of 28-day all-cause mortality in children with sepsis were 0.719, 0.719 and 0.737, respectively. The cut-off values were one point, 3.8 mmol/L and 10 mmol/L, respectively. The AUC of the age-adjusted modified qSOFA score for the validation set of was 0.925. When the three indices were combined, the AUC was 0.817, the Hosmer-Lemeshow goodness-of-fit test showed χ2 = 2.428 and p = .965. When children with sepsis are admitted to the ICU, we recommend performing rapid scoring and rapid bedside lactate and glucose testing to determine the early prognosis.

The Association between the rs3747406 Polymorphism in the Glucocorticoid-Induced Leucine Zipper Gene and Sepsis Survivals Depends on the SOFA Score.

The variability in mortality in sepsis could be a consequence of genetic variability. The glucocorticoid system and the intermediate TSC22D3 gene product-glucocorticoid-induced leucine zipper-are clinically relevant in sepsis, which is why this study aimed to clarify whether TSC22D3 gene polymorphisms contribute to the variance in sepsis mortality. Blood samples for DNA extraction were obtained from 455 patients with a sepsis diagnosis according to the Sepsis-III criteria and from 73 control subjects. A SNP TaqMan assay was used to detect single-nucleotide polymorphisms (SNPs) in the TSC22D3 gene. Statistical and graphical analyses were performed using the SPSS Statistics and GraphPad Prism software. C-allele carriers of rs3747406 have a 2.07-fold higher mortality rate when the sequential organ failure assessment (SOFA) score is higher than eight. In a multivariate COX regression model, the SNP rs3747406 with a SOFA score ≥ 8 was found to be an independent risk factor for 30-day survival in sepsis. The HR was calculated to be 2.12, with a p-value of 0.011. The wild-type allele was present in four out of six SNPs in our cohort. The promoter of TSC22D3 was found to be highly conserved. However, we discovered that the C-allele of rs3747406 poses a risk for sepsis mortality for SOFA Scores higher than 6.

Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures.

Using clustering analysis for early vital signs, unique patient phenotypes with distinct pathophysiological signatures and clinical outcomes may be revealed and support early clinical decision-making. Phenotyping using early vital signs has proven challenging, as vital signs are typically sampled sporadically. We proposed a novel, deep temporal interpolation and clustering network to simultaneously extract latent representations from irregularly sampled vital signs and derive phenotypes. Four distinct clusters were identified. Phenotype A (18%) had the greatest prevalence of comorbid disease with increased prevalence of prolonged respiratory insufficiency, acute kidney injury, sepsis, and long-term (3-year) mortality. Phenotypes B (33%) and C (31%) had a diffuse pattern of mild organ dysfunction. Phenotype B's favorable short-term clinical outcomes were tempered by the second highest rate of long-term mortality. Phenotype C had favorable clinical outcomes. Phenotype D (17%) exhibited early and persistent hypotension, high incidence of early surgery, and substantial biomarker incidence of inflammation. Despite early and severe illness, phenotype D had the second lowest long-term mortality. After comparing the sequential organ failure assessment scores, the clustering results did not simply provide a recapitulation of previous acuity assessments. This tool may impact triage decisions and have significant implications for clinical decision-support under time constraints and uncertainty.

Facial appearance associates with longitudinal multi-organ failure: an ICU cohort study.

BACKGROUND: Facial appearance, whether consciously or subconsciously assessed, may affect clinical assessment and treatment strategies in the Intensive Care Unit (ICU). Nevertheless, the association between objective clinical measurement of facial appearance and multi-organ failure is currently unknown. The objective of this study was to examine whether facial appearance at admission is associated with longitudinal evaluation of multi-organ failure. METHODS: This was a sub-study of the Simple Intensive Care Studies-II, a prospective observational cohort study. All adult patients acutely admitted to the ICU between March 26, 2019, and July 10, 2019, were included. Facial appearance was assessed within three hours of ICU admission using predefined pictograms. The SOFA score was serially measured each day for the first seven days after ICU admission. The association between the extent of eye-opening and facial skin colour with longitudinal Sequential Organ Failure Assessment (SOFA) scores was investigated using generalized estimation equations. RESULTS: SOFA scores were measured in 228 patients. Facial appearance scored by the extent of eye-opening was associated with a higher SOFA score at admission and follow-up (unadjusted 0.7 points per step (95%CI 0.5 to 0.9)). There was no association between facial skin colour and a worse SOFA score over time. However, patients with half-open or closed eyes along with flushed skin had a lower SOFA score than patients with a pale or normal facial skin colour (P-interaction < 0.1). CONCLUSIONS: The scoring of patients' facial cues, primarily the extent of eye-opening and facial colour, provided valuable insights into the disease state and progression of the disease of critically ill patients. The utilization of advanced monitoring techniques that incorporate facial appearance holds promise for enhancing future intensive care support.

Persistent high sepsis-induced coagulopathy and sequential organ failure assessment scores can predict the 28-day mortality of patients with sepsis: A prospective study.

BACKGROUND: The performance of the sepsis-induced coagulopathy (SIC) and sequential organ failure assessment (SOFA) scores in predicting the prognoses of patients with sepsis has been validated. This study aimed to investigate the time course of SIC and SOFA scores and their association with outcomes in patients with sepsis. METHODS: This prospective study enrolled 209 patients with sepsis admitted to the emergency department. The SIC and SOFA scores of the patients were assessed on days 1, 2, and 4. Patients were categorized into survivor or non-survivor groups based on their 28-day survival. We conducted a generalized estimating equation analysis to evaluate the time course of SIC and SOFA scores and the corresponding differences between the two groups. The predictive value of SIC and SOFA scores at different time points for sepsis prognosis was evaluated. RESULTS: In the non-survivor group, SIC and SOFA scores gradually increased during the first 4 days (P < 0.05). In the survivor group, the SIC and SOFA scores on day 2 were significantly higher than those on day 1 (P < 0.05); however, they decreased on day 4, dropping below the levels observed on day 1 (P < 0.05). The non-survivors showed higher SIC scores on days 2 (P < 0.05) and 4 (P < 0.001) than the survivors, whereas no significant differences were found between the two groups on day 1 (P > 0.05). The performance of SIC scores on day 4 for predicting mortality was more accurate than that on day 2, with areas under the curve of 0.749 (95% confidence interval [CI]: 0.674-0.823), and 0.601 (95% CI: 0.524-0.679), respectively. The SIC scores demonstrated comparable predictive accuracy for 28-day mortality to the SOFA scores on days 2 and 4. Cox proportional hazards models indicated that SIC on day 4 (hazard ratio [HR] = 3.736; 95% CI: 2.025-6.891) was an independent risk factor for 28-day mortality. CONCLUSIONS: The time course of SIC and SOFA scores differed between surviving and non-surviving patients with sepsis, and persistent high SIC and SOFA scores can predict 28-day mortality.

The microcirculation in the first days of ICU admission in critically ill COVID-19 patients is influenced by severity of disease.

The objective of this study was to investigate the relationship between sublingual microcirculatory parameters and the severity of the disease in critically ill coronavirus disease 2019 (COVID-19) patients in the initial period of Intensive Care Unit (ICU) admission in a phase of the COVID-19 pandemic where patients were being treated with anti-inflammatory medication. In total, 35 critically ill COVID-19 patients were included. Twenty-one critically ill COVID-19 patients with a Sequential Organ Failure Assessment (SOFA) score below or equal to 7 were compared to 14 critically ill COVID-19 patients with a SOFA score exceeding 7. All patients received dexamethasone and tocilizumab at ICU admission. Microcirculatory measurements were performed within the first five days of ICU admission, preferably as soon as possible after admission. An increase in diffusive capacity of the microcirculation (total vessel density, functional capillary density, capillary hematocrit) and increased perfusion of the tissues by red blood cells was found in the critically ill COVID-19 patients with a SOFA score of 7-9 compared to the critically ill COVID-19 patients with a SOFA score ≤ 7. No such effects were found in the convective component of the microcirculation. These effects occurred in the presence of administration of anti-inflammatory medication.

Prognostic prediction of sepsis patient using transformer with skip connected token for tabular data.

Sepsis is known as a common syndrome in intensive care units (ICU), and severe sepsis and septic shock are among the leading causes of death worldwide. The purpose of this study is to develop a deep learning model that supports clinicians in efficiently managing sepsis patients in the ICU by predicting mortality, ICU length of stay (>14 days), and hospital length of stay (>30 days). The proposed model was developed using 591 retrospective data with 16 tabular data related to a sequential organ failure assessment (SOFA) score. To analyze tabular data, we designed the modified architecture of the transformer that has achieved extraordinary success in the field of languages and computer vision tasks in recent years. The main idea of the proposed model is to use a skip-connected token, which combines both local (feature-wise token) and global (classification token) information as the output of a transformer encoder. The proposed model was compared with four machine learning models (ElasticNet, Extreme Gradient Boosting [XGBoost]), and Random Forest) and three deep learning models (Multi-Layer Perceptron [MLP], transformer, and Feature-Tokenizer transformer [FT-Transformer]) and achieved the best performance (mortality, area under the receiver operating characteristic (AUROC) 0.8047; ICU length of stay, AUROC 0.8314; hospital length of stay, AUROC 0.7342). We anticipate that the proposed model architecture will provide a promising approach to predict the various clinical endpoints using tabular data such as electronic health and medical records.