The association of depressive symptoms with adverse clinical outcomes in hypertension: Data from SPRINT randomized trail.

OBJECTIVE: This study intends to explore the effect of depressive symptoms on adverse clinical outcomes in middle-aged and elderly hypertensive patients. METHODS: This post hoc analysis was conducted using data from the Systolic Blood Pressure Intervention Trial (SPRINT), and we used cox proportional risk regression to examine the relationship between depressive symptoms and adverse clinical outcomes (primary outcome, all-cause mortality, cardiovascular disease(CVD) mortality, heart failure(HF), myocardial infarction(MI), non-myocardial infarction acute coronary syndrome(non-MI ACS)). RESULTS: In a follow-up study of 9259 participants, we found that depression symptoms was significantly and positively associated with the primary outcome (HR 1.03, 95%CI 1.01-1.05; p for trend = 0.0038), all-cause mortality (HR 1.03, 95%CI 1.01-1.05; p for trend = 0.0308), HF(HR 1.05, 95%CI 1.01-1.08; p for trend = 0.0107), and non-MI ACS(HR 1.06, 95%CI 1.01-1.10; p for trend = 0.0120). Kaplan-Meier survival curves for depression symptoms severity (none, mild, moderate, and above) and adverse clinical outcomes suggested that for all but primary clinical outcomes, the cumulative risk of adverse clinical outcomes increased with increasing depression symptoms severity. CONCLUSION: For middle-aged and elderly hypertensive patients, depression symptoms exacerbates the risk of adverse clinical outcomes (primary outcome, all-cause mortality, CVD death, MI, HF, and non-MI ACS), and the risk increases with the severity of depression symptoms.

The relationship between serum ferritin level and clinical outcomes in sepsis based on a large public database.

This study aimed to investigate the relationship between serum ferritin level and prognosis in sepsis. It also explored the potential prognostic value of serum ferritin for predicting outcomes in sepsis based on a large public database. Sepsis patients in MIMIC-IV database were included. Different models including crude model (adjusted for none), model I (adjusted for age and gender) and model II (adjusted for all potential confounders) were performed. Smooth fitting curves were constructed for exploring the relationships between serum ferritin and mortalities of 28-day, 90-day, 180-day and 1-year. Receiver operator characteristic (ROC) curve analysis was utilized for assessing the predictive value of serum ferritin. 1947 sepsis patients were included. The mortalities of 28-day, 90-day, 180-day and 1-year were 20.18% (n = 393), 28.35% (n = 552), 30.30% (n = 590) and 31.54% (n = 614), respectively. In Model II (adjusted for all potential confounders), for every 1000 ng/ml increment in serum ferritin, the values of OR in mortalities of in 28-day, 90-day, 180-day and 1-year were 1.13 (95% CI 1.07-1.19, P < 0.0001), 1.15 (95% CI 1.09-1.21, P < 0.0001), 1.16 (95% CI 1.10-1.22, P < 0.0001) and 1.17 (95% CI 1.10-1.23, P < 0.0001), respectively. The relationships between serum ferritin level and outcomes were non-linear. The areas under the ROC curve (AUC) of ferritin for predicting mortalities of 28-day, 90-day, 180-day and 1-year were 0.597 (95% CI 0.563-0.629), 0.593 (95% CI 0.564-0.621), 0.595 (95% CI 0.567-0.623) and 0.592 (95% CI 0.564-0.620), respectively. The non-linear relationships between serum ferritin and clinical outcomes in sepsis were found. Serum ferritin had a predictive value for short-term and long-term outcomes in sepsis.

Albumin Level is Associated with Short-Term and Long-Term Outcomes in Sepsis Patients Admitted in the ICU: A Large Public Database Retrospective Research.

Objective: This study aimed to explore the relationship between albumin level with short- and long-term outcomes in sepsis patients admitted in the intensive care unit (ICU) based on a large public database to provide clinical evidence for physicians to make individualized plans of albumin supplementation. Methods: Sepsis patients admitted in the ICU in MIMIC-IV were included. Different models were performed to investigate the relationships between albumin and mortalities of 28-day, 60-day, 180-day and 1-year. Smooth fitting curves were performed. Results: A total of 5357 sepsis patients were included. Mortalities of 28-day, 60-day, 180-day and 1-year were 29.29% (n = 1569), 33.92% (n = 1817), 36.70% (n = 1966) and 37.71% (n = 2020). In the fully adjusted model (adjusted for all potential confounders), with each 1g/dL increment in albumin level, the risk of mortality in 28-day, 60-day, 180-day and 1-year decreased by 39% (OR = 0.61, 95% CI: 0.54-0.69), 34% (OR = 0.66, 95% CI: 0.59-0.73), 33% (OR = 0.67, 95% CI: 0.60-0.75), and 32% (OR = 0.68, 95% CI: 0.61-0.76), respectively. The non-linear negative relationships between albumin and clinical outcomes were confirmed by smooth fitting curves. The turning point of albumin level was 2.6g/dL for short- and long-term clinical outcomes. When albumin level ≤2.6g/dL, with each 1g/dL increment in albumin level, the risk of mortality in 28-day, 60-day, 180-day and 1-year decreased by 59% (OR = 0.41, 95% CI: 0.32-0.52), 62% (OR = 0.38, 95% CI: 0.30-0.48), 65% (OR = 0.35, 95% CI: 0.28-0.45), and 62% (OR = 0.38, 95% CI: 0.29-0.48), respectively. Conclusion: Albumin level was associated with short- and long-term outcomes in sepsis. Albumin supplementation might be beneficial for septic patients with serum albumin<2.6g/dL.

Early predicting 30-day mortality in sepsis in MIMIC-III by an artificial neural networks model.

OBJECTIVE: Early identifying sepsis patients who had higher risk of poor prognosis was extremely important. The aim of this study was to develop an artificial neural networks (ANN) model for early predicting clinical outcomes in sepsis. METHODS: This study was a retrospective design. Sepsis patients from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were enrolled. A predictive model for predicting 30-day morality in sepsis was performed based on the ANN approach. RESULTS: A total of 2874 patients with sepsis were included and 30-day mortality was 29.8%. The study population was categorized into the training set (n = 1698) and validation set (n = 1176) based on the ratio of 6:4. 11 variables which showed significant differences between survivor group and nonsurvivor group in training set were selected for constructing the ANN model. In training set, the predictive performance based on the area under the receiver-operating characteristic curve (AUC) were 0.873 for ANN model, 0.720 for logistic regression, 0.629 for APACHEII score and 0.619 for SOFA score. In validation set, the AUCs of ANN, logistic regression, APAHCEII score, and SOFA score were 0.811, 0.752, 0.607, and 0.628, respectively. CONCLUSION: An ANN model for predicting 30-day mortality in sepsis was performed. Our predictive model can be beneficial for early detection of patients with higher risk of poor prognosis.

Different clinical characteristics between recurrent and non-recurrent acute pancreatitis: A retrospective cohort study from a tertiary hospital.

Background: Acute pancreatitis (AP) is a common digestive disorder with different clinical outcomes, some of which develop into recurrent acute pancreatitis (RAP). This study aimed to explore the differences between AP and RAP. Methods: All patients with AP admitted to Changsha Central Hospital between January 2015 and December 2020 were included. Characteristics between RAP and non-RAP groups were compared. Independent factors associated with RAP were identified by multivariate logistic regression analyses. Results: This was a retrospective study. A total of 1567 patients, including 262 patients in the RAP group and 1305 patients in the non-RAP group, were enrolled. Compared to the non-RAP group, results indicated that the RAP group was younger (P < 0.001), had a male predominance (P < 0.001), and had higher incidences of diabetes (P < 0.001) and hypertriglyceridemia (HTG) (P < 0.001). Lower incidences of cholelithiasis (P < 0.001) and acute liver injury (P < 0.001) were also noted in the RAP group. Scores of Ranson, BISAP, SOFA, and APACHE II were significantly higher in the non-RAP group (P < 0.001 for all). Three independent factors associated with RAP, including male gender (P = 0.006), diabetes (P < 0.001), and HTG (P < 0.001), were identified by multivariate logistic regression. Conclusion: Compared to the non-RAP, the incidence of cholelithiasis and acute liver injury was lower in RAP. Three independent factors associated with RAP, namely male, diabetes, and HTG, were identified.

Factors associated with in-hospital mortality in adult sepsis with Escherichia coli infection.

BACKGROUND: Escherichia coli (E. coli) is an important pathogen in sepsis. This study aimed to explore the factors which were associated with in-hospital mortality in adult sepsis with E. coli infection based on a public database. METHODS: All sepsis patients with E. coli infection in MIMIC-III were included in this study. Clinical characteristics between the survivor and non-survivor groups were analyzed. Factors associated with in-hospital mortality were identified by multivariate logistic regression. RESULTS: A total of 199 patients were eventually included and divided into two groups: a survivor group (n = 167) and a non-survivor group (n = 32). RDW and HCT were identified as the factors with clinical outcomes. The area under the ROC curve (AUC) were 0.633 and 0.579, respectively. When combined RDW and HCT for predicting in-hospital mortality, the AUC was 0.772, which was significantly superior to SOFA and APACHEII scores. CONCLUSION: RDW and HCT were identified as factors associated with in-hospital mortality in adult sepsis patients with E. coli infection. Our findings will be of help in early and effective evaluation of clinical outcomes in those patients.

Nomogram for the Prediction of In-Hospital Incidence of Acute Respiratory Distress Syndrome in Patients with Acute Pancreatitis.

BACKGROUND: Acute respiratory distress syndrome (ARDS) associated with high mortality is the common complication in acute pancreatitis (AP). The aim of this study was to formulate and validate an individualized predictive nomogram for in-hospital incidence of ARDS in Patients with AP. METHODS: From January 2017 to December 2018, 779 individuals with AP were involved in this study. They were randomly distributed into primary cohort (n = 560) and validation cohort (n = 219). Based on the primary cohort, risk factors were identified by logistic regression model and a nomogram was performed. The nomogram was validated in the primary and validation cohort by the bootstrap validation method. The calibration curve was applied to evaluate the consistency between the nomogram and the ideal observation. RESULTS: There were 728 patients in the non-ARDS group and 51 in the ARDS group, with an incidence of about 6.55%. Five independent factors including white blood cell counts (WBC), prothrombin time (PT), albumin (ALB), serum creatinine (SCR) and triglyceride (TG) were associated with in-hospital incidence of ARDS in Patients with AP. A nomogram was constructed based on the five independent factors with primary cohort of AUC = 0.821 and validation cohort of AUC = 0.823. Calibration curve analysis indicated that the predicted probability was in accordance with the observed probability in both primary and validation cohorts. CONCLUSIONS: The study developed an intuitive nomogram with easily available laboratory parameters for the prediction of in-hospital incidence of ARDS in patients with AP. The incidence of ARDS for an individual patient can be fast and conveniently evaluated by our nomogram.

A non-linear positive relationship between serum phosphate and clinical outcomes in sepsis.

Objective: This study aimed to evaluate the possible relationship between serum phosphate and short-term outcomes in sepsis. Methods: This was a retrospective study. Sepsis patients in MIMIC-IV database were included. Based on the quartiles of serum phosphate, all sepsis patients were divided into four groups. Univariable and multivariable regression analyses were constructed for discussing the relationship between different parameters and 30-day mortality in sepsis. A generalized additive model was performed for exploring the association of serum phosphate with 30-day mortality. Results: 6251 sepsis patients including 4368 survivors and 1883 non-survivors were included. A significant relationship between serum phosphate and 30-day mortality was found after adjusting for all potential confounders (OR = 1.19, 95%CI:1.13-1.26, P < 0.0001). The relationship was non-linear with an inflection point of 6.8 mg/dl. On the left side of the inflection point (≤6.8 mg/dl, n = 5911 (94.56%)), the OR was 1.24 (95%CI: 1.17-1.31, P < 0.0001). On the right side of the inflection point (>6.8 mg/dl, n = 340 (5.44%)), the OR was 0.94 (95%CI:0.78-1.13, P = 0.5038). Conclusion: A non-linear positive relationship was found between serum phosphate and 30-day mortality in sepsis. Serum phosphate was associated with mortality in sepsis. Our results could be used for screening out those sepsis patients with higher risk of worse outcomes.

Risk Factors of Recurrence of Acute Pancreatitis: A Retrospective Research.

BACKGROUND: Acute pancreatitis (AP) was one of the most common disorders of acute hospital admission with significant morbidity and mortality. Some of the patients experienced recurrent attacks of AP, leading to recurrent acute pancreatitis (RAP) and poor clinical outcomes. The association of clinical and laboratory variables with recurrence of AP were analyzed to evaluate the risk of RAP. METHODS: All patients with AP admitted in the hospital between January 2017 and December 2019 were included in this study. Clinical and laboratory variables were analyzed and risk factors were identified by multivariate logistic regression. The receiver operating characteristic (ROC) analysis for predicting recurrence of AP was performed. RESULTS: A total of 834 AP patients, including 671 in the non-RAP group and 167 in the RAP group, were enrolled in the study. There were significant differences in age, sex, body mass index (BMI), history of biliary surgery, cholelithiasis, diabetes, triglyceride (TG), high-density lipoprotein, and cholesterol between the non-RAP group and the RAP group. Two independent variables were identified as risk factors for recurrence of AP: TG (P = .007, odds ratio [OR] = 1.101, 95% CI, 1.025-1.183), and BMI (P = .032, OR = 1.094, 95% CI, 1.009-1.086). The area under the curve of ROC analysis of TG and BMI were 0.702 (95% CI, 0.655-0.749) and 0.593 (95% CI, 0.538-0.647). The best threshold for TG and BMI to anticipate recurrence of AP were 5.9 (sensitivity0.763, specificity 0.595) and 28.24 (sensitivity 0.302, specificity 0.844). CONCLUSION: TG and BMI were identified as independent predictors for recurrence of AP. A TG level of 5.9 mmol/L could be a clinical guide for the target level of lowering TG therapy in AP patients with hypertriglyceridemia.

Clinical Characteristics of Aortic Aneurysm in MIMIC-III.

BACKGROUND: Aortic aneurysm (AA) is an aortic disorder prone to sudden, life-threatening aortic dissection or rupture, with poor clinical outcomes. In this study, we aimed to analyze the clinical characteristics of AA in MIMIC-III to explore implications for management. METHODS: All patients with AA, including abdominal aortic aneurysm (AAA) and thoracic aortic aneurysm (TAA), in the MIMIC-III database were included. Clinical and laboratory variables were analyzed and compared in AAA and TAA. RESULTS: A total of 345 patients, including 183 patients with AAA and 162 patients with TAA, were enrolled in this study. The in-hospital mortality in AAA and TAA groups was 6.01% and 3.7%, respectively. In the nonsurvivor groups in both AAA and TAA, patients were older, and the incidence of surgery was lower. In the nonsurvivor group of AAA, the levels of alanine aminotransferase, aspartate aminotransferase, urea nitrogen, creatinine, lactate dehydrogenase (LDH), creatine kinase, anion gap, and lactate were significantly higher in the nonsurvivor group, whereas the level of albumin was lower. In the nonsurvivor group of TAA, the level of LDH significantly increased and the level of albumin decreased. In the nonsurgery group, in-hospital mortality was higher, and patients were older, with higher levels of glucose, total bilirubin, urea nitrogen, and creatinine and longer length of stay in ICU and hospital. CONCLUSION: Age, surgery, albumin, and LDH showed significant differences between survivor and nonsurvivor groups in both AAA and TAA. In the nonsurgery group, the mean age was older and disease severity was worse, with poorer clinical outcomes. Older AA patients without surgery and with lower levels of albumin and higher levels of LDH had higher risk of in-hospital mortality.

An Artificial Neural Networks Model for Early Predicting In-Hospital Mortality in Acute Pancreatitis in MIMIC-III.

BACKGROUND: Early and accurate evaluation of severity and prognosis in acute pancreatitis (AP), especially at the time of admission is very significant. This study was aimed to develop an artificial neural networks (ANN) model for early prediction of in-hospital mortality in AP. METHODS: Patients with AP were identified from the Medical Information Mart for Intensive Care-III (MIMIC-III) database. Clinical and laboratory data were utilized to perform a predictive model by back propagation ANN approach. RESULTS: A total of 337 patients with AP were analyzed in the study, and the in-hospital mortality rate was 11.2%. A total of 12 variables that differed between patients in survivor group and nonsurvivor group were applied to construct ANN model. Three independent variables were identified as risk factors associated with in-hospital mortality by multivariate logistic regression analysis. The predictive performance based on the area under the receiver operating characteristic curve (AUC) was 0.769 for ANN model, 0.607 for logistic regression, 0.652 for Ranson score, and 0.401 for SOFA score. CONCLUSION: An ANN predictive model for in-hospital mortality in patients with AP in MIMIC-III database was first performed. The patients with high risk of fatal outcome can be screened out easily in the early stage of AP by our model.

Association of clinical and laboratory variables with in-hospital incidence of deep vein thrombosis in patients after acute ischemic stroke: A retrospective study.

ABSTRACT: Deep vein thrombosis (DVT) is a serious complication in patients with acute ischemic stroke (AIS). Early prediction of DVT could enable physicians to perform a proper prevention strategy. We analyzed the association of clinical and laboratory variables with DVT to evaluate the risk of DVT in patients after AIS.AIS patients admitted to the Changsha Central Hospital between January 2017 and December 2019 with length of stay in hospital ≥7 days were included. Clinical and laboratory variables for DVT at baseline were collected, and the diagnosis of DVT was confirmed by ultrasonography. Independent factors were developed by Multivariate logistic regression analysis.A total of 101 patients were included in the study. The in-hospital incidence of DVT after AIS was 19.8%(20/101). The average level of D-dimer when DVT detected was significant increased around 4-fold than that on admission (P < .001). Pulmonary infection (odds ratio [OR] = 5.4, 95%CI:1.10-26.65, P = .037)) and increased muscle tone (OR = 0.11, 95%CI:0.02-0.58, P = .010) as independent relevant factors for DVT were confirmed.Pulmonary infection as a risk factor and increased muscle tone as a protective factor for DVT were identified in patients after AIS. The level of D-dimer which increased around 4-fold compared to the initial level could be an indicator for DVT occurrence.