To investigate the efficacy of amiodarone and lidocaine in cardiac arrest patients.

OBJECTIVE: To assess the relationship between blood pressure reactivity index (BPRI) and in-hospital mortality risk in patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: A retrospective cohort study was conducted to collect data from patients admitted to the intensive care unit (ICU) and clinically diagnosed with SA-AKI between 2008 and 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database in the United States. The collected data included demographic characteristics, comorbidities, vital signs, laboratory parameters, sequential organ failure assessment (SOFA) and simplified acute physiology scoreII(SAPSII) within 48 hours of SA-AKI diagnosis, stages of AKI, treatment regimens, mean BPRI during the first and second 24 hours (BPRI_0_24, BPRI_24_48), and outcome measures including primary outcome (in-hospital mortality) and secondary outcomes (ICU length of stay and total hospital length of stay). Variables with statistical significance in univariate analysis were included in LASSO regression analysis for variable selection, and the selected variables were subsequently incorporated into multivariate Logistic regression analysis to identify independent predictors associated with in-hospital mortality in SA-AKI patients. Restricted cubic spline (RCS) analysis was employed to examine whether there was a linear relationship between BPRI within 48 hours and in-hospital mortality in SA-AKI patients. Basic prediction models were constructed based on the independent predictors identified through multivariate Logistic regression analysis, and receiver operator characteristic curve (ROC curve) was plotted to evaluate the predictive performance of each basic prediction model before and after incorporating BPRI. RESULTS: A total of 3 517 SA-AKI patients admitted to the ICU were included, of whom 826 died during hospitalization and 2 691 survived. The BPRI values within 48 hours of SA-AKI diagnosis were significantly lower in the death group compared with the survival group [BPRI_0_24: 4.53 (1.81, 8.11) vs. 17.39 (5.16, 52.43); BPRI_24_48: 4.76 (2.42, 12.44) vs. 32.23 (8.85, 85.52), all P < 0.05]. LASSO regression analysis identified 20 variables with non-zero coefficients that were included in the multivariate Logistic regression analysis. The results showed that respiratory rate, temperature, pulse oxygen saturation (SpO₂), white blood cell count (WBC), hematocrit (HCT), activated partial thromboplastin time (APTT), lactate, oxygenation index, SOFA score, fluid balance (FB), BPRI_0_24, and BPRI_24_48 were all independent predictors for in-hospital mortality in SA-AKI patients (all P < 0.05). RCS analysis revealed that both BPRI showed "L"-shaped non-linear relationships with the risk of in-hospital mortality in SA-AKI patients. When BPRI_0_24 ≤ 14.47 or BPRI_24_48 ≤ 24.21, the risk of in-hospital mortality in SA-AKI increased as BPRI values decreased. Three basic prediction models were constructed based on the identified independent predictors: Model 1 (physiological indicator model) included respiratory rate, temperature, SpO₂, and oxygenation index; Model 2 (laboratory indicator model) included WBC, HCT, APTT, and lactate; Model 3 (scoring indicator model) included SOFA score and FB. ROC curve analysis showed that the predictive performance of the basic models ranked from high to low as follows: Model 3, Model 2, and Model 1, with area under the curve (AUC) values of 0.755, 0.661, and 0.655, respectively. The incorporation of BPRI indicators resulted in significant improvement in the discriminative ability of each model (all P < 0.05), with AUC values increasing to 0.832 for Model 3+BPRI, 0.805 for Model 2+BPRI, and 0.808 for Model 1+BPRI. CONCLUSIONS BPRI is an independent predictor factor for in-hospital mortality in SA-AKI patients. Incorporating BPRI into the prediction model for in-hospital mortality risk in SA-AKI can significantly improve its predictive capability.
Humans ; Acute Kidney Injury/mortality* ; Sepsis/complications* ; Retrospective Studies ; Hospital Mortality ; Prognosis ; Blood Pressure ; Intensive Care Units ; Male ; Female ; Length of Stay ; Middle Aged ; Aged ; Adult ; Logistic Models

Atypical hemolytic uremic syndrome(aHUS),a rare disease caused by complement abnor-malities,is characterized by microangiopathic hemolytic anemia,thrombocytopenia,and acute kidney injury.In this paper,we report a patient with severe renal insufficiency with rapidly progressive decline in binocular visual acuity,who developed eosinophilia during the course of the disease,and was diagnosed with aHUS after excluding other diseases.After glucocorticoid treatment,eosinophils decreased to normal,and after treatment with plasmapheresis combined with eculizumab,renal function tended to be stable,platelets returned to normal,but visual acuity did not improve significantly.This article reviews the diagnosis and treatment process of this patient and incorporates the review of literature,in the hope of providing reference for clinicians.

OBJECTIVE: To explore the genetic etiology for a Chinese pedigree affected with X-linked cardiac valve dysplasia (CVDPX) and congenital chronic pseudo intestinal obstruction (CIIPX). METHODS: A pedigree presented at the First Hospital of Lanzhou University for CVDPX combined with CIIX was selected as the study subject. Whole exome sequencing (Trio-WES) was carried out, and the candidate variant was verified by Sanger sequencing. This study has been approved by the Medical Ethics Committee of the First Hospital of Lanzhou University (Ethics No. LDYYSZLLKH2024-15). RESULTS: Both the proband and his affected younger brother were found to harbor a hemizygous c.443A>G (p.Tyr148Cys) variant of the FLNA gene, for which their mother was heterozygous and their father was not a carrier, suggesting an X-linked recessive inheritance pattern. The variant was not recorded in the OMIM and ClinVar databases, and was determined to be likely pathogenic (PM2+PS4+PP2+PP3) based on the guidelines from the American College of Medical Genetics and Genomics (ACMG). The patients had presented with typical CVDPX/CIIPX phenotype, including multiple valve dysplasia and chronic pseudo intestinal obstruction, in addition with gallbladder wall edema and thickening. Bioinformatic analysis showed that the variant site is highly conserved, and multiple algorithms had predicted its pathogenicity. CONCLUSION This study confirmed the diagnosis of CVDPX/CIIX in a Chinese pedigree, expanded the phenotype spectrum of FLNA gene variants, and provided a basis for genetic counseling and prenatal diagnosis for the pedigree.
Adult ; Female ; Humans ; Male ; Exome Sequencing ; Filamins/genetics* ; Genetic Diseases, X-Linked/genetics* ; Heart Defects, Congenital/genetics* ; Heart Valve Diseases/genetics* ; Pedigree ; East Asian People/genetics*

BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to find a light-weight,convenient prediction method through machine learning. METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation. RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the five most important features were acuity,arrival transportation,age,shock index,and respiratory rate. CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.

Atypical hemolytic uremic syndrome (aHUS), a rare disease caused by complement abnormalities, is characterized by microangiopathic hemolytic anemia, thrombocytopenia, and acute kidney injury. In this paper, we report a patient with severe renal insufficiency with rapidly progressive decline in binocular visual acuity, who developed eosinophilia during the course of the disease, and was diagnosed with aHUS after excluding other diseases. After glucocorticoid treatment, eosinophils decreased to normal, and after treatment with plasmapheresis combined with eculizumab, renal function tended to be stable, platelets returned to normal, but visual acuity did not improve significantly. This article reviews the diagnosis and treatment process of this patient and incorporates the review of literature, in the hope of providing reference for clinicians.

Objective:To systematically evaluate the effect of different durations of prone ventilation on the efficacy of patients with acute respiratory distress syndrome (ARDS).Methods:A computer search was conducted in databases including PubMed, Cochrane Library, Embase, CNKI, Wanfang Database, VIP Database, and China Biomedical Literature Database for studies on prone ventilation for the treatment of adult patients with ARDS published from the establishment of the database to September 2023. Studies were categorized into ≤24 hours group and > 24 hours group based on the duration of prone ventilation. Outcome indicators included mortality, the length of intensive care unit (ICU) stay, incidence of pressure ulcers, and operation of tracheotomy. Two researchers independently screened the literature, extracted information, and evaluated the risk of bias of the included literature. The quality of the included literature was assessed using the NOS scale, and the effect of different durations of prone ventilation on the efficacy of ARDS was analyzed by Meta-analysis.Results:A total of 517 patients from 4 papers were finally included, including 249 patients with prone ventilation duration ≤24 hours and 268 patients with prone ventilation duration > 24 hours. All 4 studies were cohort studies, and the overall inclusion of literature assessed for methodological quality indicated high study quality and low risk of bias. Meta-analysis showed that there were no significantly differences in mortality [relative risk ( RR) = 1.02, 95% confidence interval (95% CI) was 0.79 to 1.31, P = 0.88], the length of ICU stay [mean difference ( MD) = -2.68, 95% CI was -5.30 to - 0.05, P = 0.05] between the prone ventilation duration ≤ 24 hours group and prone ventilation duration > 24 hours group. Compared with the prone ventilation duration ≤24 hours group, the incidence of pressure ulcers ( RR = 0.76, 95% CI was 0.59 to 0.98, P = 0.04) and the operation of tracheotomy ( RR = 0.71, 95% CI was 0.53 to 0.94, P = 0.02) were significantly increased in the prone ventilation duration > 24 hours group. Conclusions:The duration of prone ventilation had no significant effect on the mortality and the length of ICU stay in ARDS patients, but prone ventilation for > 24 hours increased the incidence of pressure ulcers and the operation of tracheotomy, which still needs to be further verified by a large number of studies due to the small number of included studies.

Objective:To investigate the early clinical characteristics of elderly patients with severe burns and the risk factors on prognosis.Methods:This study was a retrospective case series study. Clinical data of 124 elderly patients with severe burns who met the inclusion criteria and were admitted to the 12 hospitals from January 2015 to December 2020 were collected, including 4 patients from the Fourth People's Hospital of Dalian, 5 patients from Fujian Medical University Union Hospital, 22 patients from Guangzhou Red Cross Hospital of Jinan University, 5 patients from Heilongjiang Provincial Hospital, 27 patients from the First Affiliated Hospital of Naval Medical University, 9 patients from the First Affiliated Hospital of Nanchang University, 10 patients from Affiliated Hospital of Nantong University, 9 patients from Tongren Hospital of Wuhan University & Wuhan Third Hospital, 12 patients from the 924 th Hospital of PLA, 6 patients from Zhangjiagang First People's Hospital, 4 patients from Taizhou Hospital of Zhejiang Province, and 11 patients from Zhengzhou First People's Hospital. The patients' overall clinical characteristics, such as gender, age, body mass index, total burn area, full-thickness burn area, inhalation injury, causative factors, whether combined with underlying medical diseases, and admission time after injury were recorded. According to the survival outcome within 28 days after injury, the patients were divided into survival group (89 cases) and death group (35 cases). The following data of patients were compared between the two groups, including the basic data and injuries (the same as the overall clinical characteristics ahead); the coagulation indexes within the first 24 hours of injury such as prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen degradation product (FDP), international normalized ratio (INR), and fibrinogen; the blood routine indexes within the first 24 hours of injury such as white blood cell count, platelet count, neutrophil-to-lymphocyte ratio, monocyte count, red blood cell count, hemoglobin, and hematocrit; the organ function indexes within the first 24 hours of injury such as direct bilirubin, total bilirubin, urea, serum creatinine, aspartate aminotransferase, alanine aminotransferase, total protein, albumin, globulin, blood glucose, triglyceride, total cholesterol, alkaline phosphatase, creatine kinase, electrolyte indexes (potassium, sodium, chlorine, calcium, magnesium, and phosphorus in blood), uric acid, myoglobin, and brain natriuretic peptide; the infection and blood gas indexes within the first 24 hours of injury such as procalcitonin, C-reactive protein, pH value, oxygenation index, base excess, and lactate; treatment such as whether conducted with mechanical ventilation, whether conducted with continuous renal replacement therapy, whether conducted with anticoagulation therapy, whether applied with vasoactive drugs, and fluid resuscitation. The analysis was conducted to screen the independent risk factors for the mortality within 28 days after injury in elderly patients with severe burns. Results:Among 124 patients, there were 82 males and 42 females, aged 60-97 years, with body mass index of 23.44 (21.09, 25.95) kg/m 2, total burn area of 54.00% (42.00%, 75.00%) total body surface area (TBSA), and full-thickness burn area of 25.00% (10.00%, 40.00%) TBSA. The patients were mainly combined with moderate to severe inhalation injury and caused by flame burns. There were 43 cases with underlying medical diseases. The majority of patients were admitted to the hospital within 8 hours after injury. There were statistically significant differences between patients in the 2 groups in terms of age, total burn area, full-thickness burn area, and inhalation injury, and PT, APTT, D-dimer, FDP, INR, white blood cell count, platelet count, urea, serum creatinine, blood glucose, blood sodium, uric acid, myoglobin, and urine volume within the first 24 hours of injury (with Z values of 2.37, 5.49, 5.26, 5.97, 2.18, 1.95, 2.68, 2.68, 2.51, 2.82, 2.14, 3.40, 5.31, 3.41, 2.35, 3.81, 2.16, and -3.82, respectively, P<0.05); there were statistically significant differences between two groups of patients in whether conducted with mechanical ventilation and whether applied with vasoactive drugs (with χ2 values of 9.44 and 28.50, respectively, P<0.05). Age, total burn area, full-thickness burn area, serum creatinine within the first 24 hours of injury, and APTT within the first 24 hours of injury were the independent risk factors for the mortality within 28 days after injury in elderly patients with severe burns (with odds ratios of 1.17, 1.10, 1.10, 1.09, and 1.27, 95% confidence intervals of 1.03-1.40, 1.04-1.21, 1.05-1.19, 1.05-1.17, and 1.07-1.69, respectively, P<0.05). Conclusions:The elderly patients with severe burns had the injuries mainly from flame burns, often accompanied by moderate to severe inhalation injury and enhanced inflammatory response, elevated blood glucose levels, activated fibrinolysis, and impaired organ function in the early stage, which are associated with their prognosis. Age, total burn area, full-thickness burn area, and serum creatinine and APTT within the first 24 hours of injury are the independent risk factors for death within 28 days after injury in this population.

Objective:To investigate the impact of the early infusion rate on prognosis and the factors of influencing the infusion rate in patients with severe burns and inhalation injury.Methods:This study was a retrospective case series research. From January 2015 to December 2020, 220 patients with severe burns and inhalation injury meeting the inclusion criteria were admitted to 7 burn treatment centers in China, including 13 cases in the Fourth People's Hospital of Dalian, 26 cases in the First Affiliated Hospital of Naval Medical University, 73 cases in Guangzhou Red Cross Hospital of Jinan University, 21 cases in the 924 th Hospital of PLA, 30 cases in the First Affiliated Hospital of Jiangxi Medical College of Nanchang University, 30 cases in Tongren Hospital of Wuhan University & Wuhan Third Hospital, and 27 cases in Zhengzhou First People's Hospital. There were 163 males and 57 females, and their ages ranged from 18 to 91 years. The patients were divided into survival group and death group according to the survival within 28 d post injury. The following data of patients in the 2 groups were collected, including basic information (gender, age, body weight, body temperature, etc.), the injury characteristics (total burn area, post-injury admission time, etc.), the underlying diseases, the post-injury fluid resuscitation condition (infusion rate and ratio of infused electrolyte solution to colloid solution in the first 24 h post injury, etc.), the results of laboratory tests on admission (blood urea nitrogen, blood creatinine, albumin, pH value, base excess, blood lactate, oxygenation index, etc.), and treatment condition (inhaled oxygen volume fraction, hospitalization day, renal replacement therapy, etc.). After adjusting covariates using univariate Cox regression analysis, the multivariate Cox regression analysis was performed to evaluate the impact of infusion rate in the first 24 h post injury on patient death. The receiver operator characteristic curve for the infusion rate in the first 24 h post injury to predict the risk of death was plotted, and the maximum Youden index was calculated. Patients were divided into 2 groups according to the cutoff value (2.03 mL·kg -1·% total body surface area (TBSA) -1) for predicting risk of death by the infusion rate in the first 24 h post injury determined by the maximum Youden index, and the risk of death was compared between the 2 groups. The correlation between the previously mentioned clinical data and the infusion rate in the first 24 h post injury was analyzed; after the univariate linear regression analysis was used to screen the independent variables, the multivariate linear regression analysis was performed to screen the independent influential factors on the infusion rate in the first 24 h post injury. Results:Compared with those in survival group, patients in death group had significantly higher age and total burn area (with Z values of 12.08 and 23.71, respectively, P<0.05), the infusion rate in the first 24 h post injury, inhaled oxygen volume fraction, and blood urea nitrogen, blood creatinine, blood lactic acid on admission (with Z values of 7.99, 4.01, 11.76, 23.24, and 5.97, respectively, P<0.05), and the proportion of patients treated with renal replacement therapy ( P<0.05) were significantly higher, the albumin, pH value, and base excess on admission were significantly lower ( t=2.72, with Z values of 8.18 and 9.70, respectively, P<0.05), and the hospitalization day was significantly reduced ( Z=85.47, P<0.05). After adjusting covariates, the infusion rate in the first 24 h post injury was the independent influential factor on death (with standardized hazard ratio of 1.69, 95% confidence interval of 1.21-2.37, P<0.05). Patients in infusion rate ≥2.03 mL·kg -1·%TBSA -1 group had a significantly higher risk of death than those in infusion rate <2.03 mL·kg -1·% TBSA -1 group (with hazard ratio of 3.47, 95% confidence interval of 1.48-8.13, P<0.05). There was a significant correlation between total burn area, body weight, inhaled oxygen volume fraction, body temperature, post-injury admission time, the ratio of infused electrolyte solution to colloid solution in the first 24 h post injury, and oxygenation index <300 on admission and the infusion rate in the first 24 h post injury (with r values of -0.192, -0.215, 0.137, -0.162, -0.252, and 0.314, respectively, Z=4.48, P<0.05). After screening the independent variables, total burn area, body weight, post-injury admission time, and oxygenation index <300 on admission were the independent influential factors on the infusion rate in the first 24 h post injury (with standardized β values of -0.22, -0.22, -0.19, and 0.46, respectively, 95% confidence intervals of -0.34 to 0.09, -0.34 to 0.10, -0.32 to 0.06, and 0.22 to 0.71, respectively, P<0.05). Conclusions:The infusion rate in the first 24 h post injury in patients with severe burns and inhalation injury is the independent factor of influencing death, and patients with infusion rate ≥2.03 mL·kg -1·%TBSA -1 in the first 24 h post injury have a significantly increased risk of death. The total burn area, body weight, post-injury admission time, and oxygenation index <300 on admission were the independent factors of influencing the infusion rate in the first 24 h post injury in patients with severe burns and inhalation injury.

OBJECTIVE: To investigate the correlation between early-stage blood pressure indexes and prognosis in sepsis patients. METHODS: A retrospective cohort study was conducted on the medical records of patients diagnosed with sepsis from 2001 to 2012 in the Medical Information Mart for Intensive Care-III (MIMIC-III) database. Patients were divided into survival group and death group according to the 28-day prognosis. General data of patients and heart rate (HR) and blood pressure at admission to ICU and within 24 hours after admission were collected. The blood pressure indexes including the maximum, median and mean value of systolic index, diastolic index and mean arterial pressure (MAP) index were calculated. The data were randomly divided into training set and validation set (4 : 1). Univariate Logistic regression analysis was used to screen covariates, and multivariate Logistic stepwise regression models were further developed. Model 1 (including HR, blood pressure, and blood pressure index related variables with P < 0.1 and other variables with P < 0.05) and Model 2 (including HR, blood pressure, and blood pressure index related variables with P < 0.1) were developed respectively. The receiver operator characteristic curve (ROC curve), precision recall curve (PRC) and decision curve analysis (DCA) curve were used to evaluate the quality of the two models, and the influencing factors of the prognosis of sepsis patients were analyzed. Finally, nomogram model was developed according to the better model and effectiveness of it was evaluated. RESULTS: A total of 11 559 sepsis patients were included in the study, with 10 012 patients in the survival group and 1 547 patients in the death group. There were significant differences in age, survival time, Elixhauser comorbidity score and other 46 variables between the two groups (all P < 0.05). Thirty-seven variables were preliminarily screened by univariate Logistic regression analysis. After multivariate Logistic stepwise regression model screening, among the indicators related to HR, blood pressure and blood pressure index, the HR at admission to ICU [odds ratio (OR) = 0.992, 95% confidence interval (95%CI) was 0.988-0.997] and the maximum HR (OR = 1.006, 95%CI was 1.001-1.011), maximum MAP index (OR = 1.620, 95%CI was 1.244-2.126), mean diastolic index (OR = 0.283, 95%CI was 0.091-0.856), median systolic index (OR = 2.149, 95%CI was 0.805-4.461), median diastolic index (OR = 3.986, 95%CI was 1.376-11.758) were selected (all P < 0.1). There were 14 other variables with P < 0.05, including age, Elixhauser comorbidity score, continuous renal replacement therapy (CRRT), use of ventilator, sedation and analgesia, norepinephrine, norepinephrine, highest serum creatinine (SCr), maximum blood urea nitrogen (BUN), highest prothrombin time (PT), highest activated partial thromboplastin time (APTT), lowest platelet count (PLT), highest white blood cell count (WBC), minimum hemoglobin (Hb). The ROC curve showed that the area under the curve (AUC) of Model 1 and Model 2 were 0.769 and 0.637, respectively, indicating that model 1 had higher prediction accuracy. The PRC curve showed that the AUC of Model 1 and Model 2 were 0.381 and 0.240, respectively, indicating that Model 1 had a better effect. The DCA curve showed that when the threshold was 0-0.8 (the probability of death was 0-80%), the net benefit rate of Model 1 was higher than that of Model 2. The calibration curve showed that the prediction effect of the nomogram model developed according to Model 1 was in good agreement with the actual outcome. The Bootstrap verification results showed that the nomogram model was consistent with the above results and had good prediction effects. CONCLUSIONS The nomogram model constructed has good prediction effects on the 28-day prognosis in sepsis patients, and the blood pressure indexes are important predictors in the model.
Humans ; Cohort Studies ; Retrospective Studies ; Blood Pressure ; Intensive Care Units ; ROC Curve ; Sepsis/diagnosis* ; Prognosis ; Critical Care ; Norepinephrine