Risk factors prediction of 6-month mortality after noncardiac surgery of older patients in China: a multicentre retrospective cohort study.

BACKGROUND: Identifying the risk factors associated with perioperative mortality is crucial, particularly in older patients. Predicting 6-month mortality risk in older patients based on large datasets can assist patients and surgeons in perioperative clinical decision-making. This study aimed to develop a risk prediction model of mortality within 6 months after noncardiac surgery using the clinical data from 11 894 older patients in China. MATERIALS AND METHODS: A multicentre, retrospective cohort study was conducted in 20 tertiary hospitals. The authors retrospectively included 11 894 patients (aged ≥65 years) who underwent noncardiac surgery between April 2020 and April 2022. The least absolute shrinkage and selection operator model based on linear regression was used to analyse and select risk factors, and various machine learning methods were used to build predictive models of 6-month mortality. RESULTS: The authors predicted 12 preoperative risk factors associated with 6-month mortality in older patients after noncardiac surgery. Including laboratory-associated risk factors such as mononuclear cell ratio and total blood cholesterol level, etc. Also including medical history associated risk factors such as stroke, history of chronic diseases, etc. By using a random forest model, the authors constructed a predictive model with a satisfactory accuracy (area under the receiver operating characteristic curve=0.97). CONCLUSION: The authors identified 12 preoperative risk factors associated with 6-month mortality in noncardiac surgery older patients. These preoperative risk factors may provide evidence for a comprehensive preoperative anaesthesia assessment as well as necessary information for clinical decision-making by anaesthesiologists.

Mental health changes in elderly patients undergoing non-cardiac surgery during the COVID-19 pandemic in China.

BACKGROUND: The COVID-19 pandemic has a heavy impact on the mental health of elderly surgical patients worldwide. In particular, the elderly patients faced considerable psychological stress due to various environmental and medical factors during the outbreak. This study aims to examine changes in mental health trends among non-cardiac surgical patients aged 65 and above in China during the COVID-19 pandemic. METHODS: This multi-center, convenient sampling, longitudinal observational study was conducted from April 1, 2020 to April 30, 2022. Primary outcome was the prevalence of postoperative depression. Secondary outcome was the prevalence of postoperative anxiety. Follow-up was conducted separately at 7 days and 30 days after surgery. Depression symptoms were assessed using the Patient Health Questionnaire 9 (PHQ-9) scale. Anxiety symptoms were assessed using Generalized Anxiety Disorder-7 (GAD-7) scale, with scores of ≥5 defining positive depression or anxiety symptoms. Multivariate logistic regression analysis was used to investigate risk factors of mental health status in more elderly patients undergoing non-cardiac surgery. RESULTS: A total of 4639 patients were included, of whom 2279 (46.0 %) were male, 752 (15.2 %) were over the age of 75, and 4346 (93.7 %) were married. The monthly prevalence trends demonstrated that compared to the outbreak period, a significant reduction in the prevalence of depression and anxiety symptoms in elderly patients who underwent surgery during the post-pandemic period. In post-pandemic period, a statistically significant decrease in the prevalence of all severity depression and anxiety patients was noted at the 7-day follow-up, but no significant decrease was observed for severe depression and anxiety in the 30-day follow-up. In COVID-19 low-risk area, a significant overall decrease in prevalence of mental health was observed during the post-pandemic period compared to the outbreak period, including 7-day depression, 7-day anxiety, 30-day depression, and 30-day anxiety (all with P < 0.001). Female and patients with ≥2 comorbidities appeared to be more susceptible to postoperative depression and anxiety during the pandemic. LIMITATION: The absence of data from the early days of the COVID-19 outbreak. CONCLUSIONS: This study analyzed the prevalence of depression and anxiety in elderly non-cardiac patients during and after the COVID-19 pandemic, focusing on dimensions such as severity, risk-areas, gender, and comorbidity. Our findings revealed a significant decrease in the prevalence of depression and anxiety in elderly surgery patients during the post-pandemic period.

[Prognosis of patients planned and unplanned admission to the intensive care unit after surgery: a comparative study].

OBJECTIVE: To compare and analyze the effect of unplanned versus planned admission to the intensive care unit (ICU) on the prognosis of high-risk patients after surgery, so as to provide a clinical evidence for clinical medical staff to evaluate whether the postoperative patients should be transferred to ICU or not after surgery. METHODS: The clinical data of patients who were transferred to ICU after surgery admitted to the Affiliated Hospital of Guizhou Medical University from January to December in 2021 were retrospectively analyzed, including gender, age, body mass index, past history (whether combined with hypertension, diabetes, pulmonary disease, cardiac disease, renal failure, liver failure, hematologic disorders, tumor, etc.), acute physiology and chronic health evaluation II (APACHE II), elective surgery, pre-operative hospital consultation, length of surgery, worst value of laboratory parameters within 24 hours of ICU admission, need for invasive mechanical ventilation (IMV), duration of IMV, length of ICU stay, total length of hospital stay, ICU mortality, in-hospital mortality, and survival status at 30th day postoperative. The unplanned patients were further divided into the immediate transfer group and delayed transfer group according to the timing of their ICU entrance after surgery, and the prognosis was compared between the two groups. Cox regression analysis was used to find the independent risk factors of 30-day mortality in patients transferred to ICU after surgery. RESULTS: Finally, 377 patients were included in the post-operative admission to the ICU, including 232 in the planned transfer group and 145 in the unplanned transfer group (42 immediate transfers and 103 delayed transfers). Compared to the planned transfer group, patients in the unplanned transfer group had higher peripheral blood white blood cell count (WBC) at the time of transfer to the ICU [×109/L: 10.86 (7.09, 16.68) vs. 10.11 (6.56, 13.27)], longer total length of hospital stay [days: 23.00 (14.00, 34.00) vs. 19.00 (12.00, 29.00)], and 30-day post-operative mortality was higher [29.66% (43/145) vs. 17.24% (40/232)], but haemoglobin (Hb), arterial partial pressure of carbon dioxide (PaCO2), oxygenation index (PaO2/FiO2), and IMV requirement rate were lower [Hb (g/L): 95.00 (78.00, 113.50) vs. 98.00 (85.00, 123.00), PaCO2 (mmHg, 1 mmHg ≈ 0.133 kPa): 36.00 (29.00, 41.50) vs. 39.00 (33.00, 43.00), PaO2/FiO2 (mmHg): 197.00 (137.50, 283.50) vs. 238.00 (178.00, 350.25), IMV requirement rate: 82.76% (120/145) vs. 93.97% (218/232)], all differences were statistically significant (all P < 0.05). Kaplan-Meier survival curve showed that the 30-day cumulative survival rate after surgery was significantly lower in the unplanned transfer group than in the planned transfer group (Log-Rank test: χ2 = 7.659, P = 0.006). Univariate Cox regression analysis showed that unplanned transfer, APACHE II score, whether deeded IMV at transfer, total length of hospital stay, WBC, blood K+, and blood lactic acid (Lac) were associated with 30-day mortality after operation (all P < 0.05). Multifactorial Cox analysis showed that unplanned transfer [hazard ratio (HR) = 2.45, 95% confidence interval (95%CI) was 1.54-3.89, P < 0.001], APACHE II score (HR = 1.03, 95%CI was 1.00-1.07, P = 0.031), the total length of hospital stay (HR = 0.86, 95%CI was 0.83-0.89, P < 0.001), the need for IMV on admission (HR = 4.31, 95%CI was 1.27-14.63, P = 0.019), highest Lac value within 24 hours of transfer to the ICU (HR = 1.17, 95%CI was 1.10-1.24, P < 0.001), and tumor history (HR = 3.12, 95%CI was 1.36-7.13, P = 0.007) were independent risk factors for patient death at 30 days post-operative, and the risk of death was 2.45 times higher in patients unplanned transferred than in those planned transferred. Subgroup analysis showed that patients in the delayed transfer group had significantly longer IMV times than those in the immediate transfer group [hours: 43.00 (11.00, 121.00) vs. 17.50 (2.75, 73.00), P < 0.05]. CONCLUSIONS: The 30-day mortality, WBC and total length of hospital stay were higher in patients who were transferred to ICU after surgery, and PaO2/FiO2 was lower. Unplanned transfer, oncology history, use of IMV, APACHE II score, total length of hospital stay, and Lac were independent risk factors for patient death at 30 days postoperatively, and patients with delayed transfer to ICU had longer IMV time.

[Prevalence, risk factors and characteristics of delirium in intensive care unit patients: a prospective observational study].

OBJECTIVE: To investigate the prevalence, risk factors, duration and outcome of delirium in intensive care unit (ICU) patients. METHODS: A prospective observational study was conducted for critically ill patients admitted to the department of critical care medicine, the Affiliated Hospital of Guizhou Medical University from September to November 2021. Delirium assessments were performed twice daily using the Richmond agitation-sedation scale (RASS) and confusion assessment method of ICU (CAM-ICU) for patients who met the inclusions and exclusion criteria. Patient's age, gender, body mass index (BMI), underlying disease, acute physiologic assessment and chronic health evaluation (APACHE) at ICU admission, sequential organ failure assessment (SOFA) at ICU admission, oxygenation index (PaO2/FiO2), diagnosis, type of delirium, duration of delirium, outcome, etc. were recorded. Patients were divided into delirium and non-delirium groups according to whether delirium occurred during the study period. The clinical characteristics of the patients in the two groups were compared, and risk factors for the development of delirium were screened using univariate analysis and multivariate Logistic regression analysis. RESULTS: A total of 347 ICU patients were included, and delirium occurred in 57.6% (200/347) patients. The most common type was hypoactive delirium (73.0% of the total). Univariate analysis showed statistically significant differences in age, APACHE score and SOFA score at ICU admission, history of smoking, hypertension, history of cerebral infarction, immunosuppression, neurological disease, sepsis, shock, glucose (Glu), PaO2/FiO2 at ICU admission, length of ICU stay, and duration of mechanical ventilation between the two groups. Multivariate Logistic regression analysis showed that age [odds ratio (OR) = 1.045, 95% confidence interval (95%CI) was 1.027-1.063, P < 0.001], APACHE score at ICU admission (OR = 1.049, 95%CI was 1.008-1.091, P = 0.018), neurological disease (OR = 5.275, 95%CI was 1.825-15.248, P = 0.002), sepsis (OR = 1.941, 95%CI was 1.117-3.374, P = 0.019), and duration of mechanical ventilation (OR = 1.005, 95%CI was 1.001-1.009, P = 0.012) were all independent risk factors for the development of delirium in ICU patients. The median duration of delirium in ICU patients was 2 (1, 3) days. Delirium was still present in 52% patients when they discharged from the ICU. CONCLUSIONS: The prevalence of delirium in ICU patients is over 50%, with hypoactive delirium being the most common. Age, APACHE score at ICU admission, neurological disease, sepsis and duration of mechanical ventilation were all independent risk factors for the development of delirium in ICU patients. More than half of patients with delirium were still delirious when they discharged from the ICU.

Dexmedetomidine attenuates inflammation and organ injury partially by upregulating Nur77 in sepsis.

PURPOSE: The aim of this study was to investigate the effect of dexmedetomidine (Dex) on inflammation and organ injury in sepsis, as well as the potential relationship between Dex and nuclear receptor 77 (Nur77). METHODS: We investigated the effects of dexmedetomidine on lipopolysaccharide (LPS)-induced inflammation in RAW264.7 cells and organ injury in the cecal ligation and puncture (CLP) mouse model. Additionally, we examined the relationship between dexmedetomidine and Nur77. The expression levels of Nur77 in RAW264.7 cells were analyzed under various types of stimulation using quantitative reverse transcription polymerase chain reaction and western blot analysis. Inflammatory cytokine levels in the cells were evaluated using enzyme-linked immunoassay. Organ injuries were assessed by examining tissue histology and pathology of the lung, liver, and kidney. RESULTS: Dexmedetomidine increased the expression of Nur77 and IL-10, and downregulated inflammatory cytokines (IL-1ß and TNF-α) in LPS-treated RAW264.7 cells. The effect of dexmedetomidine on inhibiting inflammation in LPS-treated RAW264.7 cells was promoted by overexpressing Nur77, while it was reversed by downregulating Nur77. Additionally, dexmedetomidine promoted the expression of Nur77 in the lung and CLP-induced pathological changes in the lung, liver, and kidney. Activation of Nur77 with the agonist Cytosporone B (CsnB) significantly suppressed the production of IL-1ß and TNF-α in LPS-treated RAW264.7 cells. In contrast, knockdown of Nur77 augmented IL-1ß and TNF-α production in LPS-treated RAW264.7 cells. CONCLUSION: Dexmedetomidine can attenuate inflammation and organ injury, at least partially, via upregulating Nur77 in sepsis.

Effect of an Herbal-Based Injection on 28-Day Mortality in Patients With Sepsis: The EXIT-SEP Randomized Clinical Trial.

Importance: Previous research has suggested that Xuebijing injection (XBJ), an herbal-based intravenous preparation, may reduce mortality among patients with sepsis. Objective: To determine the effect of XBJ vs placebo on 28-day mortality among patients with sepsis. Design, Setting, and Participants: The Efficacy of Xuebijing Injection in Patients With Sepsis (EXIT-SEP) trial was a multicenter, randomized double-blind, placebo-controlled trial conducted in intensive care units at 45 sites and included 1817 randomized patients with sepsis (sepsis 3.0) present for less than 48 hours. Patients aged 18 to 75 years with a Sequential Organ Failure Assessment score of 2 to 13 were enrolled. The study was conducted from October 2017 to June 2019. The final date of follow-up was July 26, 2019. Data analysis was performed from January 2020 to August 2022. Interventions: The patients were randomized to receive either intravenous infusion of XBJ (100 mL, n = 911) or volume-matched saline placebo (n = 906) every 12 hours for 5 days. Main Outcomes and Measures: The primary outcome was 28-day mortality. Results: Among the 1817 patients who were randomized (mean [SD] age, 56.5 [13.5] years; 1199 [66.0%] men), 1760 (96.9%) completed the trial. In these patients, the 28-day mortality rate was significantly different between the placebo group and the XBJ group (230 of 882 patients [26.1%] vs 165 of 878 patients [18.8%], respectively; P < .001). The absolute risk difference was 7.3 (95% CI, 3.4-11.2) percentage points. The incidence of adverse events was 222 of 878 patients (25.3%) in the placebo group and 200 of 872 patients (22.9%) in the XBJ group. Conclusions and Relevance: In this randomized clinical trial among patients with sepsis, the administration of XBJ reduced 28-day mortality compared with placebo. Trial Registration: ClinicalTrials.gov Identifier: NCT03238742.

Safety, tolerability, pharmacokinetics, and efficacy of kukoamine B in patients with sepsis: A randomized phase IIa trial.

PURPOSE: To evaluate the safety, tolerability, pharmacokinetics, and efficacy of kukoamine B (KB), an alkaloid compound with high affinity for both lipopolysaccharide (LPS) and oligodeoxynucle-otides containing CpG motifs (CpG DNA), in patients with sepsis-induced organ failure. MATERIALS AND METHODS: This was a multicenter, randomized, double-blind, placebo-controlled phase IIa trial. Patients with sepsis-induced organ failure were randomized to receive either KB (0.06, 0.12, or 0.24 mg/kg) or placebo, every 8 h for 7 days. Primary endpoint was safety, and secondary endpoints included pharmacokinetic (PK) parameters, changes in inflammatory mediators' level, and prognostic parameters. RESULTS: Of 44 patients enrolled, adverse events occurred in 28 patients [n = 20, 66.7% (KB pooled); n = 8, 57.1% (placebo)], while treatment emergent adverse events were reported in 14 patients [n = 10, 33.3% (KB pooled); n = 4, 28.6% (placebo)]. Seven patients died at 28-day follow-up [n = 4, 13.3% (KB pooled); n = 3, 21.4% (placebo)], none was related to study drug. PK parameters suggested dose-dependent drug exposure and no drug accumulation. KB did not affect clinical outcomes such as ΔSOFA score, vasopressor-free days or ventilator-free days. CONCLUSIONS: In patients with sepsis-induced organ failure, KB was safe and well tolerated. Further investigation is warranted. TRIAL REGISTRATION: http://ClinicalTrials.gov, NCT03237728.

[Factors influencing pulmonary infection in elderly neurocritical patients and their predictive values: a data analysis for consecutive four-year].

OBJECTIVE: To analyze the factors influencing pulmonary infections in elderly neurocritical patients in the intensive care unit (ICU) and to explore the predictive value of risk factors for pulmonary infections. METHODS: The clinical data of 713 elderly neurocritical patients [age ≥ 65 years, Glasgow coma score (GCS) ≤ 12 points] admitted to the department of critical care medicine of the Affiliated Hospital of Guizhou Medical University from 1 January 2016 to 31 December 2019 were retrospectively analyzed. According to whether or not they had HAP, the elderly neurocritical patients were divided into hospital-acquired pneumonia (HAP) group and non-HAP group. The differences in baseline data, medication and treatment, and outcome indicators between the two groups were compared. Logistic regression analysis was used to analyze the factors influencing the occurrence of pulmonary infection. The receiver operator characteristic curve (ROC curve) was plotted for risk factors and a predictive model was constructed to evaluate the predictive value for pulmonary infection. RESULTS: A total of 341 patients were enrolled in the analysis, including 164 non-HAP patients and 177 HAP patients. The incidence of HAP was 51.91%. According to univariate analysis, compared with the non-HAP group, mechanical ventilation time, the length of ICU stay and total hospitalization in the HAP group were significantly longer [mechanical ventilation time (hours): 171.00 (95.00, 273.00) vs. 60.17 (24.50, 120.75), the length of ICU stay (hours): 263.50 (160.00, 409.00) vs. 114.00 (77.05, 187.50), total hospitalization (days): 29.00 (13.50, 39.50) vs. 27.00 (11.00, 29.50), all P < 0.01], the proportion of open airway, diabetes, proton pump inhibitor (PPI), sedative, blood transfusion, glucocorticoids, and GCS ≤ 8 points were significantly increased than those in HAP group [open airway: 95.5% vs. 71.3%, diabetes: 42.9% vs. 21.3%, PPI: 76.3% vs. 63.4%, sedative: 93.8% vs. 78.7%, blood transfusion: 57.1% vs. 29.9%, glucocorticoids: 19.2% vs. 4.3%, GCS ≤ 8 points: 83.6% vs. 57.9%, all P < 0.05], prealbumin (PA) and lymphocyte count (LYM) decreased significantly [PA (g/L): 125.28±47.46 vs. 158.57±54.12, LYM (×109/L): 0.79 (0.52, 1.23) vs. 1.05 (0.66, 1.57), both P < 0.01]. Logistic regression analysis showed that open airway, diabetes, blood transfusion, glucocorticoids and GCS ≤ 8 points were independent risk factors for pulmonary infection in elderly neurocritical patients [open airway: odds ratio (OR) = 6.522, 95% confidence interval (95%CI) was 2.369-17.961; diabetes: OR = 3.917, 95%CI was 2.099-7.309; blood transfusion: OR = 2.730, 95%CI was 1.526-4.883; glucocorticoids: OR = 6.609, 95%CI was 2.273-19.215; GCS ≤ 8 points: OR = 4.191, 95%CI was 2.198-7.991, all P < 0.01], and LYM, PA were the protective factors for pulmonary infection in elderly neurocritical patients (LYM: OR = 0.508, 95%CI was 0.345-0.748; PA: OR = 0.988, 95%CI was 0.982-0.994, both P < 0.01). ROC curve analysis showed that the area under the ROC curve (AUC) for predicting HAP using the above risk factors was 0.812 (95%CI was 0.767-0.857, P < 0.001), with a sensitivity of 72.3% and a specificity of 78.7%. CONCLUSIONS: Open airway, diabetes, glucocorticoids, blood transfusion, GCS ≤ 8 points are independent risk factors for pulmonary infection in elderly neurocritical patients. The prediction model constructed by the above mentioned risk factors has certain predictive value for the occurrence of pulmonary infection in elderly neurocritical patients.

Clinical Characteristics and the Effect of Timing for Metagenomic Next-Generation Sequencing in Critically Ill Patients with Sepsis.

Background: Metagenomic next-generation sequencing (mNGS) has a good performance for the identification of pathogens in infectious diseases, but few studies on the clinical characteristics of mNGS and the effect of timing for mNGS in critically ill patients with sepsis. Methods: We retrospectively included all patients diagnosed with sepsis after admission to the intensive care unit (ICU) of a university-affiliated hospital between Aug 1, 2019 and Apr 1, 2021. During the study period, pathogens for all enrolled subjects were obtained by mNGS. We analyzed the composition and positive rate of different samples type for mNGS. And then we used the univariable and multivariable logistic regression to explore the risk factors associated with all-cause mortality at 28 days. Results: A total of 87 patients were included and 87 samples were analyzed among these patients. The most common sample for mNGS was bronchoalveolar lavage fluid (BALF), about 84% (73/87). The positive rate of pathogens identification by mNGS was higher than conventional culture (92% vs 36%, p < 0.001). In addition to the pathogens detected by conventional culture, mNGS can detect more viruses and fungi. Based on the mNGS report, clinicians made adjustments to the antibiotic regimen for 72% patients. The multivariate binary logistic regression analysis suggested that age (OR, 1.036; 95% CI, 1.005-1.067; p = 0.021) and the sequential organ failure assessment (SOFA) score on the day of mNGS sampling were independent risk factors of death at 28 days (OR, 1.204; 95% CI, 1.038-1.397; p = 0.014). Conclusion: In critically ill patients with sepsis, the most common sample type for mNGS was BALF, and the positive rate of mNGS is higher than conventional cultures, especially in viruses and fungi. Meanwhile, mNGS can guide clinicians in adjusting antibiotic regimens. Age and the SOFA score on the day of mNGS sampling were independent risk factors for death.

[Survey and analysis on digital construction of primary hospitals in Guizhou Province].

OBJECTIVE: To investigate the utilization status and awareness of digital hospital construction among medical staff in critical care department of primary hospitals, so as to promote the process of digital medical health. METHODS: One to two doctors and nurses (in the department on that day) from public hospitals in 88 counties and urban areas in 9 cities of Guizhou Province were enrolled of field investigation. The questionnaires form were filled in on-site and sorted out and analyzed by special personnel. RESULTS: A total of 297 medical staff from the department of critical care medicine of 146 hospitals were included. All the questionnaires were filled in with their real names, including 152 doctors and 145 nurses. There were 24 class III Grade A hospitals and 122 class II and all the hospitals had implemented digital information management. The awareness of hospital digital information management system was generally low among the surveyed medical staff, and the awareness of hospital information system (HIS) was the highest (86.5%), followed by laboratory information management system (LIS, 41.4%) and image archiving and communication system (PACS, 40.7%). The awareness of hospital management system (HERP) was the lowest (7.7%). The total number of remote consultations conducted by hospitals using big data Internet was 25 428 times in 2020, with a median of 24.5 (88.0, 240.0) times in each hospital. From 2018 to 2020, the total number of patients admitted to the intensive care unit of the hospital was 50 473, 57 565 and 57 907, respectively, of which the number of patients over 65 years old accounted for 37.47%, 41.26% and 43.31%, respectively (all P > 0.05). There were 4 242 cases of remote consultation using big data Internet in the department every year, with a median of 257.50 (96.50, 958.25) cases. 12.12% of the departments had independent critical monitoring systems, and 8.75% of them could capture data automatically to form tables. 96.30% of the medical staff participated in systematic and professional training on basic knowledge, basic theory and basic medical care skills through the Internet platform, and the number of meetings, studies and training in the provinces and prefectures were 282 and 357 times per year, respectively. More than 90% of the departments initiated remote consultation, arranged referral or admitted patients who had improved status after treatment in superior hospitals through the Internet platform. Most of the patients (69.02%) were from the lower level of the hospital. The total number of out-patient consultations was 2 959 times per year, with a median of 296 (185 473) times. 54.79% of the departments had fixed service villages, and 28.08% of the departments had fixed service population. The median furthest visit distance was 52.5 (30.0, 80.0) kilometers, and the median average visit distance was 30.0 (20.0, 50.0) kilometers. 54.88% of medical staff believed that the biggest difficulties encountered during house visits were insufficient energy and too large service groups or regions. More than 90% of medical staff had been exposed to cloud learning and cloud training, and most of the surveyed medical staff believed that cloud learning and cloud training greatly improved medical service capacity and service efficiency of medical institutions (71.04% and 67.01%, respectively). Meanwhile, they believe that "Internet+health big data" projects from various aspects brought advantage to medical institutions, but there are also low utilization rate of Internet medical equipment by village doctors, low acceptance for telemedicine and mobile hospitals by farmers. CONCLUSIONS: Guizhou public hospitals have implementation of digital information management at the grass-roots level, the surveyed health care workers have a relatively low awareness of the digital information management system, hospital use big data Internet for remote consultation is uneven, intensive care medicine is a clinical discipline used in most remote consultation information system, and can complete two-way referrals. In the past three years, the discipline operation showed an upward trend year by year. Medical staff use artificial intelligence devices such as cloud learning and training to improve medical service capacity and efficiency. The digital transformation of primary hospitals is being continuously improved.

Intensivists' cognizance of nutrition management and its determinants in ICUs in Guizhou province, China.

BACKGROUND AND OBJECTIVES: To investigate the Intensivists' cognizance of nutritional management and its determinants, and to provide evidence for standardizing nutritional therapy with protocols. METHODS AND STUDY DESIGN: From April to July 2021, a multi-stage sampling method was used to investigate the nutritional cognizance of critical care physicians in secondary and tertiary hospitals in Guizhou Province, China; Questionnaires and scales were used as survey tools. The questionnaires sought general information about the respondents and documented their nutrition cognizance and practice. Five scalar dimensions explored nutritional management, with answers scored for 1-5 points, 3 points being the pass score. RESULTS: 322 respondents from 147 hospitals were surveyed. The average score was passable, but not good at 3.37±0.71 (p<0.01 with 3.0 as reference). Among the five dimensions, evaluation and monitoring of nutritional status had the highest score (3.79±0.67, p<0.01), the understanding of nutritional preparations had the lowest (3.09±0.86, p>0.05), and the scores of other dimensions ranged from 3.21 to 3.49. Almost 70% of intensivists said that they would give priority to other than nutritional therapeutic measures in actual clinical practice. But 96% thought it necessary to strengthen and emphasise nutritional management. CONCLUSIONS: Critical care physicians' knowledge and understanding of nutritional therapy are limited, especially in the use of supportive preparations; Recourse to protocols and standardized nutritional management of assistance may depend on training, assigned role, peer expectations and health system policy, each of which has the potential for advancement in the interest of better nutritional care in provincial Guizhou.

[Analysis on the operation status of subspecialty of critical care medicine of hospital affiliated to Guizhou Medical University in the past 5 years].

OBJECTIVE: Through retrospective analysis of the admission and treatment of patients in the department of critical care medicine of the Affiliated Hospital of Guizhou Medical University over the past 5 years, it provides a basis for the construction of the subspecialty of intensive care medicine. METHODS: Collect clinical data of patients admitted to the department of critical care medicine of the Affiliated Hospital of Guizhou Medical University from January 1, 2016 to December 31, 2020, including gender, age, first consultation department, intensive care unit (ICU) hospitalization time, ventilator use time, main diagnosis, acute physiology and chronic health evaluation II (APACHE II) when transferred into and out of ICU, treatment results, whether to give mechanical ventilation, whether to use a non-invasive ventilator to assist breathing, whether to die in 24 hours, rescue times and success rate, etc. Changes in the above indicators during the 5 years were analyzed. RESULTS: In the past 5 years, our hospital has treated 2 668 patients in the comprehensive ICU with severe neurological, severe circulation, and severe trauma as the main treatment area, including 1 648 males and 1 020 females; aged 6 months to 94 years old, the average age (53.49±19.03) years old. Neurosurgery (907 cases) was the most frequently diagnosed department, the top 3 diseases were cerebral hemorrhage (539 cases), septic shock (214 cases), and hypovolemic shock (200 cases); ICU hospitalization time was 126 (52, 253) hours, ventilator time was 65 (17, 145) hours, APACHE II scores were 23.29±8.12 and 12.99±6.37 when transferred into and out of ICU. The proportion of receiving mechanical ventilation was 92.94% (2 147/2 310), and 314 cases used non-invasive ventilators. 84 cases died within 24 hours (mortality was 3.15%). A total of 2 585 rescues were performed, and the rescue success rate was 92.84% (2 400/2 585). From 2016 to 2020, the 5-year cure rates were 65.92%, 65.83%, 61.53%, 65.64%, 69.06%, respectively, and the 5-year mortality were 13.13%, 14.29%, 18.89%, 16.69%, 13.38%, respectively. CONCLUSIONS: With the continuous expansion of critical care medicine, the establishment of classified subspecialties can focus on the admission of patients, so that treatment can be professionalized and standardized, improve the cure rate, and reduce mortality. At the same time, medical staff can focus on management and learning related expertise to master the disease, it is also more in-depth, which is helpful for doctors to improve themselves, and is conducive to the proficiency of related sub-specialties, and lays a good foundation for the development of the department.

Mediastinal effusion due to pericardiocentesis with cardiac tamponade: a case report.

BACKGROUND: Pericardiocentesis is an effective treatment for cardiac tamponade, but there are risks, including haemorrhagic events, cardiac perforation, pneumothorax, arrhythmia, acute pulmonary oedema and so on. Mediastinal effusion caused by puncture is rarely reported. CASE PRESENTATION: A 47-year-old man who had a history of right leg deep vein thrombosis and pulmonary artery embolism with implantation of an inferior vena cava filter presented for inferior vena cava filter removal. Within 30 min after the procedure, he developed chest pain, nausea, vomiting and presyncope with shock. Echocardiography confirmed massive pericardial effusion with evidence of cardiac tamponade. Emergency pericardiocentesis was performed. Confusingly, only 3 mL of bloody pericardial effusion was drained in total, and subsequently, the patient's symptoms rapidly improved with stable haemodynamics. Repeat echocardiography showed that the pericardial effusion had disappeared. Urgent computed tomography pulmonary angiography demonstrated localized effusion, which was not seen the previous computed tomography results and was noted around the left ventricle in the mediastinal apace. No intervention was performed, given that there was no bleeding tendency or further adverse events related to the mediastinal effusion. The patient was subsequently discharged in a stable condition a few days later, and outpatient follow-up was advised. CONCLUSIONS: Mediastinal effusion is a rare complication of pericardiocentesis. In the case described herein, the most likely cause was pericardial effusion extravasated into the mediastinum through the needle insertion site in the puncture process due to large pressure variations in the intrapericardial space with tamponade, differing from cases of over-anticoagulation reported in the previous literature. Just as our case demonstrates that conservative treatment of an hemodynamic insignificant mediastinal effusion may be appropriate. Echocardiography is useful and effective to minimize complication rates.

[Interpretation of Guidelines for controlling confounding factors and reporting results in causal inference studies].

Causal inference research is a causal test designed to assess the impact of exposures on outcomes.Both experimental and observational studies can be used to examine causal associations between exposure factors and outcomes. Experimental studies are sometimes limited by factors such as ethics or experimental conditions. Observational studies account for a large proportion in clinical studies, but the effectiveness and research value of observational studies will be affected if the design of observational studies is not rigorous and the confounding factors are not well controlled.The Guidelines for controlling confounding factors and reporting results in causal inference studie formulated by a special group of 47 editors from 35 journals from all over the world provide good guidance to researchers. This article interprets the guidelines and hopes to provide help for clinical researchers.

[Risk factors for death in elderly patients admitted to intensive care unit after elective abdominal surgery: a consecutive 5-year retrospective study].

OBJECTIVE: To investigate the risk factors that were associated with the death of elderly patients who were admitted to the intensive care unit (ICU) after elective abdominal surgery, and to find reliable and sensitive predictive indicators for early interventions and reducing the mortality. METHODS: A retrospective case-control study was conducted. The clinical data of elderly (age ≥ 65 years old) patients after elective abdominal surgery admitted to the ICU of the Affiliated Hospital of Guizhou Medical University from January 1st 2016 to December 31st 2020 were collected, including the patient's gender, age, body mass index (BMI), medical history, American Society of Anesthesiologists (ASA) grades, surgical classification, intraoperative blood loss, duration of operation, interval time between end of operation and admission to the ICU, acute physiology and chronic health evaluation II (APACHE II) score and the worst laboratory examination results within 24 hours of ICU admission, the first blood gas analysis in ICU, the duration of invasive mechanical ventilation, and the length of ICU stay. Postoperative abdominal infection was evaluated by the pathogenic culture of peritoneal drainage fluid and clinical symptoms and signs. The patients were divided into death group and survival group based on clinical outcomes, and clinical data were compared between the two groups. Binary multivariate Logistic regression analysis was used to screen the risk factors of death, and the receiver operator characteristic curve (ROC curve) was plotted to analyze the predictive values of these risk factors. RESULTS: A total of 226 elderly patients with elective abdominal surgery were admitted to the ICU of our hospital during the past 5 years, of whom, two patients who did not undergo laboratory examinations within 24 hours of admission to the ICU were excluded. Finally, 224 patients met the criteria, with 158 survivors and 66 deaths. Univariate analysis showed that: compared with survival group, APACHE II score, blood lactate acid (Lac) and the proportion of postoperative abdominal infection were higher in death group [APACHE II score: 27.5 (25.0, 31.3) vs. 23.0 (18.0, 27.0), Lac (mmol/L): 2.9 (1.8, 6.6) vs. 1.8 (1.1, 2.8), the proportion of postoperative abdominal infection: 65.2% (43/66) vs. 35.4% (56/158), all P < 0.01], prothrombin time (PT), activated partial thromboplastin time (APTT) and interval time between end of surgery and admission to ICU were longer [PT (s): 17.20 (14.50, 18.63) vs. 14.65 (13.90, 16.23), APTT (s): 45.15 (38.68, 55.15) vs. 39.45 (36.40, 45.70), interval time between end of surgery and admission to ICU (hours): 39.2 (0.7, 128.9) vs. 0.7 (0.3, 2.0), all P < 0.01], postoperative hemoglobin (Hb), platelet count (PLT), prealbumin (PA), mean arterial pressure (MAP) and oxygenation index (PaO2/FiO2) were lower in death group [Hb (g/L): 95.79±23.64 vs. 105.58±19.82, PLT (×109/L): 138.5 (101.0, 177.5) vs. 160.5 (118.5, 232.3), PA (g/L): 80.88±43.63 vs. 116.54±50.80, MAP (mmHg, 1 mmHg = 0.133 kPa): 76.8±19.1 vs. 91.6±19.8, PaO2/FiO2 (mmHg): 180.0 (123.5, 242.5) vs. 223.5 (174.8, 310.0), all P < 0.05]. Binary multivariate Logistic regression analysis showed that APACHE II score [odds ratio (OR) = 1.187, 95% confidence interval (95%CI) = 1.008-1.294, P < 0.001], interval time between end of operation and admission to ICU (OR = 1.005, 95%CI = 1.001-1.009, P = 0.016) and postoperative abdominal infection (OR = 2.630, 95%CI = 1.148-6.024, P = 0.022) were independent risk factors for prognosis in these patients. MAP (OR = 0.978, 95%CI = 0.957-0.999, P = 0.041) and PaO2/FiO2 (OR = 0.994, 95%CI = 0.990-0.998, P = 0.003) were protective factors for the patients' prognosis. Lac, Hb, PLT, PA, PT and APTT had no predictive value for the prognosis of elderly patients admitted to ICU after elective abdominal surgery [OR value and 95%CI were 1.075 (0.945-1.223), 1.011 (0.99-1.032), 1.000 (0.995-1.005), 0.998 (0.989-1.007), 1.051 (0.927-1.192) and 1.003 (0.991-1.016), respectively, all P > 0.05. ROC curve analysis showed that APACHE II score, interval time between end of operation and admission to the ICU and the postoperative abdominal infection had certain predictive values for the prognosis of elderly patients, the area under ROC curve (AUC) were 0.755, 0.732 and 0.649 respectively, all P < 0.001; When the cut-off of APACHE II score and interval time between end of operation and admission to the ICU were 24.5 scores and 2.15 hours, the sensitivity were 78.8% and 66.7%, respectively, and the specificity were 62.0% and 76.6%, respectively. The combined predictive value of the three variables was the highest, which AUC was 0.846, the joint prediction probability was 0.27, the sensitivity was 83.3%, and the specificity was 75.3%. CONCLUSIONS: APACHE II score, interval time between end of surgery and admission to ICU, and postoperative abdominal infection may be independent risk factors for the death of elderly patients who were admitted to the ICU after elective abdominal surgery, there would be far greater predictive values when the three variables were combined.

[Field investigation of standardized construction of intensive care unit in county-level public hospitals in Dizhou City, Guizhou Province].

OBJECTIVE: To investigate the standardized construction of critical care departments in different cities and counties of Guizhou province to promote the homogenization development of critical care medicine in Guizhou Province. METHODS: Using research methods such as field investigation and data collection, the public hospitals of 88 counties and urban areas in 9 prefectures and cities of Guizhou province were divided into five routes: southeast, northeast, northwest, southwest, and Guiyang. To design the survey form for the standardized construction of ICU, the e-form was sent to the director of ICU or his/her designated personnel by email or wechat 2-3 days in advance. Check the authenticity of data item by item on site, and leave the hospital after checking the receipt form. RESULTS: From April to July 2021, the survey and research data collection was completed for 146 public hospitals (excluding provincial hospitals) with intensive care departments in 88 counties and cities of 9 dizhou cities in Guizhou Province, including 24 Grade-III Level A hospitals. 122 Grade-II and above hospitals (including 8 Grade-III Level B hospitals, 11 Grade-III comprehensive hospitals, 97 Level-II A hospitals, 3 Level-II B hospitals, and 3 Level-II comprehensive hospitals). 146 public hospitals have a total of 80 983 beds and 104 017 open beds. The department of Critical Care has 2 035 beds. The ratio of actual beds in ICU to total beds in hospital was 2.51%. From 1999 to 2010, 18 (12.33%) established departments, and from 2011 to 2021, 128 (87.67%) established departments. The total area of the discipline is 113 355.48 m2, with an average bed area of 55.70 m2. There were 97 hospitals with 1.5-2.0 m bed spacing, accounting for 66.44%, and 49 hospitals with 2.1- > 2.5 m spacing, accounting for 33.56%. The number of negative pressure wards: 1 in each of 43 hospitals, accounting for 29.45%; 103 hospitals did not have, accounting for 70.55%. The number of single rooms: 288 in 140 hospitals, accounting for 95.89%; 6 hospitals did not have, accounting for 4.11%. Central oxygen supply: 138 hospitals have (94.52%); 8 hospitals did not have, accounting for 5.48%. Natural ventilation: in 129 hospitals with 88.36%; 17 hospitals did not have, accounting for 11.64%. Specialized ICU construction: 66 hospitals, accounting for 45.21%; none in 80 hospitals, accounting for 54.79%. There are 3 712 doctors and nurses in 146 public hospitals. The total number of doctors was 1 041, and the ratio of doctors to beds was 0.51:1. The total number of nurses was 2 675, and the ratio of nurses to beds was 1.31:1. CONCLUSIONS: All 88 counties and districts in 9 prefectures and cities of Guizhou province have established intensive care medicine departments. The standardization of the discipline construction has been significantly improved. Lack of talents is still an important factor restricting the rapid development of the discipline.

Role of dexmedetomidine in the treatment of delirium in critically ill patients: a systematic review and meta-analysis.

INTRODUCTION: Although dexmedetomidine has been found to prevent delirium in critically ill patients, it is uncertain whether it can treat acute delirium. This study aimed to evaluate the efficacy and safety of dexmedetomidine in treating delirium, by analyzing and reviewing data from previous studies. EVIDENCE ACQUISITION: Clinical trial data on the use of dexmedetomidine in adult critically ill patients with delirium were retrieved from four databases (PubMed, Embase, Web of Science, and the Cochrane Library) and clinicaltrials.gov, from inception to May, 2020. EVIDENCE SYNTHESIS: Ten randomized controlled trials (RCTs) and five non-RCTs met the selection criteria and data were obtained from 1017 patients. In one study, dexmedetomidine reduced the duration of delirium to a greater extent than did the placebo. In six studies, it was associated with a lower point-prevalence of delirium after treatment (OR, 0.39; 95% CI, 0.20, 0.76; P=0.006) and a shorter time to resolution of delirium (hours; MD, -23.25; 95% CI, -45.28, -1.21; P=0.04) compared with those of other drugs. In four RCTs, it was superior to haloperidol in reducing the time to resolution of delirium (hours; MD, -30.17; P=0.01). However, in seven studies, it showed a higher risk of bradycardia (OR, 3.48; 95% CI, 1.47, 8.23; P=0.004) than that of comparators. CONCLUSIONS: Dexmedetomidine promotes the resolution of delirium but also increases the incidence of bradycardia during treatment. Furthermore, it may be superior to haloperidol in treating delirium, although more studies are needed to confirm this.

[Artificial intelligence provides promotion of big data in medical work and contribution to people's health as soon as possible: real-time warning of critical illness is the pioneer of artificial intelligence in clinical medicine].

Through the big data intelligent algorithm and application of artificial intelligence in critically ill patients, the value of the combination of clinical real-time warning and artificial intelligence in critical care medicine was explored. Artificial intelligence was used to simulate human thinking by studying, calculating, and analyzing a large amount of critical illness data in the medical work, and integrate a large number of clinical monitoring and treatment data generated in critical care medicine. The necessity, feasibility, relevance, data learning and application architecture of the application of artificial intelligence in the early warning of critical illness in medical work were analyzed, thus to promote the pioneering application of real-time warning of critical illness in clinical medicine. The development of critical care medicine in medical work requires the integration of big data and artificial intelligence. Through real-time early warning, accurate and scientific intelligent application of medical data, the life threatening uncertainties in the diagnosis and treatment of critically ill patients can be more effectively reduced and the success rate of the treatment of critically ill patients can be improved. The perfect combination of artificial intelligence technology and big data of critical care medicine can provide a favorable guarantee for the pioneering application of real-time warning of critical care medicine in clinical work.

[Clinical analysis of septic shock caused by acute upper and lower gastrointestinal perforation].

OBJECTIVE: To analyze the clinical characteristics of septic shock caused by upper and lower gastrointestinal perforation. METHODS: Clinical data of patients with septic shock due to gastrointestinal perforation admitted to the department of critical care medicine of the Affiliated Hospital of Guizhou Medical University from January 2018 to December 2019 were analyzed retrospectively. The general information; procalcitonin (PCT), acute physiology and chronic health evaluation II (APACHE II) and sequential organ failure assessment (SOFA) scores during the first 24 hours in intensive care unit (ICU); results of ascites culture during the first 72 hours in ICU; the maximum dosage and total time of norepinephrine (NE) in ICU; mechanical ventilation time, the length of ICU stay, occurrence of acute kidney injury (AKI), continuous renal replacement therapy (CRRT) and 28-day mortality were collected. The patients were divided into upper gastrointestinal tract group (stomach and duodenum) and lower gastrointestinal tract group (jejunum, ileum, appendix, colon and rectum), with a boundary of Treitz. The clinical features between the two groups were compared. RESULTS: There were 33 patients in the upper gastrointestinal tract group and 30 patients in the lower gastrointestinal tract group. There was no significant difference in gender and age between the two groups. The main pathogens in the ascites cultures in the upper gastrointestinal tract group were Candida albicans (45.5%), Enterococcus faecalis (18.2%) and Escherichia coli (18.2%). Escherichia coli (46.2%) and Enterococcus faecalis (30.8%) were the main pathogens in the lower gastrointestinal tract group. There were significant differences in PCT, the length of ICU stay, mechanical ventilation time, the maximum dosage and total time of NE between the upper gastrointestinal tract group and lower gastrointestinal tract group [PCT (µg/L): 17.69 (3.83, 26.62) vs. 32.82 (4.21, 100.00), the length of ICU stay (hours): 149.0 (102.5, 302.0) vs. 115.5 (30.8, 214.5), mechanical ventilation time (hours): 106.0 (41.5, 183.0) vs. 57.5 (25.0, 122.3), the maximum dosage of NE (µg×kg-1×min-1): 1.2 (0.5, 2.0) vs. 0.7 (0.5, 1.2), the total time of NE (hours): 72.0 (21.0, 145.0) vs. 26.5 (18.0, 80.5), all P < 0.05], while there was no statistically differences in APACHE II or SOFA scores [APACHE II: 30.0 (24.5, 35.0) vs. 28.0 (25.0, 33.5), SOFA: 10.67±4.14 vs. 9.50±3.33, both P > 0.05]. Compared with the lower gastrointestinal tract group, patients in the upper gastrointestinal tract group were more likely to have AKI (78.8% vs. 53.3%, P < 0.05) and require CRRT (39.4% vs. 16.7%, P < 0.05), but there was no significant difference in the 28-day mortality (39.4% vs. 43.3%, P > 0.05). CONCLUSIONS: The clinical characteristics of septic shock caused by upper and lower gastrointestinal perforation are not the same. Patients with septic shock caused by upper gastrointestinal perforation are more likely to suffer from fungal infection, with more severe shock, more likely to have AKI and require CRRT, and significantly longer mechanical ventilation and the length of ICU stay. While patients with septic shock caused by lower gastrointestinal perforation showed higher PCT.

[A special type of blood pressure reduction: a case of carbon dioxide ejection syndrome].

Carbon dioxide (CO2) ejection syndrome is common after artificial pneumoperitoneum, and it often attracts the attention of anesthesiologists because of its rapid changes in vital signs. CO2 ejection syndrome is not uncommon in critically ill patients, and may occur after mechanical ventilation in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). There are few relevant reports about CO2 ejection syndrome, and a considerable number of clinicians have little understanding of the pathological changes. A case of AECOPD patient with CO2 ejection syndrome after endotracheal intubation was admitted to the intensive care unit (ICU) of the Affiliated Hospital of Guizhou Medical University. After treatment, such as fluid expansion, vasoactive drugs and ventilator assistance, the patient's condition improved and was transferred out of the ICU. It is expected to provide some references by summarizing the diagnosis and treatment of this case and reviewing relevant literature reports.