Intra-abdominal candidiasis (IAC) is the most common invasive candidiasis, with a high incidence among critically ill patients, which can significantly increase medical costs and affect prognosis. In order to standardize the diagnosis and treatment of IAC in critically ill patients, experts in related fields were organized by the Peking University Critical Care Medicine (PKUCCM), Committee of Critical Care Medicine and Organ Support, China Association for Promotion of Health Science and Technology organized experts in related fields to initiate and form a working group. Expert writers drafted the consensus based on evidence-based medical evidence. A committee composed of critical care physicians, infectious disease physicians, surgeons, dermatologists specializing in antifungal fields, and clinical pharmacists discussed and revised the consensus draft through a standardized process, and finally formulated this consensus. This consensus contains a total of 20 core recommendations, mainly focusing on the epidemiology, high-risk factors, diagnostic techniques and methods (including traditional microbiological culture techniques, clinical risk prediction tools, serological tests, molecular biological tests, and histopathological examinations) of IAC, diagnostic criteria, stratified treatment strategies, antifungal drug selection, control the sources of infection, combined treatment, de-escalation strategies, drug treatment courses, prognosis, and special types of IAC. The aim is to provide expert guidance for the standardized clinical diagnosis and treatment of IAC in critically ill patients, with a view to improving prognosis of patients.
Humans ; Critical Illness ; Intraabdominal Infections/therapy* ; Antifungal Agents/therapeutic use* ; Consensus ; Candidiasis/drug therapy* ; Critical Care ; Candidiasis, Invasive/diagnosis*

OBJECTIVE: To develop and compare risk prediction models for in-hospital post-cardiac arrest brain injury (PCABI) in critically ill patients using nomograms and random forest algorithms, aiming to identify the optimal model for early identification of high-risk PCABI patients and providing evidence for precise treatment. METHODS: A retrospective cohort study was used to collect the first-time in-hospital cardiac arrest (IHCA) patients admitted to the intensive care unit (ICU) from 2008 to 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) as the study population, and the patients' age, gender, body mass, health insurance utilization, first vital signs and laboratory tests within 24 hours of ICU admission, mechanical ventilation, and critical care scores were extracted. Independent influencing factors of PCABI were identified through univariate and multivariate Logistic regression analyses. The included patients were randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio, and the PCABI risk prediction model was constructed by the nomogram and random forest algorithm, respectively, and the model was evaluated by receiver operator characteristic curve (ROC curve), the calibration curve, and the decision curve analysis (DCA), and after the better model was selected, 179 patients admitted to Tianjin Medical University General Hospital as the external validation cohort for external evaluation were collected by using the same inclusion and exclusion criteria. RESULTS: A total of 1 419 patients with without traumatic brain injury who had their first-time IHCA were enrolled, including 995 in the training cohort (including 176 PCABI and 819 non-PCABI) and 424 in the internal validation cohort (including 74 PCABI and 350 non-PCABI). Univariate and multivariate analysis showed that age, potassium, urea nitrogen, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation III (APACHE III), and mechanical ventilation were independent influences on the occurrence of PCABI in patients with IHCA (all P < 0.05). Combining the above variables, we constructed a nomogram model and a random forest model for comparison, and the results show that the nomogram model has better predictive efficacy than the random forest model [nomogram model: area under the ROC curve (AUC) of the training cohort = 0.776, with a 95% credible interval (95%CI) of 0.741-0.811; internal validation cohort AUC = 0.776, with a 95%CI of 0.718-0.833; random forest model: AUC = 0.720, with a 95%CI of 0.653-0.787], and they performed similarly in terms of calibration curves, but the nomogram performed better in terms of decision curve analysis (DCA); at the same time, the nomogram model was robust in terms of external validation cohort (external validation cohort AUC = 0.784, 95%CI was 0.692-0.876). CONCLUSIONS A nomogram risk prediction model for the occurrence of PCABI in critically ill patients was successfully constructed, which performs better than the random forest model, helps clinicians to identify the risk of PCABI in critically ill patients at an early stage and provides a theoretical basis for early intervention.
Humans ; Critical Illness ; Retrospective Studies ; Heart Arrest/complications* ; Nomograms ; Brain Injuries/etiology* ; Intensive Care Units ; Algorithms ; Male ; Female ; Middle Aged ; ROC Curve ; Risk Factors ; Risk Assessment ; Logistic Models ; Aged

Extracorporeal membrane oxygenation (ECMO) technology is an important life support method for critically ill patients. A large number of studies have found that ECMO can change the pharmacokinetic (PK) parameters of critically ill patients, thereby affecting the drug effect in vivo. However, there is still a lack of recommendations for the adjustment of commonly used drugs during ECMO support in China, and the selection or dosage adjustment of drugs during ECMO support is not clear. Therefore, a multidisciplinary group of domestic experts in clinical pharmacy and critical care medicine was established by Critical Care Medicine Committee of China International Exchange and Promotive Association for Medical and Health Care, and Hospital Pharmacy Committee of China Pharmaceutical Association, to develop the Expert consensus on drug adjustment during extracorporeal membrane oxygenation support (2025). Eight clinical issues of drug adjustment during ECMO support were discussed in this consensus: (1) Why does the patient's demand for drug dosage change during ECMO support? (2) What factors are related to the degree of drug loss during ECMO support? (3) Considering the features of drugs, which types of drugs may need to be adjusted during ECMO support? (4) How to adjust the dosage when using antibacterial drugs during ECMO support? (5) How to adjust antifungal drugs during ECMO support? (6) Does ECMO support change patients' dosage requirements for antiviral drugs? (7) How to adjust sedative and analgesic drugs during ECMO support? (8) Does ECMO support affect the dosage requirement of vasoactive agents? Eighteen consensus are elaborated based on the latest clinical evidence, aiming to provide recommendations for drug adjustment in critically ill patients receiving ECMO support to ensure the safety and effectiveness of medication.
Humans ; Critical Illness ; Extracorporeal Membrane Oxygenation ; Consensus ; Candidiasis/drug therapy* ; Intraabdominal Infections/therapy*

OBJECTIVE: To investigate the current status of early pain and agitation management in critically ill patients in Guizhou Province. METHODS: A retrospective study was performed using data collected from a quality control activity conducted between April and June 2021 in non-provincial public hospitals with general intensive care unit (ICU) in Guizhou Province. Hospital-level data included hospital name and grade, ICU staffing, and number of ICU beds. Patient-level data included characteristics of patients treated in the general ICU on the day of the survey (e.g., age, sex, primary diagnosis), as well as pain and agitation assessments and the types of analgesic and sedative medications administered within 24 hours of ICU admission. RESULTS: A total of 947 critically ill ICU patients from 145 hospitals were included, among which 104 were secondary-level hospitals and 41 were tertiary-level hospitals. Within 24 hours of ICU admission, 312 (32.9%) critically ill patients received pain assessments, and 277 (29.3%) received agitation assessments. Among the pain assessment tools, the critical care pain observation tool (CPOT) was used in 44.2% (138/312) of critically ill ICU patients, with a significantly higher usage rate in tertiary hospitals compared to secondary hospitals [52.3% (69/132) vs. 38.3% (69/180), P < 0.05]. The Richmond agitation-sedation scale (RASS) was used in 93.8% (260/277) of critically ill ICU patients for agitation assessment, with no significant difference between hospital levels. Among the 947 critically ill patients, 592 (62.5%) received intravenous analgesics within 24 hours, with remifentanil being the most commonly used [42.9% (254/592)]; 510 (53.9%) received intravenous sedatives, with midazolam being the most frequently used [60.8% (310/510)]. Mechanical ventilation data were available for 932 critically ill patients, of whom 579 (62.1%) received mechanical ventilation and 353 (37.9%) did not. Compared with non-ventilated patients, ventilated patients had significantly higher rates of analgesic and sedative use [analgesics: 77.9% (451/579) vs. 38.8% (137/353); sedatives: 71.8% (416/579) vs. 25.8% (91/353); both P < 0.05]. In terms of analgesic selection, ventilated patients were more likely to receive strong opioids than non-ventilated patients [85.8% (95/137) vs. 69.3% (387/451), P < 0.05]. For sedatives, ventilated patients preferred midazolam [66.6% (277/416)], whereas non-ventilated patients more often received dexmedetomidine [45.1 (41/91)]. Blood pressure within 24 hours of ICU admission were available for 822 critically ill patients, of whom 245 (29.8%) had hypotension and 577 (70.2%) did not. Compared with non-hypotensive patients, hypotensive patients had significantly higher rates of analgesic and sedative use [analgesics: 74.7% (183/245) vs. 59.8% (345/577); sedatives: 65.7% (161/245) vs. 51.3% (296/577); both P < 0.05], but there was no significant difference in the choice of analgesic or sedative agents between the two groups. CONCLUSIONS The proportion of critically ill ICU patients in Guizhou Province who received standardized pain and agitation assessments was relatively low. The most commonly used assessment tools were CPOT and RASS, while remifentanil and midazolam were the most frequently used analgesic and sedative agents, respectively. Secondary-level hospitals had a lower rate of using standardized pain assessment tools compared to tertiary-level hospitals. Mechanical ventilation and hypotension were associated with the use of analgesic and sedative medications.
Humans ; Critical Illness ; Intensive Care Units ; Analgesics/therapeutic use* ; Hypnotics and Sedatives/therapeutic use* ; Retrospective Studies ; China ; Pain Measurement ; Pain Management ; Female ; Male ; Critical Care ; Middle Aged

Critically ill patients often experience significant skeletal muscle wasting due to prolonged bed rest, metabolic disorders, inflammatory responses and malnutrition, which affects the patient's mobility and may also lead to increased mortality. Timely and accurate assessment of muscle status is important for optimizing treatment strategies and improving patient prognosis. There are various limitations in the current methods of assessing muscle mass, and muscle ultrasound, as a noninvasive, convenient, low-cost and suitable technique for bedside monitoring, has received increasing attention for its application in muscle assessment of critically ill patients. However, there are still a number of challenges in its practical application, such as the lack of uniform standards for the measurement method, the high dependence on the operation, and the reproducibility of the data that needs to be optimized, and so on. The aim of this article is to systematize the research progress of muscle ultrasound in muscle assessment of critically ill patients, and to discuss the advantages and limitations of its clinical application, in order to provide a scientific basis for future research and clinical practice.
Humans ; Critical Illness ; Ultrasonography ; Muscle, Skeletal/diagnostic imaging*

Nutritional support therapy is one of the extremely important treatment methods for patients in the intensive care unit. Timely and effective nutritional support regimens can improve patients' immune function, reduce complications, and optimize clinical outcomes. Energy expenditure is influenced by multiple factors, including patients' baseline characteristics (such as physical condition, gender, age) and dynamic changes in indicators (such as body temperature, nutritional support regimens, and therapeutic interventions). The currently recognized "gold standard" for accurately assessing energy metabolism in clinical practice is the indirect calorimetry system, also known as the metabolic cart. This device monitors carbon dioxide production and oxygen consumption in real time and uses specific algorithms to estimate the metabolic proportions of the three major nutrients (carbohydrates, fats, and proteins) in energy expenditure. An appropriate nutrient ratio helps maintain the balance between supply and demand in the body's nutritional metabolism. In the management of critically ill patients, the application of the metabolic cart enables personalized nutritional therapy, avoiding over- or under-supply of energy and optimizing the use of medical resources. Furthermore, with real-time, quantitative data support from the energy metabolism monitoring system, clinicians can develop more precise nutritional intervention strategies, thereby improving patient prognosis. This article provides a systematic review of the technical features of the metabolic cart and its application value in various critical care scenarios, aiming to offer a reference for indirect calorimetry in clinical practice.
Humans ; Critical Illness/therapy* ; Nutritional Support ; Energy Metabolism ; Calorimetry, Indirect

OBJECTIVE: To analyze the efficacy and access safety of extracorporeal membrane oxygenation (ECMO) in series with continuous renal replacement therapy (CRRT) access for critically ill patients using propensity score matching analysis, and to explore the potential influencing factors of infection. METHODS: A total of 200 critically ill patients who received both ECMO and CRRT treatment in the intensive care unit (ICU) of Huai'an Second People's Hospital from December 2020 to December 2024 were retrospectively selected as the research subjects. They were divided into the independent operation group (72 cases) and the series system group (128 cases) according to the access connection mode of ECMO and CRRT. Propensity score matching analysis was used to perform 1 : 1 matching for patients of the two groups. The general data [age, gender, body mass index (BMI), clinical diagnosis, underlying disease, intubation method, intubation position, disease severity, ECMO support duration, catheter indwelling duration, oxygenation index (PaO₂/FiO₂) at 48 hours after ECMO initiation, serum creatinine (SCr), procalcitonin (PCT), hemoglobin (Hb), white blood cell count (WBC), platelet count (PLT)], treatment status [ECMO initiation duration, ECMO operation duration, ECMO flow, left ventricular ejection fraction (LVEF), CRRT initiation duration, CRRT catheter indwelling duration, inflow and outflow volume of replacement fluid], clinical outcome indicators (28-day survival rate, length of ICU stay, renal function recovery, fluid balance compliance rate), and access safety indicators (incidence of ECMO access thrombosis, incidence of infection, and incidence of bleeding events) of all the patients were collected. Subgroup analysis was conducted based on the occurrence of infection, and multivariate Logistic regression analysis was used to screen the potential risk factors for infection in critically ill patients receiving both ECMO and CRRT treatment. RESULTS: Finally, a total of 120 patients were successfully matched, with 60 patients in both the independent operation group and the series system group. No statistically significant differences were observed in the general data between the two groups, indicating comparability. Compared with the independent operation group, the ECMO flow at 48 hours after ECMO initiation, SCr, and alanine transaminase (ALT) of the patients in the series system group were significantly decreased, while the LVEF at 48 hours after ECMO initiation was significantly increased, additionally, the CRRT initiation duration, CRRT catheter indwelling duration, and the length of ICU stay were significantly shortened, and the inflow and outflow volume of replacement fluid were significantly increased. The incidence of infection and bleeding events in the series system group was significantly lower than that in the independent operation group [infection incidence: 11.67% (7/60) vs. 36.67% (22/60), bleeding event incidence: 8.33% (5/60) vs. 48.33% (29/60), both P < 0.05]. No significant difference was found in the other general data, treatment status, clinical outcome indicators, or access safety indicators between the two groups. Among the 120 patients, 29 cases developed infection (accounting for 24.17%), and 91 cases had no infection (accounting for 75.83%). Compared with the non-infection group, the catheter indwelling duration was significantly prolonged and PCT was significantly increased in the infection group, while the PLT and the proportion of patients with ECMO and CRRT access connected via the series system were significantly decreased. Multivariate Logistic regression analysis showed that catheter indwelling duration [odds ratio (OR) = 1.277, 95% confidence interval (95%CI) was 1.001-1.629, P = 0.049], PCT (OR = 1.529, 95%CI was 1.222-1.914, P < 0.001], PLT (OR = 0.953, 95%CI was 0.926-0.981, P = 0.001), and access connection mode (OR = 0.289, 95%CI was 0.090-0.930, P = 0.037) were potential risk factors for infection in critically ill patients. CONCLUSIONS The ECMO-in-series CRRT access can accelerate the initiation of CRRT, avoid local bleeding, stabilize patients' cardiac, hepatic and renal functions, reduce potential infection risks, and improve the prognosis of patients.
Humans ; Extracorporeal Membrane Oxygenation/adverse effects* ; Critical Illness/therapy* ; Retrospective Studies ; Continuous Renal Replacement Therapy ; Male ; Female ; Intensive Care Units ; Propensity Score ; Middle Aged ; Renal Replacement Therapy ; Adult ; Aged ; Risk Factors

OBJECTIVES: To explore the risk factors of feeding intolerance (FI) in critically ill children receiving enteral nutrition (EN) and to construct a prediction nomogram model for FI. METHODS: A retrospective study was conducted to collect data from critically ill children admitted to the Pediatric Intensive Care Unit of Xiangya Hospital, Central South University, between January 2015 and October 2020. The children were randomly divided into a training set (346 cases) and a validation set (147 cases). The training set was further divided into a tolerance group (216 cases) and an intolerance group (130 cases). Multivariate logistic regression analysis was used to screen for risk factors for FI in critically ill children receiving EN. A nomogram was constructed using R language, which was then validated on the validation set. The model's discrimination, calibration, and clinical net benefit were evaluated using receiver operating characteristic curves, calibration curves, and decision curves. RESULTS: Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition were identified as independent risk factors for FI in critically ill children receiving EN (P<0.05). Based on these factors, a nomogram prediction model for FI in critically ill children receiving EN was developed. The area under the receiver operating characteristic curve for the training set and validation set was 0.934 (95%CI: 0.906-0.963) and 0.852 (95%CI: 0.787-0.917), respectively, indicating good discrimination of the model. The Hosmer-Lemeshow goodness-of-fit test showed that the model had a good fit (χ 2=12.559, P=0.128). Calibration curve and decision curve analyses suggested that the model has high predictive efficacy and clinical application value. CONCLUSIONS Duration of bed rest, shock, gastrointestinal decompression, use of non-steroidal anti-inflammatory drugs, and combined parenteral nutrition are independent risk factors for FI in critically ill children receiving EN. The nomogram model developed based on these factors exhibits high predictive efficacy and clinical application value.
Humans ; Critical Illness ; Enteral Nutrition/adverse effects* ; Male ; Risk Factors ; Female ; Child, Preschool ; Infant ; Nomograms ; Retrospective Studies ; Child ; Logistic Models

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Critically ill children often present with anemia and have a higher demand for transfusions compared to other pediatric patients. This guideline provides guidance and recommendations for blood transfusions in cases of general critical illness, septic shock, acute brain injury, extracorporeal membrane oxygenation, non-life-threatening bleeding, and hemorrhagic shock. This article interprets the background and evidence of the blood transfusion provisions for critically ill and severely bleeding children in the "Guideline for pediatric transfusion", aiming to enhance understanding and implementation of this aspect of the guidelines. Citation:Chinese Journal of Contemporary Pediatrics, 2025, 27(4): 395-403.
Humans ; Critical Illness ; Blood Transfusion/standards* ; Child ; Hemorrhage/therapy* ; Practice Guidelines as Topic

OBJECTIVES: To investigate the association of serum albumin level after human albumin infusion with 28-day mortality in critically ill patients with acute kidney injury (AKI) and its impact on 90-day outcomes of the patients. METHODS: We conducted a retrospective cohort study based on the MIMIC IV database (2008-2019), including 5918 AKI patients treated with albumin in the ICU. Based on serum albumin levels within 72 h after albumin infusion, the patients were divided into low (<30 g/L), medium (30-35 g/L), and high albumin (>35 g/L) groups. Restricted cubic spline regression and multivariate logistic regression were used to analyze the association of albumin levels with patient mortality, and the results were verified in a external validation cohort consisting of 110 sepsis-induced AKI patients treated in Nanfang Hospital between 2017 and 2022 using survival analysis and multivariate adjustment. RESULTS: In the MIMIC training cohort, multivariate logistic regression showed no significant differences in 28-day mortality of the patients with different albumin levels (P>0.05). However, restricted cubic spline analysis indicated a non-linear dose-response relationship between albumin levels and 28-day mortality (threshold effect: risk increased when albumin levels >3.6 g/dL). Secondary endpoint analysis revealed that the patients with high albumin levels had a shorter duration of mechanical ventilation (P<0.001) but a longer ICU stay (P<0.001). In the validation cohort, albumin levels ≥30 g/L were significantly associated with a reduced 28-day mortality rate (P<0.05). CONCLUSIONS The association between increased serum albumin levels following albumin infusion and 28-day mortality of critically ill patients with AKI exhibits a cohort dependency and can be influenced by multiple factors including disease type and severity, infusion strategies, and statistical methods.
Humans ; Acute Kidney Injury/therapy* ; Critical Illness/mortality* ; Retrospective Studies ; Serum Albumin/analysis* ; Male ; Female ; Intensive Care Units ; Middle Aged ; Logistic Models ; Aged