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

OBJECTIVE: To explore the feasibility of incorporating simple bedside indicators into death predictive model for elderly critically ill patients based on interpretability machine learning algorithms, providing a new scheme for clinical disease assessment. METHODS: Elderly critically ill patients aged ≥ 65 years who were hospitalized in the intensive care unit (ICU) of Tacheng People's Hospital of Ili Kazak Autonomous Prefecture from June 2017 to May 2020 were retrospectively selected. Basic parameters including demographic characteristics, basic vital signs and fluid intake and output within 24 hours after admission, as well acute physiology and chronic health evaluation II (APACHE II), Glasgow coma score (GCS) and sequential organ failure assessment (SOFA) were also collected. According to outcomes in hospital, patients were divided into survival group and death group. Four datasets were constructed respectively, namely baseline dataset (B), including age, body temperature, heart rate, pulse oxygen saturation, respiratory rate, mean arterial pressure, urine output volume, infusion volume, and crystal solution volume; B+APACHE II dataset (BA), B+GCS dataset (BG), and B+SOFA dataset (BS). Then three machine learning algorithms, Logistic regression (LR), extreme gradient boosting (XGboost) and gradient boosting decision tree (GBDT) were used to develop the corresponding mortality predictive models within four datasets. The feature importance histogram of each prediction model was drawn by SHapley additive explanation (SHAP) method. The area under curve (AUC), accuracy and F1 score of each model were compared to determine the optimal prediction model and then illuminate the nomogram. RESULTS: A total of 392 patients were collected, including 341 in the survival group and 51 in the death group. There were statistically significant differences in heart rate, pulse oxygen saturation, mean arterial pressure, infusion volume, crystal solution volume, and etiological distribution between the two groups. The top three causes of death were shock, cerebral hemorrhage, and chronic obstructive pulmonary disease. Among the 12 prognostic models trained by three machine learning algorithms, overall performance of prognostic models based on B dataset was behind, whereas the LR model trained by BA dataset achieved the best performance than others with AUC of 0.767 [95% confidence interval (95%CI) was 0.692-0.836], accuracy of 0.875 (95%CI was 0.837-0.903) and F1 score of 0.190. The top 3 variables in this model were crystal solution volume with first 24 hours, heart rate and mean arterial pressure. The nomogram of the model showed that the total score between 150 and 230 were advisable. CONCLUSION The interpretable machine learning model including simple bedside parameters combined with APACHE II score could effectively identify the risk of death in elderly patients with critically illness.
Humans ; Critical Illness ; Machine Learning ; Aged ; Algorithms ; Intensive Care Units ; Retrospective Studies ; APACHE ; Prognosis ; Organ Dysfunction Scores ; Hospital Mortality ; Male ; Female

INTRODUCTION: This systematic review and meta-analysis aimed to evaluate the effectiveness and safety of adjunct systemic corticosteroid therapy in patients admitted to the intensive care unit (ICU) with bacterial community-acquired pneumonia (CAP). METHOD: We searched MEDLINE, Embase and the Cochrane Library to identify randomised controlled trials (RCTs) published from the databases' inception to February 2024. All RCTs evaluating the effect of systemic corticosteroids on mortality, compared to standard of care among adult bacterial CAP patients admitted to ICU were included. Bayesian meta-analysis was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Independent authors reviewed each study for eligibility, extracted data and assessed risk of bias in duplicate, with discrepancies referred to senior reviewers. RESULTS: A total of 6 RCTs comprising 1585 patients were included for analysis. In ICU patients with severe CAP who were treated with corticosteroids, there was no significant reduction in hospital mortality (risk ratio [RR] 0.70, 95% confidence interval [CI] 0.39-1.14, certainty of evidence: ⊕⊕⊝⊝ low) or all-cause mortality (RR 0.68, 95% CI 0.34-1.22, ⊕⊕⊝⊝ low) compared with placebo. The use of corticosteroids showed a significant reduction in mechanical ventilation post-intervention (RR 0.58, 95% CI 0.37-0.86, ⊕⊕⊕⊕ high) compared with placebo. In a subgroup analysis of patients treated with hydrocortisone, hospital mortality was significantly reduced (RR 0.45, 95% CI 0.20-0.88, ⊕⊕⊝⊝ low) compared with placebo. There was no significant increase in gastrointestinal bleeding, secondary infections or hyperglycaemia in patients treated with corticosteroids. CONCLUSION Corticosteroids significantly reduced mechanical ventilation requirements, and hydrocor-tisone significantly reduced hospital mortality. Further work is required to determine whether other corticosteroids reduce mortality among ICU patients with CAP.
Humans ; Adrenal Cortex Hormones/therapeutic use* ; Bayes Theorem ; Community-Acquired Infections/mortality* ; Critical Illness ; Hospital Mortality ; Intensive Care Units ; Pneumonia, Bacterial/mortality* ; Randomized Controlled Trials as Topic ; Respiration, Artificial

Child ; Critical Illness ; Hospital Mortality ; Humans ; Virus Diseases/epidemiology*

INTRODUCTION: There is paucity of data on the occurrence of cardiovascular events (CVEs) in critically ill patients with sepsis. We aimed to describe the incidence, risk factors and impact on mortality of CVEs in these patients. METHODS: This was a retrospective cohort study of critically ill patients admitted to the medical intensive care unit (ICU) between July 2015 and October 2016. The primary outcome was intra-hospital CVEs, while the secondary outcomes were in-hospital mortality, ICU and hospital length of stay. RESULTS: Patients with sepsis (n=662) had significantly more CVEs compared to those without (52.9% versus 23.0%, P<0.001). Among sepsis patients, 350 (52.9%) had 1 or more CVEs: 59 (8.9%) acute coronary syndrome; 198 (29.9%) type 2 myocardial infarction; 124 (18.7%) incident atrial fibrillation; 76 (11.5%) new or worsening heart failure; 32 (4.8%) cerebrovascular accident; and 33 (5.0%) cardiovascular death. Factors associated with an increased risk of CVEs (adjusted relative risk [95% confidence interval]) included age (1.013 [1.007-1.019]); ethnicity-Malay (1.214 [1.005-1.465]) and Indian (1.240 [1.030-1.494]) when compared to Chinese; and comorbidity of ischaemic heart disease (1.317 [1.137-1.527]). There were 278 patients (79.4%) who developed CVEs within the first week of hospitalisation. Sepsis patients with CVEs had a longer median (interquartile range [IQR]) length of stay in the ICU (6 [3-12] vs 4 [2-9] days, P<0.001), and hospital (21 [10-42] vs 15 [7-30] days, P<0.001) compared to sepsis patients without CVEs. There was no difference in in-hospital mortality between the 2 groups (46.9% vs 45.8%, P=0.792). CONCLUSION CVEs complicate half of the critically ill patients with sepsis, with 79.4% of patients developing CVEs within the first week of hospitalisation, resulting in longer ICU and hospital length of stay.
Cardiovascular Diseases/epidemiology* ; Critical Illness/epidemiology* ; Hospital Mortality ; Humans ; Intensive Care Units ; Length of Stay ; Retrospective Studies ; Risk Factors ; Sepsis/epidemiology*

mortality.CONCLUSION: There is a high prevalence of VDD in critically ill Korean children. There were significant associations between the 25(OH) vitamin D level and gastrointestinal/hepatobiliary disorders, the pMODS score and with coagulation related factors. Further large-scale studies with more specific subgroup analyses are required to more precisely assess the clinical implications of VDD in critically ill pediatric patients.]]>
Bilirubin ; Blood Platelets ; C-Reactive Protein ; Child ; Critical Illness ; Disseminated Intravascular Coagulation ; Hemostasis ; Humans ; Intensive Care Units ; Length of Stay ; Mortality ; Multiple Organ Failure ; Pediatrics ; Prevalence ; Prothrombin Time ; Serum Albumin ; Thrombosis ; Ventilators, Mechanical ; Vitamin D Deficiency ; Vitamin D ; Vitamins

BACKGROUND: Unplanned intensive care unit admission (UIA) is associated with perioperative morbidity and mortality, and can be used as a surrogate marker for patient safety. This study aimed to compare the characteristics of planned and unplanned intensive care unit (ICU) admission groups. METHODS: We retrospectively reviewed the electronic medical records of adult patients admitted to the ICU after abdominal and thyroid surgery under general anesthesia between 2016 and 2017. Preoperative, intraoperative, and postoperative information of enrolled patients was recorded. We compared patients' characteristics and outcomes between the unplanned and planned admission groups. RESULTS: In the total cohort, the proportion of UIA was 82.8% (202/244). In the unplanned admission group, total hospital stay was significantly shorter and ICU stay longer than that in the planned admission group (19.0 and 3.0 days, respectively vs. 28.5 and 2.0 days, respectively). In-hospital mortality rates were 21.3% and 7.1% in the unplanned and planned groups, respectively (P = 0.055). Patients in the UIA group showed higher Acute Physiology And Chronic Health Evaluation II scores, higher American Society of Anesthesiologist physical status class, and more co-morbidities than those in the planned group. There were significant differences in the incidence of UIA among surgery types. CONCLUSIONS: The UIA group had a relatively high mortality rate and longer ICU stay. More critically ill patients tended to be admitted to the ICU without planning.
Adult ; Anesthesia ; Anesthesia, General ; APACHE ; Biomarkers ; Cohort Studies ; Critical Care ; Critical Illness ; Electronic Health Records ; Hospital Mortality ; Humans ; Incidence ; Intensive Care Units ; Length of Stay ; Mortality ; Patient Safety ; Perioperative Care ; Retrospective Studies ; Thyroid Gland

BACKGROUND: The objective of this study was to establish the efficacy and safety of procalcitonin (PCT)-guided antibiotic discontinuation in critically ill patients with sepsis in a country with a high prevalence of antimicrobial resistance and a national health insurance system. METHODS: In a multi-center randomized controlled trial, patients were randomly assigned to a PCT group (stopping antibiotics based on a predefined cut-off range of PCT) or a control group. The primary end-point was antibiotic duration. We also performed a cost-minimization analysis of PCT-guided antibiotic discontinuation. RESULTS: The two groups (23 in the PCT group and 29 in the control group) had similar demographic and clinical characteristics except for need for renal replacement therapy on ICU admission (46% vs. 14%; P = 0.010). In the per-protocol analysis, the median duration of antibiotic treatment for sepsis was 4 days shorter in the PCT group than the control group (8 days; interquartile range [IQR], 6–10 days vs. 14 days; IQR, 12–21 days; P = 0.001). However, main secondary outcomes, such as clinical cure, 28-day mortality, hospital mortality, and ICU and hospital stays were not different between the two groups. In cost evaluation, PCT-guided therapy decreased antibiotic costs by USD 30 (USD 241 in the PCT group vs. USD 270 in the control group). The results of the intention-to-treat analysis were similar to those obtained for the per-protocol analysis. CONCLUSION: PCT-guided antibiotic discontinuation in critically ill patients with sepsis could reduce the duration of antibiotic use and its costs with no apparent adverse outcomes. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02202941
Anti-Bacterial Agents ; Biomarkers ; Calcitonin ; Costs and Cost Analysis ; Critical Illness ; Hospital Mortality ; Humans ; Intensive Care Units ; Length of Stay ; Mortality ; National Health Programs ; Prevalence ; Renal Replacement Therapy ; Sepsis

BACKGROUND: The purpose of this study was to evaluate whether institutional case volume affects clinical outcomes in patients receiving mechanical ventilation for 48 hours or more. METHODS: We conducted a nationwide retrospective cohort study using the database of Korean National Healthcare Insurance Service. Between January 2007 and December 2016, 158,712 adult patients were included at 55 centers in Korea. Centers were categorized according to the average annual number of patients: > 500, 500 to 300, and < 300. RESULTS: In-hospital mortality rates in the high-, medium-, and low-volume centers were 32.6%, 35.1%, and 39.2%, respectively. After adjustment, in-hospital mortality was significantly higher in low-volume centers (adjusted odds ratio [OR], 1.332; 95% confidence interval [CI], 1.296–1.368; P < 0.001) and medium-volume centers (adjusted OR, 1.125; 95% CI, 1.098–1.153; P < 0.001) compared to high-volume centers. Long-term survival for up to 8 years was better in high-volume centers. CONCLUSION: Centers with higher case volume (> 500 patients/year) showed lower in-hospital mortality and long-term mortality, compared to centers with lower case volume (< 300 patients/year) in patients who required mechanical ventilation for 48 hours or more.
Adult ; Cohort Studies ; Critical Illness ; Delivery of Health Care ; Hospital Mortality ; Humans ; Insurance ; Korea ; Mortality ; Odds Ratio ; Respiration, Artificial ; Retrospective Studies

BACKGROUND: Admission blood glucose (BG) level is a predictor of mortality in critically ill patients with various conditions. However, limited data are available regarding this relationship in critically ill patients with cardiovascular diseases according to diabetic status. METHODS: A total of 1,780 patients (595 with diabetes) who were admitted to cardiac intensive care unit (CICU) were enrolled from a single center registry. Admission BG level was defined as maximal serum glucose level within 24 hours of admission. Patients were divided by admission BG level: group 1 (< 7.8 mmol/L), group 2 (7.8–10.9 mmol/L), group 3 (11.0–16.5 mmol/L), and group 4 (≥ 16.6 mmol/L). RESULTS: A total of 105 patients died in CICU (62 non-diabetic patients [5.2%] and 43 diabetic patients [7.9%]; P = 0.105). The CICU mortality rate increased with admission BG level (1.7%, 4.8%, 10.3%, and 18.8% from group 1 to group 4, respectively; P < 0.001). On multivariable analysis, hypertension, mechanical ventilator, continuous renal replacement therapy, acute physiology and chronic health evaluation II (APACHE II) score, and admission BG level significantly influenced CICU mortality in non-diabetic patients (group 1 vs. group 3: hazard ratio [HR], 3.31; 95% confidence interval [CI], 1.47–7.44; P = 0.004; group 1 vs. group 4: HR, 6.56; 95% CI, 2.76–15.58; P < 0.001). However, in diabetic patients, continuous renal replacement therapy and APACHE II score influenced CICU mortality but not admission BG level. CONCLUSION: Admission BG level was associated with increased CICU mortality in critically ill, non-diabetic patients admitted to CICU but not in diabetic patients.
APACHE ; Blood Glucose ; Cardiovascular Diseases ; Critical Care ; Critical Illness ; Diabetes Mellitus ; Humans ; Hypertension ; Intensive Care Units ; Mortality ; Prognosis ; Renal Replacement Therapy ; Ventilators, Mechanical