Acute and Critical Care最新文献

Background: Early detection of critical events in hospitalized patients improves clinical outcomes and reduces mortality rates. Traditional early warning score systems, such as the National Early Warning Score 2 (NEWS2), effectively identify at-risk patients. Integrating artificial intelligence (AI) could enhance the predictive accuracy and operational efficiency of such systems. The study describes the development and implementation of an AI-enhanced early warning system based on a modified NEWS2 scale with laboratory parameters (mNEWS2-Lab) and evaluates its ability to improve patient safety in hospital wards.

Methods: For this retrospective cohort study of 3,790 adults admitted to hospital wards, data were collected before and after implementing the mNEWS2-Lab protocol with and without AI enhancement. The study used a multivariate prediction model with statistical analyses such as Fisher's chi-square test, relative risk (RR), RR reduction, and various AI models (logistic regression, decision trees, neural networks). The economic cost of the intervention was also analyzed.

Results: The mNEWS2-Lab reduced critical events from 6.15% to 2.15% (RR, 0.35; P<0.001), representing a 65% risk reduction. AI integration further reduced events to 1.59% (RR, 0.26; P<0.001) indicating a 10% additional risk reduction and enhancing early warning accuracy by 15%. The intervention was cost-effective, resulting in substantial savings by reducing critical events in hospitalized patients.

Conclusions: The mNEWS2-Lab scale, particularly when integrated with AI models, is a powerful and cost-effective tool for the early detection and prevention of critical events in hospitalized patients.

Background: Carbon monoxide (CO) poisoning can lead to significant morbidity and mortality. However, relatively few studies have investigated its long-term mortality impact. This nationwide population-based cohort study examined the association between CO poisoning and long-term mortality.

Methods: This retrospective study utilized data from the National Health Insurance Service database in South Korea. We compared the patients with CO poisoning to those without CO poisoning. Inverse probability treatment weights were applied to both groups to control for potential confounding factors. Subsequently, mortality was assessed using the incidence rate and Cox proportional hazard ratios.

Results: This study included 23,387 patients with CO poisoning and 359,851 without it. Over a median follow-up period of 7.6 years after CO poisoning diagnosis, the mortality risk was 2.6 times higher in patients with CO poisoning compared to that in the control group. In a long-term follow-up of patients surviving beyond 30 days, mortality remained 2.18 times higher. Additionally, a higher mortality risk was observed in the relatively younger age group (18-39 years) and the group with fewer underlying diseases, as indicated by a Charlson Comorbidity Index score of 0.

Conclusions: CO poisoning is associated with an elevated long-term mortality rate particularly in a relatively young and healthy population.

Background: Long-term survival data for critically ill children discharged to post-intensive care clinics are scarce, especially in Asia. The main objective of this study was to assess the prevalence of post-intensive-care morbidity among pediatric intensive care unit (PICU) survivors at 1 month and 1 year after hospital discharge and to identify the associated risk factors.

Methods: We conducted a retrospective chart review of all children aged 1 month to 15 years who were admitted to the PICU for >48 hours from July 2019 to July 2022 and visited a post-intensive-care clinic 1 month and 1 year after hospital discharge. Post-intensive care morbidity was defined using the Pediatric Cerebral Performance Category (PCPC). Descriptive statistics, univariate, and multivariate analyses were conducted.

Results: A total of 111 children visited the clinic at 1 month, and 100 of these children visited the clinic at 1 year. Only 39 of 111 children (35.2%) had normal PCPC assessments at 1 month, while 54 of 100 (54.0%) were normal at 1 year. Baseline developmental delays were significantly associated with any degree of disability and at least moderate disability at both time points. Mechanical ventilation for >7 days was associated with at least moderate disability at both time points, while PICU stay >7 days was significantly associated with moderate disability at 1 month and any degree of disability at 1 year.

Conclusions: A substantial percentage of PICU survivors had persistent disabilities even 1 year after critical illness. A structured multidisciplinary post-intensive-care follow-up plan is warranted to provide optimal care for such children.

Background: Candidemia is associated with markedly high intensive care unit (ICU) mortality rates. Although the Impact of Early Enteral vs. Parenteral Nutrition on Mortality in Patients Requiring Mechanical Ventilation and Catecholamines (NUTRIREA-2) trial indicated that early enteral nutrition (EN) did not reduce 28-day mortality rates among critically ill patients with shock, the European Society for Clinical Nutrition and Metabolism (ESPEN) guidelines recommend avoiding EN in cases of uncontrolled shock. Whether increased caloric intake from EN positively impacts clinical outcomes in patients with candidemia and shock remains unclear.

Methods: We retrospectively collected data from a tertiary medical center between January 2015 and December 2018. We enrolled patients who developed shock within the first 7 days following ICU admission and received a diagnosis of candidemia during their ICU stay. Patients with an ICU stay shorter than 48 hours were excluded.

Results: The study included 106 patients, among whom the hospital mortality rate was 77.4% (82 patients). The median age of the patients was 71 years, and the median Acute Physiology and Chronic Health Evaluation II score was 29. The Cox regression model revealed that a higher 7-day average caloric intake through EN (hazard ratio, 0.61; 95% CI, 0.44-0.83) was significantly associated with lower hospital mortality rates. Our findings suggest EN as the preferred feeding route for critically ill patients with shock.

Conclusions: Increased caloric intake through EN may be associated with lower hospital mortality rates in patients with candidemia and shock.

Background: This meta-analysis was conducted to evaluate the impact of high-intensity statin treatment on new-onset postoperative atrial fibrillation (POAF) after coronary artery bypass grafting (CABG).

Methods: Four databases were searched for studies that enrolled patients who underwent CABG and investigated the impact of perioperative use of high-intensity statins on the occurrence rate of POAF. The primary outcome was the incidence of POAF. Secondary outcomes were operative mortality and perioperative myocardial infarction (PMI). Publication bias was assessed using a funnel plot and Egger's test.

Results: Nine articles (eight randomized controlled trials and one non-randomized study: n=3,072) were selected. Rosuvastatin (20 mg) was used in four studies, while atorvastatin (40-80 mg) was used in the other five studies. Reported incidences of POAF in the included studies ranged from 11% to 48.8%. Pooled analyses showed that the incidence of POAF was significantly lower in patients treated with high-intensity statins than in patients in the control group patients (odds ratio, 0.43; 95% CI, 0.27-0.68; P<0.001). Subgroup analyses showed that the impact of high-intensity statins was significant in studies using atorvastatin but not in studies using rosuvastatin. There was no significant subgroup difference in the primary endpoint between studies using a placebo and those using low-dose statins. Secondary outcomes, including operative mortality and the incidence of PMI, were not affected by high-intensity statin treatment.

Conclusions: Perioperative use of high-intensity statins is associated with a 57% reduction in the occurrence of POAF among patients undergoing CABG.

Background: Optimal sedation assessment in critically ill children remains challenging due to the subjective nature of behavioral scales and intermittent evaluation schedules. This study aimed to develop a deep learning model based on heart rate variability (HRV) parameters and vital signs to predict effective and safe sedation levels in pediatric patients.

Methods: This retrospective cross-sectional study was conducted in a pediatric intensive care unit at a tertiary children's hospital. We developed deep learning models incorporating HRV parameters extracted from electrocardiogram waveforms and vital signs to predict Richmond Agitation-Sedation Scale (RASS) scores. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC). The data were split into training, validation, and test sets (6:2:2), and the models were developed using a 1D ResNet architecture.

Results: Analysis of 4,193 feature sets from 324 patients achieved excellent discrimination ability, with AUROC values of 0.867, 0.868, 0.858, 0.851, and 0.811 for whole number RASS thresholds of -5 to -1, respectively. AUPRC values ranged from 0.928 to 0.623, showing superior performance in deeper sedation levels. The HRV metric SDANN2 showed the highest feature importance, followed by systolic blood pressure and heart rate.

Conclusions: A combination of HRV parameters and vital signs can effectively predict sedation levels in pediatric patients, offering the potential for automated and continuous sedation monitoring in pediatric intensive care settings. Future multi-center validation studies are needed to establish broader applicability.

Background: In trauma patients, unplanned intensive care unit (ICU) readmission (UIR) is associated with poor clinical outcomes. In this study, we aimed to analyze associated factors for UIR in trauma patients.

Methods: This retrospective study was conducted on trauma patients admitted to the ICU at a trauma center from January 2016 to December 2022. Clinical information at admission, the first ICU hospitalization, first discharge from the ICU, and reasons for readmission were collected. Patients who were successfully discharge from the ICU were compared to UIR patients. Logistic regression was performed to determine the factors with a significant impact on ICU readmission.

Results: Here, 5,529 patients were admitted to the ICU over 7 years, and 212 patients (3.8%) experienced UIR. Among patients who experienced UIR, 9 (4.2%) died. In the UIR patients, hospital stay (20 days [interquartile range, 13-35] vs. 45 days [28-67], P<0.001), total ICU stay (5 days [3- 11] vs. 17 days [9-35], P<0.001), and complications during the first ICU hospitalization were significantly higher. The most common reason for UIR was respiratory problem (53.8%). In multivariable analysis, cervical spine operation during the first ICU hospitalization (odds ratio, 6.56; 95% CI, 3.62-11.91; P<0.001), renal replacement therapy (RRT; 3.52, 2.06-5.99, P<0.001), and massive blood transfusion protocol (MTP; 1.74, 1.08-2.81, P=0.023) were most highly related with UIR.

Conclusions: Because UIR patients had poor outcomes, trauma patients who underwent cervical spine operation, RRT, or MTP require monitoring in the general ward, especially for respiratory problems.

Background: With the increasing incidence of violence against women (VAW), emergency department (ED) nurses should be trained to respond appropriately to victims of VAW (VVAW). However, the psychological preparedness of nurses caring for VVAW and its relationship to nurse gender remains unclear in Japan.

Methods: A nationwide self-administered questionnaire survey was conducted among 430 randomly selected certified emergency nurses. The questionnaire was a Japanese translation of the evaluation tools from the World Health Organization (WHO) curriculum "Caring for women subjected to violence: a WHO curriculum for training healthcare providers."

Results: The final sample included 104 participants, and the effective response rate was 24.2%. More than 60% of nurses had experience in caring for VVAW; however, only 10% had received training concerning VAW. The mean number of VVAW cared for by these nurses was 6.2 (standard deviation, 6.1) with no significant difference in nurse gender (P=0.52, effect size [ES]=0.09). Male nurses had a higher mean score of psychological preparedness than female nurses (22.6 vs. 20.4; P=0.03, ES=0.22); moreover, female nurses scored lower than male nurses on all items of the psychological preparedness evaluation. Less than half of the participants reported having institutional support systems.

Conclusions: Establishing an education program for all emergency nurses, providing support to ensure the psychological preparedness of female emergency nurses, and ensuring improvement of facilities nationwide are essential for enhancing nursing care for VVAW in Japanese EDs.

Background: Despite the high mortality associated with bloodstream infection (BSI), early detection of this condition is challenging in critical settings. The objective of this study was to create a machine learning tool for rapid recognition of BSI in critically ill children.

Methods: Data were extracted from a derivative cohort comprising patients who underwent at least one blood culture during hospitalization in the pediatric intensive care unit (PICU) of a tertiary hospital from January 2020 to June 2023 for model development. Data from another tertiary hospital were utilized for external validation. Variables selected for model development were age, white blood cell count with segmented neutrophil count, C-reactive protein, bilirubin, liver enzymes, glucose, body temperature, heart rate, and respiratory rate. Algorithms compared were extra trees, random forest, light gradient boosting, extreme gradient boosting, and CatBoost.

Results: We gathered 1,806 measurements and recorded 290 hospitalizations from 263 patients in the derivative cohort. Median age on admission was 43 months, with an interquartile range of 10-118.75 months, and a male predominance was observed (n=160, 55.2%). Candida albicans was the most prevalent pathogen, and median duration to confirm BSI was 3 days (range, 3-4). Patients with BSI experienced significantly higher in-hospital mortality and prolonged stays in the PICU than patients without BSI. Random forest classifier achieved the highest area under the receiver operating characteristic curve of 0.874 (0.762 for the validation set).

Conclusions: We developed a machine learning model that predicts BSI with acceptable performance. Further research is necessary to validate its effectiveness.