Prognostic impact of hypernatremia for septic shock patients in the intensive care unit

BACKGROUND Hypernatremia represents a significant electrolyte imbalance associated with numerous adverse outcomes,particularly in cases of intensive care unit(ICU)-acquired hypernatremia(IAH).Nevertheless,its relevance in patients with septic shock remains uncertain.AIM To identify independent risk factors and their predictive efficacy for IAH to improve outcomes in patients with septic shock.METHODS In the present retrospective single-center study,a cohort of 157 septic shock patients with concurrent hypernatremia in the ICU at The First Affiliated Hospital of Soochow University,between August 1,2018,and May 31,2023,were analyzed.Patients were categorized based on the timing of hypernatremia occurrence into the IAH group(n=62),the non-IAH group(n=41),and the normonatremia group(n=54).RESULTS In the present study,there was a significant association between the high serum sodium concentrations,excessive persistent inflammation,immunosuppression and catabolism syndrome and chronic critical illness,while rapid recovery had an apparent association with normonatremia.Moreover,multivariable analyses revealed the following independent risk factors for IAH:Total urinary output over the preceding three days[odds ratio(OR)=1.09;95%CI:1.02–1.17;P=0.014],enteral nutrition(EN)sodium content of 500 mg(OR=2.93;95%CI:1.13–7.60;P=0.027),and EN sodium content of 670 mg(OR=6.19;95%CI:1.75–21.98;P=0.005)were positively correlated with the development of IAH.Notably,the area under the curve for total urinary output over the preceding three days was 0.800(95%CI:0.678–0.922,P=0.001).Furthermore,maximum serum sodium levels,the duration of hypernatremia,and varying sodium correction rates were significantly associated with 28-day in-hospital mortality in septic shock patients(P<0.05).CONCLUSION The present findings illustrate that elevated serum sodium level was significantly associated with a poor prognosis in septic shock patients in the ICU.It is highly recommended that hypernatremia be considered a potentially important prognostic indicator for the outcome of septic shock.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Predicting intensive care unit-acquired weakness:A multilayer perceptron neural network approach

In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(ICUAW),a neuromuscular disorder affecting critically ill patients,by employing a novel processing strategy based on repeated machine learning.The editorial presents a dataset comprising clinical,demographic,and laboratory variables from intensive care unit(ICU)patients and employs a multilayer perceptron neural network model to predict ICUAW.The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW.This editorial contributes to the growing body of literature on predictive modeling in critical care,offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.

Epidemiological characteristics of traumatic spinal cord injuries in the intensive care unit from 2018 to 2023:a retrospective hospital-based study

BACKGROUND:The objective of this retrospective hospital-based study was to describe the epidemiological features of traumatic spinal cord injury(TSCI)in the intensive care unit(ICU)and assess the incidence and possible risk factors for venous thromboembolism(VTE)following TSCI.METHODS:We retrospectively reviewed the medical records of 370 patients with TSCI who were admitted between January 2018 and March 2023.The following parameters were collected:age,sex,body mass index,occupation,underlying diseases,smoking history,education level,etiology of injury,injury segments,American Spinal Injury Association(ASIA)Impairment Scale score,severity of injury,injury severity score(ISS),VTE risk score(Caprini score),treatment,VTE prophylaxis,ICU length of stay,length of hospital stay,concomitant injuries,and complications.Descriptive statistics were used to summarize the demographic and clinical characteristics of the study participants.Logistic regression analysis was used to determine the risk factors for VTE.RESULTS:The mean age of patients with TSCI was 55.5±13.4 years,with a male-to-female ratio of 6.5:1.The leading cause of TSCI was falls from height(46.5%),followed by traffic accidents(36.5%).The cervical spinal cord was the most affected segment,followed by the thoracolumbar region.Among all the patients,362(97.8%)had concomitant injuries.Complications were observed in 255 patients(68.9%)during hospitalization.The incidence rate of VTE was 25.1%.Logistic regression analysis revealed that age(OR=1.721,95%CI:1.207-2.454,P=0.003),mechanical ventilation(OR=3.427,95%CI:1.873-6.271,P<0.001),and non-use of chemical prophylaxis(OR=2.986,95%CI:1.749-5.099,P<0.001)were risk factors for VTE.CONCLUSION:Falls from height and traffic accidents were the main causes of TSCIs in the ICU,especially for male patients with cervical spinal cord injuries.VTE is a frequent complication in patients with TSCI in the ICU.Age,mechanical ventilation,and non-use of chemical prophylaxis were found to be independent risk factors for VTE following TSCI.

Machine learning insights on intensive care unit-acquired weakness

Intensive care unit-acquired weakness(ICU-AW)significantly hampers patient recovery and increases morbidity.With the absence of established preventive strategies,this study utilizes advanced machine learning methodologies to unearth key predictors of ICU-AW.Employing a sophisticated multilayer perceptron neural network,the research methodically assesses the predictive power for ICU-AW,pinpointing the length of ICU stay and duration of mechanical ventilation as pivotal risk factors.The findings advocate for minimizing these elements as a preventive approach,offering a novel perspective on combating ICU-AW.This research illuminates critical risk factors and lays the groundwork for future explorations into effective prevention and intervention strategies.

Discharging patients home from the intensive care unit:A new trend

Discharging patients directly to home from the intensive care unit(ICU)is becoming a new trend.This review examines the feasibility,benefits,challenges,and considerations of directly discharging ICU patients.By analyzing available evidence and healthcare professionals'experiences,the review explores the potential impacts on patient outcomes and healthcare systems.The practice of direct discharge from the ICU presents both opportunities and complexities.While it can potentially reduce costs,enhance patient comfort,and mitigate complications linked to extended hospitalization,it necessitates meticulous patient selection and robust post-discharge support mechanisms.Implementing this strategy successfully mandates the availability of home-based care services and a careful assessment of the patient's readiness for the transition.Through critical evaluation of existing literature,this review underscores the significance of tailored patient selection criteria and comprehensive post-discharge support systems to ensure patient safety and optimal recovery.The insights provided contribute evidence-based recommendations for refining the direct discharge approach,fostering improved patient outcomes,heightened satisfaction,and streamlined healthcare processes.Ultimately,the review seeks to balance patientcentered care and effective resource utilization within ICU discharge strategies.

Unveiling significant risk factors for intensive care unit-acquired weakness:Advancing preventive care

In this editorial,we discuss an article titled,“Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning,”published in a recent issue of the World Journal of Clinical Cases.Intensive care unit-acquired weakness(ICU-AW)is a debilitating condition that affects critically ill patients,with significant implications for patient outcomes and their quality of life.This study explored the use of artificial intelligence and machine learning techniques to predict ICU-AW occurrence and identify key risk factors.Data from a cohort of 1063 adult intensive care unit(ICU)patients were analyzed,with a particular emphasis on variables such as duration of ICU stay,duration of mechanical ventilation,doses of sedatives and vasopressors,and underlying comorbidities.A multilayer perceptron neural network model was developed,which exhibited a remarkable impressive prediction accuracy of 86.2%on the training set and 85.5%on the test set.The study highlights the importance of early prediction and intervention in mitigating ICU-AW risk and improving patient outcomes.

Evaluation of the effectiveness of preventive nursing measures for pressure injuries in patients in the neurology intensive care unit

BACKGROUND Patients in neurology intensive care units(ICU)are prone to pressure injuries(PU)due to factors such as severe illness,long-term bed rest,and physiological dysfunction.PU not only causes pain and complications to patients,but also increases medical burden,prolongs hospitalization time,and affects the recovery process.AIM To evaluate and optimize the effectiveness of pressure injury prevention nursing measures in neurology ICU patients.METHODS A retrospective study was conducted,and 60 patients who were admitted to the ICU of the Department of Neurology were selected and divided into an observation group and a control group according to the order of admission,with 30 people in each group.The observation group implemented pressure injury prevention and nursing measures,while the control group adopted routine care.RESULTS Comparison between observation and control groups following pressure injury prevention nursing intervention revealed significantly lower incidence rates in the observation group compared to the control group at 48 h(8.3%vs 26.7%),7 d(16.7%vs 43.3%),and 14 d(20.0%vs 50.0%).This suggests a substantial reduction in pressure injury incidence in the observation group,with the gap widening over time.Additionally,patients in the observation group exhibited quicker recovery,with a shorter average time to get out of bed(48 h vs 72 h)and a shorter average length of stay(12 d vs 15 d)compared to the control group.Furthermore,post-intervention,patients in the observation group reported significantly improved quality of life scores,including higher scores in body satisfaction,feeling and function,and comfort(both psychological and physiological),indicating enhanced overall well-being and comfort following the implementation of pressure injury prevention nursing measures.CONCLUSION Implementing pressure injury preventive care measures for neurology ICU patients will have better results.

Risk factors for intensive-care-unit-acquired weakness

Wang et al reported 1063 cases from the initial 14 d of intensive care unit(ICU)stay,and analyzed relevant data such as age,comorbidities,recent dosages,vapor pressure dosages,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,which are closely related to ICU-acquired weakness(ICUAW).It is suggested that the length of ICU stay and the duration of mechanical ventilation are the main factors.ICU-AW is the most common neuromuscular injury in the ICU,which affects clinical progression and outcomes of patients.This manuscript helps to improve the early recognition of ICU-AW,thereby reducing mortality and improving prognosis.

Development and validation of a nomogram for predicting in-hospital mortality of intensive care unit patients with liver cirrhosis

BACKGROUND Liver cirrhosis patients admitted to intensive care unit(ICU)have a high mortality rate.AIM To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis.METHODS We extracted demographic,etiological,vital sign,laboratory test,comorbidity,complication,treatment,and severity score data of liver cirrhosis patients from the Medical Information Mart for Intensive Care IV(MIMIC-IV)and electronic ICU(eICU)collaborative research database(eICU-CRD).Predictor selection and model building were based on the MIMIC-IV dataset.The variables selected through least absolute shrinkage and selection operator analysis were further screened through multivariate regression analysis to obtain final predictors.The final predictors were included in the multivariate logistic regression model,which was used to construct a nomogram.Finally,we conducted external validation using the eICU-CRD.The area under the receiver operating characteristic curve(AUC),decision curve,and calibration curve were used to assess the efficacy of the models.RESULTS Risk factors,including the mean respiratory rate,mean systolic blood pressure,mean heart rate,white blood cells,international normalized ratio,total bilirubin,age,invasive ventilation,vasopressor use,maximum stage of acute kidney injury,and sequential organ failure assessment score,were included in the multivariate logistic regression.The model achieved AUCs of 0.864 and 0.808 in the MIMIC-IV and eICU-CRD databases,respectively.The calibration curve also confirmed the predictive ability of the model,while the decision curve confirmed its clinical value.CONCLUSION The nomogram has high accuracy in predicting in-hospital mortality.Improving the included predictors may help improve the prognosis of patients.

Intensive care unit-acquired weakness:Unveiling significant risk factors and preemptive strategies through machine learning

This editorial discusses an article recently published in the World Journal of Clinical Cases,focusing on risk factors associated with intensive care unit-acquired weak-ness(ICU-AW).ICU-AW is a serious neuromuscular complication seen in criti-cally ill patients,characterized by muscle dysfunction,weakness,and sensory impairments.Post-discharge,patients may encounter various obstacles impacting their quality of life.The pathogenesis involves intricate changes in muscle and nerve function,potentially leading to significant disabilities.Given its global significance,ICU-AW has become a key research area.The study identified critical risk factors using a multilayer perceptron neural network model,highlighting the impact of intensive care unit stay duration and mechanical ventilation duration on ICU-AW.Recommendations were provided for preventing ICU-AW,empha-sizing comprehensive interventions and risk factor mitigation.This editorial stresses the importance of external validation,cross-validation,and model tran-sparency to enhance model reliability.Moreover,the application of machine learning in clinical medicine has demonstrated clear benefits in improving disease understanding and treatment decisions.While machine learning presents oppor-tunities,challenges such as model reliability and data management necessitate thorough validation and ethical considerations.In conclusion,integrating ma-chine learning into healthcare offers significant potential and challenges.Enhan-cing data management,validating models,and upholding ethical standards are crucial for maximizing the benefits of machine learning in clinical practice.

Evaluating neuromuscular electrical stimulation for preventing and managing intensive care unit-acquired weakness:Current evidence and future directions

Intensive care unit-acquired weakness(ICU-AW)is a prevalent issue in critical care,leading to significant muscle atrophy and functional impairment.Aiming to address this,Neuromuscular Electrical Stimulation(NMES)has been explored as a therapy.This systematic review assesses NMES's safety and effectiveness in enhancing functional capacity and mobility in pre-and post-cardiac surgery patients.NMES was generally safe and feasible,with intervention sessions varying in frequency and duration.Improvements in muscle strength and 6-minute walking test distances were observed,particularly in preoperative settings,but postoperative benefits were inconsistent.NMES showed promise in preventing muscle loss and improving strength,although its impact on overall functional capacity remained uncertain.Challenges such as short ICU stays and body composition affecting NMES efficacy were noted.NMES also holds potential for other conditions like cerebral palsy and stroke.Further research is needed to optimize NMES protocols and better understand its full benefits in preventing ICU-AW and improving patient outcomes.

Risk Factors for Mortality in Acute Kidney Injury in Intensive Care Units in Togo

Context: Acute kidney injury (AKI) in intensive care unit (ICU) is common and associated with very high mortality. In Togo, a tropical country with limited resources and only one nephrology department in the north, acute kidney injury seems to be a real tragedy with high mortality. Aims: to determine risk factors for mortality in acute kidney injury in the intensive care units. Methods and Material: We made a multicentric cross sectional study during 6 months in the four referral centers in northern Togo. Univariate and multivariate logistic regression was used to identify factors associated with mortality. Data were analyzed using RStudio 2023.04.1. Results: A total of 12.6% of patients admitted to intensive care had presented with AKI. The mean age was 49.6 ± 17.9. The sex ratio (M/F) was 2.1. Community-acquired AKI was in the majority (67.7%). Oligo anuria was the most frequent functional sign (38.4%). In our series, 81.6% of patients were in KDIGO stages 2 to 3. AKI was organic in 56.2% of cases. Mortality was 44.3%. In multivariate analysis, the main factors predictive of death were: respiratory distress (OR = 2.36;p Conclusions: Acute kidney injury in intensive care is common in northern Togo, and mortality is high. Identification of associated factors should help anticipate prognosis.

Study of the intensive care unit activity scale in the early rehabilitation of patients after direct cardiac surgery

BACKGROUND Direct cardiac surgery often necessitates intensive post-operative care,and the intensive care unit(ICU)activity scale represents a crucial metric in assessing and guiding early rehabilitation efforts to enhance patient recovery.AIM To clarify the clinical application value of the ICU activity scale in the early recovery of patients after cardiac surgery.METHODS One hundred and twenty patients who underwent cardiac surgery between September 2020 and October 2021 were selected and divided into two groups using the random number table method.The observation group was rated using the ICU activity scale and the corresponding graded rehabilitation interventions were conducted based on the ICU activity scale.The control group was assessed in accordance with the routine rehabilitation activities,and the postoperative rehabilitation indexes of the patients in both groups were compared(time of tracheal intubation,time of ICU admission,occurrence of complications,and activity scores before ICU transfer).The two groups were compared according to postoperative rehabilitation indicators(time of tracheal intubation,length of ICU stay,and occurrence of complications)and activity scores before ICU transfer.RESULTS In the observation group,tracheal intubation time lasted for 18.30±3.28 h and ICU admission time was 4.04±0.83 d,which were significantly shorter than the control group(t-values:2.97 and 2.038,respectively,P<0.05).The observation group also had a significantly lower number of complications and adverse events compared to the control group(P<0.05).Before ICU transfer,the observation group(6.7%)had few complications and adverse events than the control group(30.0%),and this difference was statistically significant(P<0.05).Additionally,the activity score was significantly higher in the observation(26.89±0.97)compared to the control groups(22.63±1.12 points)(t-value;-17.83,P<0.05).CONCLUSION Implementation of early goal-directed activities in patients who underwent cardiac surgery using the ICU activity scale can promote the recovery of cardiac function.

Effect of programmed comprehensive nursing on delirium incidence in intensive care unit children following severe cardiac surgery

BACKGROUND Programmed comprehensive nursing was adopted for intensive care unit(ICU)children following severe cardiac surgery to improve respiratory function and delirium incidence.AIM To explore how programmed comprehensive nursing impacts respiratory func-tion and delirium incidence in ICU children post cardiac surgery.METHODS Between January 2022 and January 2024,180 pediatric patients from the Chil-dren’s Hospital of Nanjing were admitted to the ICU after cardiac surgery and randomly grouped.The control group comprised 90 patients and received routine nursing care.The observation group comprised 90 patients and received program-med comprehensive nursing.Both groups received continuous nursing care until discharge.Their respiratory function,incidence of delirium,and clinical outcomes were compared.The memory state and sleep quality of both groups were com-pared.RESULTS The incidence of delirium was 5.56%in the observation group when admitted to ICU,which was lower than that in the control group(20.00%;P<0.05).The observation group demonstrated higher peak expiratory flow rate,respiratory frequency,deep breathing volume,and tidal volume in the ICU compared with the control group.Additionally,the observation group showed higher sleep depth,sleep latency,night awakening,return to sleep,and sleep quality com-pared with the control group(P<0.05).CONCLUSION Programmed comprehensive nursing in ICU patients following severe cardiac surgery can reduce the impact on respiratory function,improve sleep quality,and alleviate postoperative delirium,showing significant promise for clinical application.

Improvement of the nutritional support management system for patients in intensive care units

BACKGROUND Nutritional support for patients hospitalized in the intensive care unit(ICU)is an important part of clinical treatment and care,but there are significant implementation difficulties.AIM To introduce a modified nutritional support management system for ICU patients based on closed-loop information management and psychological counseling.METHODS The division of functions,personnel training,system construction,development of an intelligent decision-making software system,quality control,and improvement of the whole process were carried out to systematically manage nutritional support for ICU patients.RESULTS Following the implementation of the whole process management system,the scores of ICU medical staff’s knowledge,attitudes/beliefs,and practices regarding nutritional support were comprehensively enhanced.The proportion of hospital bed-days of total enteral nutrition(EN)in ICU patients increased from 5.58%to 11.46%,and the proportion of EN plus parenteral nutrition increased from 42.71%to 47.07%.The rate of EN initiation within 48 h of ICU admission increased from 37.50%to 48.28%,and the EN compliance rate within 72 h elevated from 20.59%to 31.72%.After the implementation of the project,the Self-rating Anxiety Scale score decreased from 61.07±9.91 points to 52.03±9.02 points,the Self-rating Depression Scale score reduced from 62.47±10.50 points to 56.34±9.83 points,and the ICU stay decreased from 5.76±2.77 d to 5.10±2.12 d.CONCLUSION The nutritional support management system based on closed-loop information management and psychological counseling achieved remarkable results in clinical applications in ICU patients.

Nurse Stress Associated with Delirium Care in Intensive Care Units: A Cross-Sectional Study

Background and Objectives: Delirium is highly prevalent in Intensive Care Units (ICUs). While prior studies have identified hyperactive and hyperalert behaviors as major stressors for nurses caring for delirious patients, limited research exists on ICU nurses’ stress specifically related to delirium care. This study aims to investigate the stress experienced by ICU nurses in China when managing patients with delirium. Methods: This cross-sectional survey was conducted in China from January to February 2023. A total of 243 ICU nurses participated by completing an online survey that included the Personal Information Questionnaire and the Strain of Caring for Delirium Index (SCDI). Although 260 responses were initially collected, 29 invalid questionnaires were excluded, resulting in a final sample size of 243 valid responses. The SCDI scale demonstrated reliable internal consistency, with Cronbach’s α coefficients of 0.744, 0.812, 0.778, and 0.920 across its four subscales. Results: The survey results indicated that hypoactive delirium behaviors were perceived as the most significant stressors when caring for delirious patients. Among the behaviors, “noisy/yelling” was identified as the most challenging, whereas “pulling at tubes, dressings” was rated as the least challenging. No significant associations were found between demographic factors and stress levels. Conclusion: This study sheds light on the stress levels ICU nurses experience when caring for delirious patients, particularly in relation to hypoactive behaviors. Based on these findings, it is recommended that nurse managers implement stress management strategies and provide targeted delirium-related care training to better support ICU nurses and enhance the quality of delirium care.

Unplanned intensive care admission leading to an adverse event:Incidence,preventability and feature analysis

Objective:To compare the characteristics of patients between adverse event(AE)group and non-AE group,and to assess the causes,preventability,and severity of AE.Methods:A retrospective triple-phase medical record study was conducted at a Spanish tertiary hospital.Data was collected over a 6-month period,including all patients with an unplanned intensive care admission.Demographic characteristics,APACHEⅡ,length of ICU stay,mortality were compare between AE and non-AE group causes,preventability and severity were analyzed in AE cases.Results:597 Patients were included in the study.The overall incidence of AEs was 17.3%(n=103),of which 83.5%were considered preventable.Mortality within the AE group was higher than in the non-AE group(23.3%vs.13.6%),making it 1.7 times more frequent in the AE group(95%CI:1.143-2.071).The primary cause of AE was associated with surgical procedures(43.7%).Of the AEs,18.4%were classified as mild,58.3%as moderate,and 23.3%as severe.Conclusions:The incidence of unplanned intensive care admissions due to AE is high and potentially preventable.This is concerning given the high mortality observed in patients admitted to the intensive care unit because of an AE,although direct causality cannot always be established.The findings emphasize the importance of patient safety and underscore the need for improved quality and management of care resources.They also indicate where efforts should be directed to enhance care risk management.

A Retrospective Analysis of Intoxicated Patients Admitted to the Intensive Care Unit: A Single-Institution Assessment in the Post-Pandemic Period

Background: The aim of this study was to evaluate the clinical and epidemiological characteristics of patients with acute intoxication admitted to the Intensive Care Unit (ICU). Material and Methods: An observational retrospective study was conducted on intoxicated patients who admitted to ICU between January 2022 and January 2024. Data were collected from the patients medical records. The demographic characteristics, causes of intoxications, clinical parameters, the mean stay in the ICU, treatment modalities and prognosis were recorded. Results: A total of 2875 critically ill patients were admitted during the study period, and 109 (3.79%) of them were acute intoxications. Their mean of ages was 38.09 ± 12.29. The female-to-male ratio was 1.37/1. Drugs were found to be the primary cause (62.39%) of intoxications, and analgesics, antidepressants, and antibiotics were the most frequent agents. Suicidal attempts were present in 66 patients, most of them were female (62.13%) and between 17 - 24 years (40.91%). The other common causes of intoxications were carbon monoxide (CO) (22.02%), methyl/ethyl alcohol (8.26%) and mushroom (5.50%). The mean stay in the ICU was 2.69 ± 0.89 days. Mechanical ventilation was applied to 10 of our patients. Renal replacement therapy was required in 6 patients. Despite all treatments, 6 of our patients died, and we found the mortality rate to be 5.50%. Conclusion: Intoxications were more frequent in young female patients and drugs were the most common cause with suicidal intent. Unfortunately, CO poisoning continues to be a very important problem in our city. These findings provided significant information about the characteristics of intoxications in Karabuk.

Pioneering role of machine learning in unveiling intensive care unitacquired weakness

In the research published in the World Journal of Clinical Cases,Wang and Long conducted a quantitative analysis to delineate the risk factors for intensive care unit-acquired weakness(ICU-AW)utilizing advanced machine learning methodologies.The study employed a multilayer perceptron neural network to accurately predict the incidence of ICU-AW,focusing on critical variables such as ICU stay duration and mechanical ventilation.This research marks a significant advancement in applying machine learning to clinical diagnostics,offering a new paradigm for predictive medicine in critical care.It underscores the importance of integrating artificial intelligence technologies in clinical practice to enhance patient management strategies and calls for interdisciplinary collaboration to drive innovation in healthcare.