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.

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.

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.

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.

Individualized intensive insulin therapy of diabetes: Not only thegoal, but also the time

Intensive insulin therapy has been extensively used to control blood glucose levels because of its ability to reduce the risk of chronic complications of diabetes.According to current guidelines,intensive glycemic control requires individu-alized glucose goals rather than as low as possible.During intensive therapy,rapid blood glucose reduction can aggravate microvascular and macrovascular complications,and prolonged overuse of insulin can lead to treatment-induced neuropathy and retinopathy,hypoglycemia,obesity,lipodystrophy,and insulin antibody syndrome.Therefore,we need to develop individualized hypoglycemic plans for patients with diabetes,including the time required for blood glucose normalization and the duration of intensive insulin therapy,which deserves further study.

Perspectives on non-emergent neonatal intensive care unit to pediatric intensive care unit care transfers in the United States

BACKGROUND There is a substantial population of long-stay patients who non-emergently transfer directly from the neonatal intensive care unit(NICU)to the pediatric intensive care unit(PICU)without an interim discharge home.These infants are often medically complex and have higher mortality relative to NICU or PICUonly admissions.Given an absence of data surrounding practice patterns for nonemergent NICU to PICU transfers,we hypothesized that we would encounter a broad spectrum of current practices and a high proportion of dissatisfaction with current processes.AIM To characterize non-emergent NICU to PICU transfer practices across the United States and query PICU providers’evaluations of their effectiveness.METHODS A cross-sectional survey was drafted,piloted,and sent to one physician representative from each of 115 PICUs across the United States based on membership in the PARK-PICU research consortium and membership in the Children’s Hospital Association.The survey was administered via internet(REDCap).Analysis was performed using STATA,primarily consisting of descriptive statistics,though logistic regressions were run examining the relationship between specific transfer steps,hospital characteristics,and effectiveness of transfer.RESULTS One PICU attending from each of 81 institutions in the United States completed the survey(overall 70%response rate).Over half(52%)indicated their hospital transfers patients without using set clinical criteria,and only 33%indicated that their hospital has a standardized protocol to facilitate non-emergent transfer.Fewer than half of respondents reported that their institution’s nonemergent NICU to PICU transfer practices were effective for clinicians(47%)or patient families(38%).Respondents evaluated their centers’transfers as less effective when they lacked any transfer criteria(P=0.027)or set transfer protocols(P=0.007).Respondents overwhelmingly agreed that having set clinical criteria and standardized protocols for non-emergent transfer were important to the patient-family experience and patient safety.CONCLUSION Most hospitals lacked any clinical criteria or protocols for non-emergent NICU to PICU transfers.More positive perceptions of transfer effectiveness were found among those with set criteria and/or transfer protocols.

In-hospital new-onset seizures in patients admitted to the medical intensive care unit:An observational study and algorithmic approach

BACKGROUND Seizures are one of the most common neurological complications encountered in the intensive care unit(ICU).They can occur in the background of exacerbation of a known neurological disease or secondary to non-neurological conditions such as sepsis and metabolic disturbances.However,there is a paucity of literature on the incidence and pattern of new-onset seizures in ICUs.AIM To study the incidence and patterns of new-onset seizures in patients admitted to the medical ICU.METHODS This was a prospective,multicenter,observational study performed in two tertiary care centers in Hyderabad,India over a period of 1 year.Patients upon ICU admission,who developed new-onset generalized tonic clonic seizures(GTCS),were enrolled.Those with a pre-existing seizure disorder,acute cerebrovascular accident,head injury,known structural brain lesions,or chronic liver disease were excluded as they have a higher likelihood of developing seizures.All enrolled patients were subjected to biochemical routines,radiological imaging of either computed tomography or magnetic resonance imaging,and other relevant laboratory tests as per clinical suspicion according to the protocol,and their data were recorded.Statistical analyses were conducted using descriptive statistics,χ2 tests,and linear regression.RESULTS A total of 61 of 2522 patients developed GTCS.Among all etiologies of seizures,metabolic causes were most frequent(35%)followed by infective causes(27%)and others(new-onset structural,drug withdrawal,druginduced,toxicology-related,and miscellaneous factors).Logistic regression analysis showed that increased sodium and calcium levels were associated with a lower likelihood of developing seizures.CONCLUSION This study identified the etiology of new-onset seizures developing in critically ill patients admitted to the ICU.These findings highlight the need for targeted monitoring of those at risk of developing seizures.

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.

Comparison of fungal vs bacterial infections in the medical intensive liver unit:Cause or corollary for high mortality?

BACKGROUND Due to development of an immune-dysregulated phenotype,advanced liver disease in all forms predisposes patients to sepsis acquisition,including by opportunistic pathogens such as fungi.Little data exists on fungal infection within a medical intensive liver unit(MILU),particularly in relation to acute on chronic liver failure.AIM To investigate the impact of fungal infections among critically ill patients with advanced liver disease,and compare outcomes to those of patients with bacterial infections.METHODS From our prospective registry of MILU patients from 2018-2022,we included 27 patients with culture-positive fungal infections and 183 with bacterial infections.We compared outcomes between patients admitted to the MILU with fungal infections to bacterial counterparts.Data was extracted through chart review.RESULTS All fungal infections were due to Candida species,and were most frequently blood isolates.Mortality among patients with fungal infections was significantly worse relative to the bacterial cohort(93%vs 52%,P<0.001).The majority of the fungal cohort developed grade 2 or 3 acute on chronic liver failure(ACLF)(90%vs 64%,P=0.02).Patients in the fungal cohort had increased use of vasopressors(96%vs 70%,P=0.04),mechanical ventilation(96%vs 65%,P<0.001),and dialysis due to acute kidney injury(78%vs 52%,P=0.014).On MILU admission,the fungal cohort had significantly higher Acute Physiology and Chronic Health Evaluation(108 vs 91,P=0.003),Acute Physiology Score(86 vs 65,P=0.003),and Model for End-Stage Liver Disease-Sodium scores(86 vs 65,P=0.041).There was no significant difference in the rate of central line use preceding culture(52%vs 40%,P=0.2).Patients with fungal infection had higher rate of transplant hold placement,and lower rates of transplant;however,differences did not achieve statistical significance.CONCLUSION Mortality was worse among patients with fungal infections,likely attributable to severe ACLF development.Prospective studies examining empiric antifungals in severe ACLF and associations between fungal infections and transplant outcomes are critical.

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.

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.

Effects of intensive psychological intervention on treatment compliance,psychological status,and quality of life of patients with epilepsy

BACKGROUND Epilepsy is a nervous system disease characterized by recurrent attacks,a long disease course,and an unfavorable prognosis.It is associated with an enduring therapeutic process,and finding a cure has been difficult.Patients with epilepsy are predisposed to adverse moods,such as resistance,anxiety,nervousness,and anxiety,which compromise treatment compliance and overall efficacy.AIM To explored the influence of intensive psychological intervention on treatment compliance,psychological status,and quality of life(QOL)of patients with epilepsy.METHODS The clinical data of 105 patients with epilepsy admitted between December 2019 and July 2023 were retrospectively analyzed,including those of 50 patients who underwent routine intervention(control group)and 55 who underwent intensive psychological intervention(research group).Treatment compliance,psychological status based on the Self-Rating Anxiety Scale(SAS)and Depression Scale Self-Rating Depression Scale(SDS)scores,hope level assessed using the Herth Hope Scale(HHS),psychological resilience evaluated using the Psychological Resilience Scale,and QOL determined using the QOL in Epilepsy-31 Inventory(QOLIE-31)were comparatively analyzed.RESULTS Treatment compliance in the research group was 85.5%,which is significantly better than the 68.0%of the control group.No notable intergroup differences in preinterventional SAS and SDS scores were identified(P>0.05);however,after the intervention,the SAS and SDS scores decreased significantly in the two groups,especially in the research group(P<0.05).The two groups also exhibited no significant differences in preinterventional HHS,Connor-Davidson Resilience Scale(CD-RISC),and QOLIE-31 scores(P>0.05).After 6 months of intervention,the research group showed evidently higher HHS,CD-RISC,tenacity,optimism,strength,and QOLIE-31 scores(P<0.05).CONCLUSION Intensive psychological intervention enhances treatment compliance,psychological status,and QOL of patients with epilepsy.

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.

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.

Evaluation of Economical and Intensive Use of Construction Land in a County Town:A case study of Wan’an County,Ji’an City

Taking the changes of construction land in Wan’an County over the years as the research object,the quantity and spatial characteristics of construction land in Wan’an County were analyzed,and the overall situation and regional differences of construction land utilization in Wan’an County were revealed.From the aspects of main influencing factors such as land use structure,land use intensity,land input intensity and output benefit,an evaluation indicator system was established to evaluate the economical and intensive use level of construction land in Wan’an County.The results show that the score of the economical and intensive use level of construction land in Wan’an County was 56.92,which was the lowest among all the districts and counties in Ji’an City.Based on the evaluation results,the corresponding economizing and intensive strategies were put forward,and the safeguard measures for its implementation were explored.The purpose is to provide some support for the preparation of territorial spatial planning,the delineation of urban development boundaries,and the potential exploitation of construction land stock,hoping to improve the utilization efficiency and benefit of construction land in Wan’an County,and promote the economic growth of Wan’an County to the stage of high-quality development.

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.

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.

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.