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.

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.

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.

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.

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.

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.

Intensive care unit-acquired weakness–preventive,and therapeutic aspects;future directions and special focus on lung transplantation

In this editorial,comments are made on an interesting article in the recent issue of the World Journal of Clinical Cases by Wang and Long.The authors describe the use of neural network model to identify risk factors for the development of intensive care unit(ICU)-acquired weakness.This condition has now become common with an increasing number of patients treated in ICUs and continues to be a source of morbidity and mortality.Despite identification of certain risk factors and corrective measures thereof,lacunae still exist in our understanding of this clinical entity.Numerous possible pathogenetic mechanisms at a molecular level have been described and these continue to be increasing.The amount of retrievable data for analysis from the ICU patients for study can be huge and enormous.Machine learning techniques to identify patterns in vast amounts of data are well known and may well provide pointers to bridge the knowledge gap in this condition.This editorial discusses the current knowledge of the condition including pathogenesis,diagnosis,risk factors,preventive measures,and therapy.Furthermore,it looks specifically at ICU acquired weakness in recipients of lung transplantation,because–unlike other solid organ transplants-muscular strength plays a vital role in the preservation and survival of the transplanted lung.Lungs differ from other solid organ transplants in that the proper function of the allograft is dependent on muscle function.Muscular weakness especially diaphragmatic weakness may lead to prolonged ventilation which has deleterious effects on the transplanted lung–ranging from ventilator associated pneumonia to bronchial anastomotic complications due to prolonged positive pressure on the anastomosis.

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.

Advancing critical care recovery:The pivotal role of machine learning in early detection of intensive care unit-acquired weakness

This editorial explores the significant challenge of intensive care unit-acquiredweakness(ICU-AW),a prevalent condition affecting critically ill patients,characterizedby profound muscle weakness and complicating patient recovery.Highlightingthe paradox of modern medical advances,it emphasizes the urgent needfor early identification and intervention to mitigate ICU-AW's impact.Innovatively,the study by Wang et al is showcased for employing a multilayer perceptronneural network model,achieving high accuracy in predicting ICU-AWrisk.This advancement underscores the potential of neural network models inenhancing patient care but also calls for continued research to address limitationsand improve model applicability.The editorial advocates for the developmentand validation of sophisticated predictive tools,aiming for personalized carestrategies to reduce ICU-AW incidence and severity,ultimately improving patientoutcomes in critical care settings.

Effects of nursing team communication and collaboration on treatment outcomes in intensive care unit patients with severe pneumonia

BACKGROUND Severe pneumonia is a common severe respiratory infection worldwide,and its treatment is challenging,especially for patients in the intensive care unit(ICU).AIM To explore the effect of communication and collaboration between nursing teams on the treatment outcomes of patients with severe pneumonia in ICU.METHODS We retrospectively analyzed 60 patients with severe pneumonia who were treated at the ICU of the hospital between January 1,2021 and December 31,2023.We compared and analyzed the respiratory mechanical indexes[airway resistance(Raw),mean airway pressure(mPaw),peak pressure(PIP)],blood gas analysis indexes(arterial oxygen saturation,arterial oxygen partial pressure,and oxygenation index),and serum inflammatory factor levels[C-reactive protein(CRP),procalcitonin(PCT),cortisol(COR),and high mobility group protein B1(HMGB1)]of all patients before and after treatment.RESULTS Before treatment,there was no significant difference in respiratory mechanics index and blood gas analysis index between 2 groups(P>0.05).However,after treatment,the respiratory mechanical indexes of patients in both groups were significantly improved,and the improvement of Raw,mPaw,plateau pressure,PIP and other indexes in the combined group after communication and collaboration with the nursing team was significantly better than that in the single care group(P<0.05).The serum CRP and PCT levels of patients were significantly decreased,and the difference was statistically significant compared with that of nursing group alone(P<0.05).The levels of serum COR and HMGB1 before and after treatment were also significantly decreased between the two groups.CONCLUSION The communication and collaboration of the nursing team have a significant positive impact on respiratory mechanics indicators,blood gas analysis indicators and serum inflammatory factor levels in the treatment of severe pneumonia patients in ICU.

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.

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.

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.

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.

Effects of strengthening prospective nursing practice on sleep quality,anxiety,and depression of awake patients in intensive care unit

BACKGROUND The intensive care unit(ICU)is a specialized hospital department.Awake patients in the ICU frequently encounter adverse psychological states,such as anxiety and fear,often accompanied by poor sleep quality.This situation has garnered significant attention within the medical community.AIM To investigate the impact of prospective nursing intervention strategies on the sleep quality and negative emotional state of conscious ICU patients.METHODS One hundred and twenty ICU awake patients admitted to our hospital were selected and randomly divided into control(n=60)and observation(n=60)groups.Patients in the control group were cared for using the conventional nursing model,while patients in the observation group were cared for using the prospective nursing model.Sleep improvement was assessed using the International Standardized Sleep Efficiency Formula and Pittsburgh Sleep Quality Index(PSQI).The PSQI,Generalized Anxiety Disorder 7-item(GAD-7)scale,Self-Depression Scale(SDS),and satisfaction before and after treatment were used to assess the negative emotional states of patients under the two care models.RESULTS Patient satisfaction in the observation group was significantly higher than in the control group.The GAD-7 and SDS scores in the observation group were significantly lower than those in the control group,and the total effective rate of sleep improvement in the observation group was significantly higher than in the control group.After treatment,the PSQI scores of the two groups significantly decreased(P<0.05).The decrease in the observation group was more significan than that in the control group,and the difference between the two groups was statistically significant.CONCLUSION Prospective nursing interventions can improve sleep quality and psychological levels and significantly affect conscious patients in the ICU,which is worthy of clinical application.

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,APACHE栻,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.