American Journal of Critical Care最新文献_第7页

Machine Learning-Based Prediction of Subsyndromal Delirium in Intensive Care Patients. 基于机器学习的重症监护患者亚综合征性谵妄预测。

IF 2.6 3区医学

American Journal of Critical Care Pub Date : 2026-01-01 DOI: 10.4037/ajcc2026815

Weiguang Wen, Xue Bai, Huimiao Jing, Ni Yang, Jie Zhai, Yingli Gao

{"title":"Machine Learning-Based Prediction of Subsyndromal Delirium in Intensive Care Patients.","authors":"Weiguang Wen, Xue Bai, Huimiao Jing, Ni Yang, Jie Zhai, Yingli Gao","doi":"10.4037/ajcc2026815","DOIUrl":"10.4037/ajcc2026815","url":null,"abstract":"Background: Subsyndromal delirium is common in intensive care unit (ICU) patients and can prolong hospital stay, increase costs, and worsen prognosis. Advance intervention to prevent subsyndromal delirium would be valuable.Objective: To construct a machine learning-based model to predict the risk of subsyndromal delirium in ICU patients.Methods: This prospective cohort study included data from 447 patients hospitalized in the ICU between September 2023 and August 2024. Eight independent predictors of subsyndromal delirium were identified by least absolute shrinkage and selection operator and multivariate logistic regression analyses. Four machine learning models and a logistic regression model were constructed and validated to obtain the optimal algorithmic model.Results: Subsyndromal delirium occurred in 90 ICU patients (20.1%). Richards-Campbell Sleep Questionnaire score, sedative use, restraint tape use, receipt of continuous renal replacement therapy or extracorporeal membrane oxygenation, intra-abdominal pressure, prealbumin level, history of alcohol consumption, and stroke were independent predictors of subsyndromal delirium. Of the 4 machine learning models constructed, the random forest model had the best comprehensive performance (area under the receiver operating characteristic curve, 0.885; F1 score, 0.629).Conclusions: Four machine learning-based risk prediction models and 1 traditional logistic regression model were developed to predict risk of subsyndromal delirium in ICU patients. Choosing a suitable model for early screening of ICU patients at high risk of subsyndromal delirium would allow medical staff to formulate individualized early intervention plans, which could improve patients' prognosis and save medical costs.","PeriodicalId":7607,"journal":{"name":"American Journal of Critical Care","volume":"35 1","pages":"20-31"},"PeriodicalIF":2.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145877549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unit Layout and Critical Care Nurses' Perceptions of Visibility, Teamwork, and Taking Breaks. 病房布局与重症护理护士对可见度、团队合作和休息的感知。

IF 2.6 3区医学

American Journal of Critical Care Pub Date : 2026-01-01 DOI: 10.4037/ajcc2026276

Yolanda Keys, Ellen Taylor

{"title":"Unit Layout and Critical Care Nurses' Perceptions of Visibility, Teamwork, and Taking Breaks.","authors":"Yolanda Keys, Ellen Taylor","doi":"10.4037/ajcc2026276","DOIUrl":"10.4037/ajcc2026276","url":null,"abstract":"Background: The compounding effects of providing care during the COVID-19 pandemic and subsequent post-pandemic staffing shortages have led many experienced nurses to leave the bedside, with novice nurses being hired to fill the gap. Less experienced nurses need access to team members for the consultation, collaboration, and support required for intensive care work. Decentralization of nursing work stations and large, private rooms have resulted in intensive care units with long corridors that separate coworkers and make activities such as coaching, mentoring, and finding assistance more challenging.Objectives: To examine relationships between critical care unit layouts and nurses' perceptions of teamwork, breaks, unit layout, and visibility.Methods: A national sample of nurses participated via an online survey in which respondents selected their unit layout from a variety of newly developed unit graphics and subsequently answered survey questions. Researchers explored relationships between teamwork and break-taking behaviors, unit layout, and both patient and coworker visibility with the aim of guiding health care leaders, design professionals, and the nursing profession in critical care unit design and operations.Results: A statistically significant relationship was found between nurses' perceptions of teamwork and the likelihood of taking both meal breaks and nonmeal breaks, but no correlation was identified between unit layout and teamwork.Conclusions: Although more research is needed to understand how unit layouts influence nursing outcomes, units that foster connection and collaboration between critical care team members may encourage break-taking behaviors.","PeriodicalId":7607,"journal":{"name":"American Journal of Critical Care","volume":"35 1","pages":"54-61"},"PeriodicalIF":2.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145877368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Discussion Guide for the Olson Article. 奥尔森文章讨论指南。

IF 2.2 3区医学

American Journal of Critical Care Pub Date : 2026-01-01 DOI: 10.4037/ajcc2026554

Grant A Pignatiello

引用次数: 0

The Role of Regret. 后悔的作用。

IF 2.2 3区医学

American Journal of Critical Care Pub Date : 2026-01-01 DOI: 10.4037/ajcc2026518

Richard H Savel, Carolina Escobar

引用次数: 0

Unraveling the Stubborn Problem of Alarm Fatigue in the Intensive Care Unit. 解开重症监护病房报警疲劳的顽疾。

IF 2.2 3区医学

American Journal of Critical Care Pub Date : 2026-01-01 DOI: 10.4037/ajcc2026671

Cindy Cain

引用次数: 0

From the Iron Lung to Artificial Intelligence: Integrating New Technology Into Critical Care. 从铁肺到人工智能：将新技术融入重症监护。

IF 2.6 3区医学

American Journal of Critical Care Pub Date : 2026-01-01 DOI: 10.4037/ajcc2026154

Seo Yoon Lee, Alvin D Jeffery

{"title":"From the Iron Lung to Artificial Intelligence: Integrating New Technology Into Critical Care.","authors":"Seo Yoon Lee, Alvin D Jeffery","doi":"10.4037/ajcc2026154","DOIUrl":"10.4037/ajcc2026154","url":null,"abstract":"Artificial intelligence technology has emerged rapidly and is being incorporated into the health care delivery system as a new bedside tool. Artificial intelligence has the potential to be paradigm-changing; however, critical care clinicians have a long history of adopting new technologies that transform care delivery in remarkable ways. Just as introduction of the mechanical ventilator revolutionized life support, artificial intelligence promises to transform modern critical care by improving prediction of disease course and patient outcomes, supporting clinical decision-making, and optimizing clinician workflow, with future potential for autonomous therapeutic adjustments and personalized care. However, as with mechanical ventilation, adopting artificial intelligence as a new technology requires caution and rigorous validation. Key challenges include ensuring accountability, preventing algorithmic bias, maintaining patient safety, and preserving the human element in care. It is vital to maintain a human-centered approach, in which artificial intelligence serves as a tool to augment, not replace, the nuanced judgment of health care professionals. To navigate this transition, critical care clinicians must become literate in artificial intelligence, understanding the capabilities and limitations of these new tools. It is crucial to cultivate a critical mindset, continuously validating artificial intelligence outputs against clinical judgment. Integrating artificial intelligence into team workflows, developing clear ethical guidelines, and fostering collaboration between clinicians and data scientists are essential for successful implementation. By proactively preparing for the transition, the critical care community can harness artificial intelligence's power to improve patient recovery and survival while ensuring that technology remains guided by human expertise and compassion.","PeriodicalId":7607,"journal":{"name":"American Journal of Critical Care","volume":"35 1","pages":"70-76"},"PeriodicalIF":2.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145877606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Spirit of Fear. 恐惧之灵。

IF 2.2 3区医学

American Journal of Critical Care Pub Date : 2025-11-01 DOI: 10.4037/ajcc2025138

Lakshman Swamy, Cindy L Munro

引用次数: 0

Reducing Delirium in Intensive Care Patients Receiving Mechanical Ventilation: An Innovative Approach. 减少重症监护患者接受机械通气的谵妄：一种创新方法。

IF 2.2 3区医学

American Journal of Critical Care Pub Date : 2025-11-01 DOI: 10.4037/ajcc2025215

Meredith Padilla

引用次数: 0

Importance of Verifying Arrhythmia Alarms After Aortic Valve Replacement Surgery. 主动脉瓣置换术后心律失常报警验证的重要性。

IF 2.2 3区医学

American Journal of Critical Care Pub Date : 2025-11-01 DOI: 10.4037/ajcc2025531

Sukardi Suba, Dillon J Dzikowicz, Mary G Carey, Michele M Pelter

引用次数: 0

Delirium Reduction via Scripted Family Voice Recordings in Critically Ill Patients Receiving Mechanical Ventilation. 危重病人接受机械通气时通过家庭录音减少谵妄。

IF 2.2 3区医学

American Journal of Critical Care Pub Date : 2025-11-01 DOI: 10.4037/ajcc2025486

Cindy L Munro, Zhan Liang, Maya N Elias, Ming Ji, Xusheng Chen, Paula L Kip, Judy Greengold, E Wesley Ely, Karel Calero

{"title":"Delirium Reduction via Scripted Family Voice Recordings in Critically Ill Patients Receiving Mechanical Ventilation.","authors":"Cindy L Munro, Zhan Liang, Maya N Elias, Ming Ji, Xusheng Chen, Paula L Kip, Judy Greengold, E Wesley Ely, Karel Calero","doi":"10.4037/ajcc2025486","DOIUrl":"10.4037/ajcc2025486","url":null,"abstract":"Background: Delirium affects many critically ill patients receiving mechanical ventilation and is an independent predictor of death, length of stay, cost of care, and acquired dementia. More evidence is needed for nonpharmacological interventions that reduce delirium in patients receiving mechanical ventilation in intensive care units (ICUs).Objectives: A structured intervention, Family Automated Voice Recording (FAVoR), used recorded voices of family members to provide patients receiving mechanical ventilation with hourly reorientation to the ICU environment during daytime hours. The primary aim was to compare the effect of the FAVoR intervention vs usual care on delirium in adults receiving mechanical ventilation in the ICU.Methods: This prospective, 2-arm, blinded randomized controlled trial included 178 adults receiving mechanical ventilation in 9 ICUs at 2 large hospitals in south Florida. Delirium was measured with the Confusion Assessment Method for the ICU, administered by study personnel twice daily for 7 days or until ICU discharge. Data analyses included descriptive statistics, χ2 tests, and multivariable modeling analysis following the intent-to-treat principle.Results: Clinical characteristics and demographics were similar between groups. Patients in the FAVoR group (n = 89) had more delirium-free days than did those in the usual-care group (n = 89) (P < .001). Response to the intervention was dose dependent; more doses of intervention were associated with less delirium (P < .001).Conclusions: The FAVoR intervention is a nonpharmacological, low-resource-using intervention to reorient ICU patients receiving mechanical ventilation. In this trial, FAVoR was effective in preventing delirium among these patients. ClinicalTrials.gov identifier: NCT03128671.","PeriodicalId":7607,"journal":{"name":"American Journal of Critical Care","volume":"34 6","pages":"429-437"},"PeriodicalIF":2.2,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13021135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0