CHEST critical care最新文献

{"title":"Omitting Omission Bias in the ICU","authors":"Rajmund M. Niwinski MD ,&nbsp;Scott K. Aberegg MD, MPH","doi":"10.1016/j.chstcc.2026.100239","DOIUrl":"10.1016/j.chstcc.2026.100239","url":null,"abstract":"<div><div>In recent years, much attention has been given to cognitive biases as a source of error in diagnostic decision-making. Omission bias, which results from overemphasis on harms resulting from action while devaluing harms resulting from omission, may lead to suboptimal therapeutic decisions. In this “How I Do It” article, we highlight some common scenarios in critical care that are prone to influence by omission bias. We describe a simple and easily implementable approach to mitigating omission bias by shifting the frame of reference around the status quo, allowing clinicians to avoid the temptation to simplify therapeutic decisions by “going with the status quo flow.” This approach, termed <em>consider the opposite</em> in the cognitive psychology literature, prompts the clinician to ask, “If the situation were reversed, would I view the decision differently?” Based on this discussion, we propose a decision-making approach focused on ensuring the best outcome for the patient, rather than understandable, but misplaced, intuitions about asymmetric culpability around omission vs commission.</div></div>","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100239"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147419583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Challenges of Prognosticating Persistent Critical Illness","authors":"Kaitland M. Byrd PhD ,&nbsp;Madeline M. Lagina MD, MPH ,&nbsp;Kathleen T. Lee MPH ,&nbsp;Ashwatha Thenappan MD ,&nbsp;Jacqueline M. Kruser MD ,&nbsp;Theodore J. Iwashyna MD, PhD ,&nbsp;Hallie C. Prescott MD ,&nbsp;Elizabeth M. Viglianti MD, MPH","doi":"10.1016/j.chstcc.2025.100232","DOIUrl":"10.1016/j.chstcc.2025.100232","url":null,"abstract":"<div><h3>Background</h3><div>Medical decision-making in the ICU is influenced by a patient’s anticipated clinical course. However, intensivists struggle to identify accurately which patients will experience within-ICU events—such as new late-onset shock or acute hypoxic respiratory failure (AHRF)—that contribute to the development of persistent critical illness (PerCI). Given the uniqueness of patients who experience PerCI, understanding how intensivists process and incorporate evolving clinical information into their prognostication remains unknown for this population.</div></div><div><h3>Research Question</h3><div>What processes do intensivists use to prognosticate a patient’s risk of new shock or AHRF and PerCI developing and what challenges are encountered?</div></div><div><h3>Study Design and Methods</h3><div>We conducted semistructured interviews with 17 intensivists at a quaternary academic medical center from July 2022 through January 2023. Interviews occurred within 4 weeks of completing medical ICU service and lasted 30 to 60 minutes. Each interview focused on 2 real-world patient cases treated by the intensivist, using chart-stimulated recall to examine the information used to prognosticate each patient’s risk of new shock or AHRF and PerCI developing across the ICU course and the challenges of prognostication. We performed qualitative content analysis to explore the themes discussed by the intensivists.</div></div><div><h3>Results</h3><div>We identified 3 major themes about how intensivists formulate prognostic estimates about the risk of new shock or AHRF and PerCI: first, the contextualization of patient factors at ICU admission; second, the type of illness script or mental model of disease, including those within and outside of the intensivists’ expertise; and third, the impact of clinical setbacks and consultant input on the patient’s predicted clinical trajectory.</div></div><div><h3>Interpretation</h3><div>This study shows that intensivists rely on patient factors and the illness script to shape their prognostication. However, clinical setbacks and consultant recommendations were common, leading to changes in prognostication and subsequent medical decision-making. Future research should explore the value of time-limited trials in guiding treatment decisions in the context of prognostic uncertainty.</div></div>","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100232"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147419585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuous Opioid Infusion Among Patients Who Receive Mechanical Ventilation and Who Transition to Comfort-Focused Care","authors":"Justin M. Rucci MD ,&nbsp;Tenzin Dechen MPH ,&nbsp;Ashley O’Donoghue PhD ,&nbsp;Emma Lee BA ,&nbsp;Nicholas A. Bosch MD ,&nbsp;Allan J. Walkey MD ,&nbsp;Jennifer P. Stevens MD","doi":"10.1016/j.chstcc.2025.100214","DOIUrl":"10.1016/j.chstcc.2025.100214","url":null,"abstract":"","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100214"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reflective Biomarker or Independent Risk Predictor?","authors":"Alexandra A. Rizaldi BA ,&nbsp;Shi Nan Feng BSPH ,&nbsp;Maria Rain Jennings PhD ,&nbsp;Zachary Darby MD ,&nbsp;Shivalika Khanduja MBBS ,&nbsp;Albert Leng BA ,&nbsp;Diane E. Alejo BA ,&nbsp;James S. Gammie MD ,&nbsp;Glenn J.R. Whitman MD ,&nbsp;Hanghang Wang MD, PhD","doi":"10.1016/j.chstcc.2025.100221","DOIUrl":"10.1016/j.chstcc.2025.100221","url":null,"abstract":"<div><h3>Background</h3><div>Hyperlactatemia after cardiac surgery is associated with poor outcomes and often guides clinical decision-making.</div></div><div><h3>Research Question</h3><div>Do lactate dynamics provide incremental value beyond established risk models in predicting outcomes for patients who have undergone cardiac surgery?</div></div><div><h3>Study Design And Methods</h3><div>We retrospectively analyzed adult patients (≥ 18 years of age) undergoing cardiac operations at 1 institution from 2016 through 2021. Lactate parameters—time to clearance (first lactate ≤ 3 mM), trend (ascending vs descending), and maximum level within 24 hours—were assessed for associations with operative mortality, stroke, prolonged ventilation (&gt; 24 hours total), renal failure, deep sternal wound infection, reoperation, and delayed extubation (&gt; 6 hours initially) using multivariable logistic regression. We evaluated the predictive value of lactate parameters with the Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PROM) and maximum vasoactive-inotropic scores at 6 hours after surgery, a marker of pharmacologic support required for hemodynamic instability, using receiver operating characteristic curves, net reclassification and integrated discrimination improvement, and decision curve analysis.</div></div><div><h3>Results</h3><div>Among 2,514 patients, lactate clearance times were: 0 to 1 hours in 50%, &gt; 1 to 6 hours in 7%, &gt; 6 to 12 hours in 17%, &gt; 12 to 24 hours in 22%, and &gt; 24 hours or never ≤ 3 mM in 5%. Delayed clearance (&gt; 24 hours) was associated with older age (69 years vs 66 years; <em>P &lt;</em> .001), preoperative mechanical circulatory support (10% vs 7%; <em>P &lt;</em> .001), longer bypass times (125 minutes vs 101 minutes; <em>P &lt;</em> .001) and cross-clamp times (89 minutes vs 75 minutes; <em>P &lt;</em> .001), higher transfusion requirements (1 vs 0 units, <em>P &lt;</em> .001), and higher STS-PROM score (1.9% vs 1.1%; <em>P &lt;</em> .001). Although it was associated with increased operative mortality (adjusted OR, 9.23 [95% CI, 4.97-17.2]), it did not improve model performance of predicting operative mortality using STS-PROM score alone (area under the receiver operating characteristic curve, 0.83 vs 0.84; <em>P &gt;</em> .9).</div></div><div><h3>Interpretation</h3><div>Our results indicate that although delayed lactate clearance is associated with worse outcomes, it does not enhance risk prediction beyond STS-PROM, suggesting that lactate is a reflective rather than independent prognostic biomarker.</div></div>","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100221"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationship Between ICU Delirium and Change in Quality of Life, Mood, and Cognition Over 12 Months in Survivors of Acute Respiratory Failure","authors":"Haley Ferguson MD ,&nbsp;Adriano Sanjuan MD ,&nbsp;Anthony J. Perkins MS ,&nbsp;Maya Elias PhD ,&nbsp;Sophia Wang MD ,&nbsp;Suneetha Naidu Mekala MD ,&nbsp;Brendan Devine BS ,&nbsp;Zachary Koehler DO ,&nbsp;Rosalyn Chi MD ,&nbsp;Sujuan Gao PhD ,&nbsp;Babar Khan MD ,&nbsp;Sikandar Khan DO","doi":"10.1016/j.chstcc.2026.100242","DOIUrl":"10.1016/j.chstcc.2026.100242","url":null,"abstract":"<div><h3>Background</h3><div>Both acute respiratory failure (ARF) and ICU delirium are risk factors for postintensive care syndrome but whether quality of life (QoL) differs between delirium and subsyndromal delirium (SSD) over time is not well quantified.</div></div><div><h3>Research Question</h3><div>In ARF ICU survivors, are delirium and SSD associated with longitudinal changes in QoL, mood, and cognition up to 12 months postdischarge?</div></div><div><h3>Study Design and Methods</h3><div>In this secondary analysis, delirium (exposure variable) and SSD were assessed 2 times per day using the Richmond Agitation-Sedation Scale and Confusion Assessment Method for the ICU. QoL was the primary outcome; 36-Item Short Form Health Survey (SF-36) Physical Component Summary, SF-36 Mental Component Summary (MCS), Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) scores were collected at discharge, 3 months, 6 months, and 12 months. Mixed effects models were used with delirium group (delirium vs SSD vs no delirium), time, and an interaction term for group × time as independent variables.</div></div><div><h3>Results</h3><div>Of 456 ARF ICU survivors, 227 (50%) experienced delirium, 110 (24%) had SSD, and 121 (26%) had no delirium. The 3 groups did not significantly differ by pattern of change in SF-36 Physical Component Summary, SF-36 MCS, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, or RBANS scores over time. Delirium survivors had significantly lower SF-36 MCS scores vs SSD (predicted mean difference, –2.81; 95% CI, –5.03 to –0.59; <em>P</em> = .013) and no delirium (predicted mean difference, –2.93; 95% CI, –5.17 to –0.69; <em>P</em> = .011). Delirium survivors had significantly lower RBANS <em>z</em> scores than individuals with SSD (predicted mean difference, –0.19; 95% CI, –0.35 to –0.03; <em>P</em> = .023) and no delirium (predicted mean difference, –0.20; 95% CI, –0.36 to –0.03; <em>P</em> = .019). All outcomes showed improvement over time in all 3 groups.</div></div><div><h3>Interpretation</h3><div>Delirium, rather than SSD, was associated with lower SF-36 MCS and RBANS scores up to 12 months. Further research is needed to identify ideal time points for interventions aimed at these postintensive care syndrome-related outcomes.</div></div><div><h3>Clinical Trial Registration</h3><div><span><span>ClinicalTrials.gov</span><svg><path></path></svg></span>; No.: NCT03053245; URL: <span><span>www.clinicaltrials.gov</span><svg><path></path></svg></span></div></div>","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100242"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147419586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Use of the Rox Index to Guide High-Flow Nasal Cannula Therapy and the Need for Intubation Is Associated With Meaningful Patient Outcomes","authors":"Jonathan Taylor MD ,&nbsp;Aaron Gans MD ,&nbsp;Taylor Treacy MD ,&nbsp;Ashish Bosukonda MD ,&nbsp;Zhan Zhao MA ,&nbsp;Neha N. Goel MD","doi":"10.1016/j.chstcc.2025.100223","DOIUrl":"10.1016/j.chstcc.2025.100223","url":null,"abstract":"<div><h3>Background</h3><div>Acute hypoxemic respiratory failure (AHRF) is a common and life-threatening condition frequently managed with high-flow nasal cannula (HFNC) oxygenation. The ROX index, the ratio of oxygen saturation to F<span>io</span>₂ to respiratory rate, has been validated to predict HFNC oxygenation failure, but its impact on outcomes when used to guide decision-making in the timing of intubation remains unclear.</div></div><div><h3>Research Question</h3><div>What is the impact on outcomes when the ROX index is used to guide decisions-making in the timing of intubation in patients receiving high-flow nasal cannula therapy?</div></div><div><h3>Study Design and Methods</h3><div>A retrospective observational cohort study at an academic medical center emergency department (ED) was undertaken. Two hundred thirty-three adults were initiated on HFNC oxygenation for AHRF between January and December 2022. ROX indices were calculated retrospectively at 4, 6, and 12 hours after HFNC oxygenation initiation. Patients were categorized based on whether their care aligned with ROX predictions as ROX concordant or ROX discordant. The primary outcome was persistent organ dysfunction plus death (POD+D), a composite measure of death and ongoing need for mechanical ventilation, vasopressors, or new dialysis, assessed at day 28.</div></div><div><h3>Results</h3><div>Eighty-two percent of patients (n = 191) received ROX-concordant care, whereas 18% of patients (n = 42) received ROX-discordant care. Despite similar baseline characteristics, patients receiving ROX-discordant care experienced significantly worse outcomes: higher POD+D (62% vs 16%; <em>P</em> &lt; .001), 28-day mortality (38% vs 13.6%; <em>P</em> &lt; .001), and in-hospital mortality (50% vs 15%; <em>P</em> &lt; .001). Outcomes were driven by patients intubated despite ROX indices predicting HFNC oxygenation success. Multivariable regression showed that ROX-discordant care increased odds of POD+D 9-fold (OR, 9.2; 95% CI, 4.0-21.1; <em>P</em> &lt; .001) and increased the odds of 28-day mortality by 4.76 times compared with receiving ROX-concordant care (OR, 4.76; 95% CI, 1.76-12.88; <em>P</em> &lt; .001).</div></div><div><h3>Interpretation</h3><div>In patients treated with HFNC oxygenation in the ED, clinical decisions aligned with ROX index predictions were associated with significantly better outcomes. Discordant care, especially premature intubation, correlates with increased morbidity and mortality. These findings support prospective validation of improved outcomes with ROX-concordant actions.</div></div>","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100223"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing Granular Data to Evaluate a New Indication For an Old Therapy","authors":"Anna K. Barker MD, PhD,&nbsp;Michael W. Sjoding MD","doi":"10.1016/j.chstcc.2025.100216","DOIUrl":"10.1016/j.chstcc.2025.100216","url":null,"abstract":"","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100216"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"One-Year Effects of the Composite Allocation Score on Lung Transplantation in Critically Ill Patients","authors":"Richa Asija DO, MS ,&nbsp;Samantha E. Halpern MD, MHS ,&nbsp;George Olverson BS ,&nbsp;Antonia Kreso MD, PhD ,&nbsp;Seyed Alireza Rabi MD, PhD ,&nbsp;Eriberto Michel MD ,&nbsp;Asvin M. Ganapathi MD ,&nbsp;Brian C. Keller MD, PhD ,&nbsp;Nathaniel B. Langer MD ,&nbsp;Ruby Singh MD, MPH ,&nbsp;Asishana A. Osho MD, MPH","doi":"10.1016/j.chstcc.2026.100234","DOIUrl":"10.1016/j.chstcc.2026.100234","url":null,"abstract":"<div><h3>Background</h3><div>The Composite Allocation Score (CAS) was intended to optimize net benefit of lung transplantation, balancing medical urgency with anticipated posttransplant survival while broadening geographic distribution. This system may disadvantage critically ill patients in whom urgency may outweigh projected survival.</div></div><div><h3>Research Question</h3><div>What are the waitlist and posttransplant outcomes for patients in the ICU within the first year of the CAS era?</div></div><div><h3>Study Design and Methods</h3><div>Patients in the ICU in the Organ Procurement and Transplantation Network registry listed for or undergoing primary isolated lung transplantation between March 9, 2022, and March 9, 2024, were included and stratified into before and after the March 9, 2023, CAS system change. Survival between eras was compared using Cox regression and Kaplan-Meier curves for transplant recipients as well as waitlisted patients.</div></div><div><h3>Results</h3><div>Eight hundred fifty-one of 6,052 candidates (14%) and 998 of 5,716 recipients (18%) were in the ICU during the study period. In the CAS era, transplantation rate (334 of 368 [90.8%] vs 362 of 483 [75%]) was higher and waitlist duration was shorter (12 days vs 18 days; <em>P</em> &lt; .001 for both). Waitlist mortality (16 of 483 [3%] vs 12 of 368 [3%]; <em>P</em> = .97) and posttransplant 30-day mortality (15 of 453 [3%] vs 17 of 545 [3%]; <em>P</em> = .86) was similar in lung allocation score vs CAS eras. The primary outcome, 6-month mortality, also was similar in unadjusted analysis (36 of 453 [8%] vs 41 of 545 [8%]; <em>P</em> = .80). Although adjusted analysis showed a higher risk in the CAS era (adjusted hazard ratio [aHR], 1.65 [95% CI, 1.01-2.67]; <em>P</em> = .04), sensitivity analysis excluding 69 patients listed before CAS implementation but who underwent transplantation after CAS implementation did not demonstrate significant mortality (aHR, 1.61 [95% CI, 0.98-2.67]; <em>P</em> = .06). Other posttransplant outcomes of acute rejection, extracorporeal membrane oxygenation requirement, ventilator requirement, and posttransplant length of stay were comparable between eras (<em>P</em> &gt; .05).</div></div><div><h3>Interpretation</h3><div>Our results suggest that CAS implementation has increased lung transplantation rates and decreased waitlist time with no meaningful differences in primary and secondary outcomes between the eras. Continued reassessment of this continuous distribution policy is required to understand implications for high-acuity patients.</div></div>","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100234"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147419581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Treatment Response Phenotyping Informed by Patient Physiologic Characteristics Could Drive Precision Critical Care Through Augmented Intelligence","authors":"Andre L. Holder MD, FCCM ,&nbsp;Gwénolé Abgrall MD ,&nbsp;Ran Xiao PhD ,&nbsp;Jacques Kpodonu MD ,&nbsp;Shane Nanayakkara MD ,&nbsp;Irene Dankwa-Mullan MD, MPH ,&nbsp;Ann Zalucky MD, MSc ,&nbsp;Xavier Monnet MD, PhD ,&nbsp;Ewan C. Goligher MD, PhD","doi":"10.1016/j.chstcc.2025.100215","DOIUrl":"10.1016/j.chstcc.2025.100215","url":null,"abstract":"<div><div>The paradigm of precision medicine often focuses on novel biomarkers, but other types of data directly applicable to patient care could individualize treatment. The response to a cardiovascular and pulmonary intervention is important to critical care providers because it may determine the need and intensity of organ support. Using patient response to predict benefit (or no effect or harm) from an intervention could streamline care better for common syndromes of critical illness such as shock and ARDS, but the necessary data collection and analysis often are complex. Augmented intelligence technologies could assist with this kind of phenotyping because they can analyze and interpret complex multimodal data. In this narrative review, we summarize how augmented intelligence has been used to phenotype responses to diagnostic and therapeutic interventions in cardiovascular and pulmonary failure. We also discuss opportunities for future research that could make this precision approach useful in the clinical environment.</div></div>","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100215"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147419584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ICU Implementation Determinants and Delivery of Lung Protective Ventilation","authors":"Chad H. Hochberg MD, MHS ,&nbsp;Sophia A. Emetu MD ,&nbsp;Kevin J. Psoter PhD ,&nbsp;Sarina K. Sahetya MD, MHS ,&nbsp;Meeta P. Kerlin MD MSCE ,&nbsp;Theodore J. Iwashyna MD, PhD ,&nbsp;David N. Hager MD, PhD ,&nbsp;Michelle N. Eakin PhD","doi":"10.1016/j.chstcc.2026.100240","DOIUrl":"10.1016/j.chstcc.2026.100240","url":null,"abstract":"<div><h3>Background</h3><div>Lung protective ventilation (LPV) improves mortality in patients with ARDS and is applied widely in other patients receiving mechanical ventilation. Despite strong evidence, LPV is implemented inconsistently.</div></div><div><h3>Research Question</h3><div>Are staff-rated ICU implementation determinants associated with delivery of patient-level LPV delivery</div></div><div><h3>Study Design and Methods</h3><div>We conducted a cross-sectional survey of ICU clinical staff (January-June 2024) and a retrospective study of patients with hypoxemic respiratory failure receiving mechanical ventilation (January 2023-December 2024). We assessed staff-rated implementation determinants using validated surveys including domains for implementation culture (eg, team cooperation), staff stress, and available resources. We assessed the association of ICU-level survey scores with patient-level LPV (defined as tidal volume [V_T] ≤ 6.5 mL/kg of perdicted body weight (PBW) and plateau pressure ≤ 30 cm H₂O), and, as a complementary secondary outcome, hours spent at V_T &gt; 8 mL/kg PBW on day 1 of mechanical ventilation. We used mixed-effects negative binomial models including LPV hours as the outcome, eligible time as an offset, patient and ICU covariates, and a random effect for ICU.</div></div><div><h3>Results</h3><div>Survey measures from 469 ICU staff (50% response rate) were incorporated into the cohort of 2,120 patients across 5 hospitals and 14 ICUs. Median percentage compliance with LPV on day 1 was 68% (interquartile range, 0%-100%). A 1-SD increase in ICU implementation culture score was not associated with LPV (adjusted rate ratio [aRR], 1.04 [95% CI, 0.95-1.14]; <em>P</em> = .37), but was associated with less time at V_T &gt; 8 mL/kg PBW (aRR, 0.48 [95% CI, 0.32-0.71]; <em>P</em> &lt; .01). Increased staff stress was not associated with time at LPV (aRR, 0.98 [95% CI, 0.89-1.07]; <em>P</em> = .62), but was associated with more time at V_T &gt; 8 mL/kg (aRR, 1.71 [95% CI, 1.19-2.45]; <em>P</em> &lt; .01). Results for ICU resources were: aRR of 1.02 (95% CI, 0.88-1.17; <em>P</em> = .83) for LPV and aRR of 0.36 (95% CI, 0.20-0.64; <em>P</em> &lt; .01) for V_T &gt; 8 mL/kg PBW.</div></div><div><h3>Interpretation</h3><div>In this multihospital study, ICU implementation determinants were associated with receiving V_T &gt;8 mL/kg PBW, but not with a stricter LPV definition. These findings may inform development of interventions to enhance ICU implementation determinants and improve LPV delivery.</div></div>","PeriodicalId":93934,"journal":{"name":"CHEST critical care","volume":"4 1","pages":"Article 100240"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147419590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}