Critical care explorations最新文献

[This corrects the article DOI: 10.1097/CCE.0000000000001130.].

Importance: A time-limited trial (TLT) is a collaborative plan among clinicians, patients, and families to use life-sustaining therapy for a defined duration, after which the patient's response informs whether to continue care directed toward recovery or shift the focus toward comfort. TLTs are a promising approach to help navigate uncertainty in critical illness, yet little is known about their current use.

Objectives: To characterize TLT use in patients with acute respiratory failure (ARF).

Design, setting, and participants: Prospective 12-month observational cohort study at an U.S. academic medical center of adult ICU patients with ARF receiving invasive mechanical ventilation for greater than or equal to 48 hours.

Main outcomes and measures: Primary exposure was TLT participation, identified by patients' ICU physician. Patient characteristics, care delivery elements, and hospital outcomes were extracted from the electronic medical record.

Results: Among 176 eligible patients, 36 (20.5%) participated in a TLT. Among 18 ICU attending physicians, nine (50%) participated in greater than or equal to 1 TLT (frequency 0-39% of patients cared for). Median TLT duration was 3.0 days (interquartile range [IQR], 3.0-4.5 d). TLT patients had a higher mean age (67.4 yr [sd, 12.0 yr] vs. 60.0 yr [sd, 16.0 yr]; p < 0.01), higher Charlson Comorbidity Index (5.1 [sd, 2.2] vs. 3.8 [sd, 2.6]; p < 0.01), and similar Sequential Organ Failure Assessment score (9.6 [sd, 3.3] vs. 9.5 [sd, 3.7]; p = 0.93), compared with non-TLT patients. TLT patients were more likely to die or be discharged to hospice (80.6% vs. 42.1%; p < 0.05) and had shorter ICU length of stay (median, 5.7 d [IQR, 4.0-9.0 d] vs. 10.3 d [IQR, 5.5-14.5 d]; p < 0.01).

Conclusions and relevance: In this study, approximately one in five patients with ARF participated in a TLT. Our findings suggest TLTs are used primarily in patients near end of life but with substantial physician variation, highlighting a need for evidence to guide optimal use.

Objective: Pulse oximetry, a ubiquitous vital sign in modern medicine, has inequitable accuracy that disproportionately affects minority Black and Hispanic patients, with associated increases in mortality, organ dysfunction, and oxygen therapy. Previous retrospective studies used self-reported race or ethnicity as a surrogate for skin tone which is believed to be the root cause of the disparity. Our objective was to determine the utility of skin tone in explaining pulse oximetry discrepancies.

Design: Prospective cohort study.

Setting: Patients were eligible if they had pulse oximetry recorded up to 5 minutes before arterial blood gas (ABG) measurements. Skin tone was measured using administered visual scales, reflectance colorimetry, and reflectance spectrophotometry.

Participants: Admitted hospital patients at Duke University Hospital.

Interventions: None.

Measurements and main results: Sao2-Spo2 bias, variation of bias, and accuracy root mean square, comparing pulse oximetry, and ABG measurements. Linear mixed-effects models were fitted to estimate Sao2-Spo2 bias while accounting for clinical confounders.One hundred twenty-eight patients (57 Black, 56 White) with 521 ABG-pulse oximetry pairs were recruited. Skin tone data were prospectively collected using six measurement methods, generating eight measurements. The collected skin tone measurements were shown to yield differences among each other and overlap with self-reported racial groups, suggesting that skin tone could potentially provide information beyond self-reported race. Among the eight skin tone measurements in this study, and compared with self-reported race, the Monk Scale had the best relationship with differences in pulse oximetry bias (point estimate: -2.40%; 95% CI, -4.32% to -0.48%; p = 0.01) when comparing patients with lighter and dark skin tones.

Conclusions: We found clinical performance differences in pulse oximetry, especially in darker skin tones. Additional studies are needed to determine the relative contributions of skin tone measures and other potential factors on pulse oximetry discrepancies.

Objectives: Increasing numbers of patients experience a prolonged stay in intensive care. Yet existing quality improvement (QI) tools used to improve safety and standardize care are not designed for their specific needs. This may result in missed opportunities for care and contribute to worse outcomes. Following an experience-based codesign process, our objective was to build consensus on the most important actionable processes of care for inclusion in a QI tool for adults with prolonged critical illness.

Design: Items were identified from a previous systematic review and interviews with former patients, their care partners, and clinicians. Two rounds of an online modified Delphi survey were undertaken, and participants were asked to rate each item from 1 to 9 in terms of importance for effective care; where 1-3 was not important, 4-6 was important but not critical, and 7-9 was critically important for inclusion in the QI tool. A final consensus meeting was then moderated by an independent facilitator to further discuss and prioritize items.

Setting: Carried out in the United Kingdom.

Patients/subjects: Former patients who experienced a stay of over 7 days in intensive care, their family members and ICU staff.

Interventions: None.

Measurements and main results: We recruited 116 participants: 63 healthcare professionals (54%), 45 patients (39%), and eight relatives (7%), to Delphi round 1, and retained 91 (78%) in round 2. Of the 39 items initially identified, 32 were voted "critically important" for inclusion in the QI tool by more than 70% of Delphi participants. These were prioritized further in a consensus meeting with 15 ICU clinicians, four former patients and one family member, and the final QI tool contains 25 items, including promoting patient and family involvement in decisions, providing continuity of care, and structured ventilator weaning and rehabilitation.

Conclusions: Using experience-based codesign and rigorous consensus-building methods we identified important content for a QI tool for adults with prolonged critical illness. Work is underway to understand tool acceptability and optimum implementation strategies.

Importance: In-hospital cardiac arrest (IHCA) is a significant public health burden. Rates of return of spontaneous circulation (ROSC) have been improving, but the best way to care for patients after the initial resuscitation remains poorly understood, and improvements in survival to discharge are stagnant. Existing North American cardiac arrest databases lack comprehensive data on the post-resuscitation period, and we do not know current post-IHCA practice patterns. To address this gap, we developed the Discover In-Hospital Cardiac Arrest (Discover IHCA) study, which will thoroughly evaluate current post-IHCA care practices across a diverse cohort.

Objectives: Our study collects granular data on post-IHCA treatment practices, focusing on temperature control and prognostication, with the objective of describing variation in current post-IHCA practice.

Design, setting, and participants: This is a multicenter, prospectively collected, observational cohort study of patients who have suffered IHCA and have been successfully resuscitated (achieved ROSC). There are 24 enrolling hospital systems (23 in the United States) with 69 individual enrolling hospitals (39 in the United States). We developed a standardized data dictionary, and data collection began in October 2023, with a projected 1000 total enrollments. Discover IHCA is endorsed by the Society of Critical Care Medicine.

Interventions, outcomes, and analysis: The study collects data on patient characteristics including pre-arrest frailty, arrest characteristics, and detailed information on post-arrest practices and outcomes. Data collection on post-IHCA practice was structured around current American Heart Association and European Resuscitation Council guidelines. Among other data elements, the study captures post-arrest temperature control interventions and post-arrest prognostication methods. Analysis will evaluate variations in practice and their association with mortality and neurologic function.

Conclusions: We expect this study, Discover IHCA, to identify variability in practice and outcomes following IHCA, and be a vital resource for future investigations into best-practice for managing patients after IHCA.

Objective: Pulse oximetry, a ubiquitous vital sign in modern medicine, has inequitable accuracy that disproportionately affects minority Black and Hispanic patients, with associated increases in mortality, organ dysfunction, and oxygen therapy. Previous retrospective studies used self-reported race or ethnicity as a surrogate for skin tone which is believed to be the root cause of the disparity. Our objective was to determine the utility of skin tone in explaining pulse oximetry discrepancies.

Design: Prospective cohort study.

Setting: Patients were eligible if they had pulse oximetry recorded up to 5 minutes before arterial blood gas (ABG) measurements. Skin tone was measured using administered visual scales, reflectance colorimetry, and reflectance spectrophotometry.

Participants: Admitted hospital patients at Duke University Hospital.

Interventions: None.

Measurements and main results: Sao₂-Spo₂ bias, variation of bias, and accuracy root mean square, comparing pulse oximetry, and ABG measurements. Linear mixed-effects models were fitted to estimate Sao₂-Spo₂ bias while accounting for clinical confounders.One hundred twenty-eight patients (57 Black, 56 White) with 521 ABG-pulse oximetry pairs were recruited. Skin tone data were prospectively collected using six measurement methods, generating eight measurements. The collected skin tone measurements were shown to yield differences among each other and overlap with self-reported racial groups, suggesting that skin tone could potentially provide information beyond self-reported race. Among the eight skin tone measurements in this study, and compared with self-reported race, the Monk Scale had the best relationship with differences in pulse oximetry bias (point estimate: -2.40%; 95% CI, -4.32% to -0.48%; p = 0.01) when comparing patients with lighter and dark skin tones.

Conclusions: We found clinical performance differences in pulse oximetry, especially in darker skin tones. Additional studies are needed to determine the relative contributions of skin tone measures and other potential factors on pulse oximetry discrepancies.

Background: Prediction-based strategies for physiologic deterioration offer the potential for earlier clinical interventions that improve patient outcomes. Current strategies are limited because they operate on inconsistent definitions of deterioration, attempt to dichotomize a dynamic and progressive phenomenon, and offer poor performance.

Objective: Can a deep learning deterioration prediction model (Deep Learning Enhanced Triage and Emergency Response for Inpatient Optimization [DETERIO]) based on a consensus definition of deterioration (the Adult Inpatient Decompensation Event [AIDE] criteria) and that approaches deterioration as a state "value-estimation" problem outperform a commercially available deterioration score?

Derivation cohort: The derivation cohort contained retrospective patient data collected from both inpatient services (inpatient) and emergency departments (EDs) of two hospitals within the University of California San Diego Health System. There were 330,729 total patients; 71,735 were inpatient and 258,994 were ED. Of these data, 20% were randomly sampled as a retrospective "testing set."

Validation cohort: The validation cohort contained temporal patient data. There were 65,898 total patients; 13,750 were inpatient and 52,148 were ED.

Prediction model: DETERIO was developed and validated on these data, using the AIDE criteria to generate a composite score. DETERIO's architecture builds upon previous work. DETERIO's prediction performance up to 12 hours before T0 was compared against Epic Deterioration Index (EDI).

Results: In the retrospective testing set, DETERIO's area under the receiver operating characteristic curve (AUC) was 0.797 and 0.874 for inpatient and ED subsets, respectively. In the temporal validation cohort, the corresponding AUC were 0.775 and 0.856, respectively. DETERIO outperformed EDI in the inpatient validation cohort (AUC, 0.775 vs. 0.721; p < 0.01) while maintaining superior sensitivity and a comparable rate of false alarms (sensitivity, 45.50% vs. 30.00%; positive predictive value, 20.50% vs. 16.11%).

Conclusions: DETERIO demonstrates promise in the viability of a state value-estimation approach for predicting adult physiologic deterioration. It may outperform EDI while offering additional clinical utility in triage and clinician interaction with prediction confidence and explanations. Additional studies are needed to assess generalizability and real-world clinical impact.

Objectives: Increasing numbers of patients experience a prolonged stay in intensive care. Yet existing quality improvement (QI) tools used to improve safety and standardize care are not designed for their specific needs. This may result in missed opportunities for care and contribute to worse outcomes. Following an experience-based codesign process, our objective was to build consensus on the most important actionable processes of care for inclusion in a QI tool for adults with prolonged critical illness.

Design: Items were identified from a previous systematic review and interviews with former patients, their care partners, and clinicians. Two rounds of an online modified Delphi survey were undertaken, and participants were asked to rate each item from 1 to 9 in terms of importance for effective care; where 1-3 was not important, 4-6 was important but not critical, and 7-9 was critically important for inclusion in the QI tool. A final consensus meeting was then moderated by an independent facilitator to further discuss and prioritize items.

Setting: Carried out in the United Kingdom.

Patients/subjects: Former patients who experienced a stay of over 7 days in intensive care, their family members and ICU staff.

Interventions: None.

Measurements and main results: We recruited 116 participants: 63 healthcare professionals (54%), 45 patients (39%), and eight relatives (7%), to Delphi round 1, and retained 91 (78%) in round 2. Of the 39 items initially identified, 32 were voted "critically important" for inclusion in the QI tool by more than 70% of Delphi participants. These were prioritized further in a consensus meeting with 15 ICU clinicians, four former patients and one family member, and the final QI tool contains 25 items, including promoting patient and family involvement in decisions, providing continuity of care, and structured ventilator weaning and rehabilitation.

Conclusions: Using experience-based codesign and rigorous consensus-building methods we identified important content for a QI tool for adults with prolonged critical illness. Work is underway to understand tool acceptability and optimum implementation strategies.

Importance: The relationship between post-hospital arrival factors and out-of-hospital cardiac arrest (OHCA) outcomes remains unclear.

Objectives: This study assessed the impact of post-hospital arrival factors on OHCA outcomes during the COVID-19 pandemic using a prediction model.

Design, setting, and participants: In this cohort study, data from the All-Japan Utstein Registry, a nationwide population-based database, between 2015 and 2021 were used. A total of 541,781 patients older than 18 years old who experienced OHCA of cardiac origin were included.

Main outcomes and measures: The primary exposure was trends in COVID-19 cases. The study compared the predicted proportion of favorable neurologic outcomes 1 month after resuscitation with the actual outcomes. Neurologic outcomes were categorized based on the Cerebral Performance Category score (1, good cerebral function; 2, moderate cerebral function).

Results: The prediction model, which had an area under the curve of 0.96, closely matched actual outcomes in 2019. However, a significant discrepancy emerged after the pandemic began in 2020, where outcomes continued to deteriorate as the virus spread, exacerbated by both pre- and post-hospital arrival factors.

Conclusions and relevance: Post-hospital arrival factors were as important as pre-hospital factors in adversely affecting the prognosis of patients following OHCA during the COVID-19 pandemic. The results suggest that the overall response of the healthcare system needs to be improved during infectious disease outbreaks to improve outcomes.