Critical care explorations最新文献

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.

Objectives: It is suggested that sepsis may be classified into four clinical phenotypes, using an algorithm employing 29 admission parameters. We applied a simplified phenotyping algorithm among patients with bacterial sepsis and severe COVID-19 and assessed characteristics and outcomes of the derived phenotypes.

Design: Retrospective analysis of data from prospective clinical studies.

Setting: Greek ICUs and Internal Medicine departments.

Patients and interventions: We analyzed 1498 patients, 620 with bacterial sepsis and 878 with severe COVID-19. We implemented a six-parameter algorithm (creatinine, lactate, aspartate transaminase, bilirubin, C-reactive protein, and international normalized ratio) to classify patients with bacterial sepsis intro previously defined phenotypes. Patients with severe COVID-19, included in two open-label immunotherapy trials were subsequently classified. Heterogeneity of treatment effect of anakinra was assessed. The primary outcome was 28-day mortality.

Measurements and main results: The algorithm validated the presence of the four phenotypes across the cohort of bacterial sepsis and the individual studies included in this cohort. Phenotype α represented younger patients with low risk of death, β was associated with high comorbidity burden, and δ with the highest mortality. Phenotype assignment was independently associated with outcome, even after adjustment for Charlson Comorbidity Index. Phenotype distribution and outcomes in severe COVID-19 followed a similar pattern.

Conclusions: A simplified algorithm successfully identified previously derived phenotypes of bacterial sepsis, which were predictive of outcome. This classification may apply to patients with severe COVID-19 with prognostic implications.

Importance: Acute respiratory distress syndrome (ARDS) is associated with high mortality and morbidity. Extracorporeal membrane oxygenation (ECMO) is one of the interventions that have been in practice for ARDS for decades.

Objectives: The purpose of the study was to investigate the outcomes of ECMO in pediatric trauma patients who suffered from ARDS.

Design: Observational cohort study.

Setting and participants: The Trauma Quality Improvement Program database for years 2017 to 2019 and 2021 through 2022 was accessed for the study. All children younger than 18 years old who were admitted to the hospital after trauma and suffered from ARDS were included in the study. Other variables included in the study were patients' demographics, clinical characteristics, Injury Severity Score (ISS), Glasgow Coma Scale (GCS) score, comorbidities, and outcomes.

Main outcomes and measures: ECMO is the exposure, and the outcomes are in-hospital mortality and hospital complications (acute kidney injury [AKI], pneumonia and deep vein thrombosis [DVT]).

Results: Of 453 patients who qualified for the study, propensity score matching found 50 pairs of patients. There were no significant differences identified between the groups, ECMO+ vs. ECMO- on patients' age in years (16 yr; interquartile range [IQR], 13.25-17 yr vs. 16 yr [14.25-17 yr]), race (White; 62.0% vs. 66.0%), sex (male; 78% vs. 76%), ISS (23 [IQR, 9.25-34] vs. 22 [9.25-32]), and GCS (15 [IQR, 3-15] vs. 13.5 [3-15]), mechanism of injury; and comorbidities. There was no difference between the groups, ECMO+ vs. ECMO-, in-hospital mortality (10.0% vs. 20.0%; p = 0.302), hospital complications (AKI 12.0% vs. 2.0%; p = 0.131), pneumonia (10.0% vs. 20.0%; p = 0.182 > ), and DVT (16% vs. 6%; p = 0.228).

Conclusions and relevance: No difference in mortality was observed in injured children who suffered from the ARDS and were placed on ECMO when compared with patients who were not placed on ECMO. Patients with trauma and ARDS who require ECMO have comparable outcomes to those who do not receive ECMO. A larger sample size study is needed to find the exact benefit of ECMO in this patients' cohort.

Objectives: It is suggested that sepsis may be classified into four clinical phenotypes, using an algorithm employing 29 admission parameters. We applied a simplified phenotyping algorithm among patients with bacterial sepsis and severe COVID-19 and assessed characteristics and outcomes of the derived phenotypes.

Design: Retrospective analysis of data from prospective clinical studies.

Setting: Greek ICUs and Internal Medicine departments.

Patients and interventions: We analyzed 1498 patients, 620 with bacterial sepsis and 878 with severe COVID-19. We implemented a six-parameter algorithm (creatinine, lactate, aspartate transaminase, bilirubin, C-reactive protein, and international normalized ratio) to classify patients with bacterial sepsis intro previously defined phenotypes. Patients with severe COVID-19, included in two open-label immunotherapy trials were subsequently classified. Heterogeneity of treatment effect of anakinra was assessed. The primary outcome was 28-day mortality.

Measurements and main results: The algorithm validated the presence of the four phenotypes across the cohort of bacterial sepsis and the individual studies included in this cohort. Phenotype α represented younger patients with low risk of death, β was associated with high comorbidity burden, and δ with the highest mortality. Phenotype assignment was independently associated with outcome, even after adjustment for Charlson Comorbidity Index. Phenotype distribution and outcomes in severe COVID-19 followed a similar pattern.

Conclusions: A simplified algorithm successfully identified previously derived phenotypes of bacterial sepsis, which were predictive of outcome. This classification may apply to patients with severe COVID-19 with prognostic implications.

Importance: In the setting of an active pandemic the impact of public vaccine hesitancy on healthcare workers has not yet been explored. There is currently a paucity of literature that examines how patient resistance to disease prevention in general impacts practitioners.

Objectives: The COVID-19 pandemic created unprecedented healthcare challenges with impacts on healthcare workers' wellbeing. Vaccine hesitancy added complexity to providing care for unvaccinated patients. Our study qualitatively explored experiences of healthcare providers caring for unvaccinated patients with severe COVID-19 infection in the intensive care setting.

Design: We used interview-based constructivist grounded theory methodology to explore experiences of healthcare providers with critically ill unvaccinated COVID-19 patients.

Setting and participants: Healthcare providers who cared for unvaccinated patients with severe COVID-19 respiratory failure following availability of severe acute respiratory syndrome coronavirus 2 vaccines were recruited from seven ICUs located within two large academic centers and one community-based hospital. We interviewed 24 participants, consisting of eight attending physicians, seven registered nurses, six critical care fellows, one respiratory therapist, one physiotherapist, and one social worker between March 2022 and September 2022 (approximately 1.5 yr after the availability of COVID-19 vaccines in Canada).

Analysis: Interviews were recorded, transcribed, de-identified, and coded to identify emerging themes. The final data was analyzed to generate the thematic framework. Reflexivity was employed to reflect upon and discuss individual pre-conceptions and opinions that may impact collection and interpretation of the data.

Results: Healthcare providers maintained dedication toward professionalism during provision of care, at the cost of suffering emotional turmoil from the pandemic and COVID-19 vaccine hesitancy. Evolving sources of stress associated with vaccine hesitancy included ongoing high volumes of critically ill patients, resource shortages, and visitation restrictions, which contributed to perceived emotional distress, empathy loss, and professional dissatisfaction. As a result, there were profound personal and professional consequences for healthcare professionals, with perceived impacts on patient care.

Conclusions: Our study highlights struggles of healthcare providers in fulfilling professional duties while navigating emotional stressors unique to vaccine hesitancy. System-based interventions should be explored to help providers navigate biases and moral distress, and to foster resilience for the next major healthcare system strain.

Objective: This study aimed to elucidate the association between IV contrast media CT and acute kidney injury (AKI) and in-hospital mortality among patients requiring emergency admission.

Design: In this retrospective observational study, we examined AKI within 48 hours after CT, renal replacement therapy (RRT) dependence at discharge, and in-hospital mortality in patients undergoing contrast-enhanced CT or nonenhanced CT. We performed 1:1 propensity score matching to adjust for confounders in the association between IV contrast media use and outcomes. Subgroup analyses were performed according to age, sex, diagnosis at admission, ICU admission, and preexisting chronic kidney disease (CKD).

Setting and patients: This study used the Medical Data Vision database between 2008 and 2019. This database is Japan's largest commercially available hospital-based claims database, covering about 45% of acute-care hospitals in Japan, and it also records laboratory results.

Interventions: None.

Measurements and main results: The study included 144,149 patients with (49,057) and without (95,092) contrast media exposure, from which 43,367 propensity score-matched pairs were generated. Between the propensity score-matched groups of overall patients, exposure to contrast media showed no significant risk of AKI (4.6% vs. 5.1%; odds ratio [OR], 0.899; 95% CI, 0.845-0.958) or significant risk of RRT dependence (0.6% vs. 0.4%; OR, 1.297; 95% CI, 1.070-1.574) and significant benefit for in-hospital mortality (5.4% vs. 6.5%; OR, 0.821; 95% CI, 0.775-0.869). In subgroup analyses regarding preexisting CKD, exposure to contrast media was a significant risk for AKI in patients with CKD but not in those without CKD.

Conclusions: In this large-scale observational study, IV contrast media was not associated with an increased risk of AKI but concurrently showed beneficial effects on in-hospital mortality among patients requiring emergency admission.