Pub Date : 2024-03-28DOI: 10.1101/2024.03.27.24304929
Aman Khanna, Krish Vaidya, Dharmesh Shah, Amaresh K. Ranjan, Anil Gulati
Background: Centhaquine is a resuscitative agent that acts on alpha-2B adrenergic receptors to enhance venous return in hypovolemic shock. The effect of centhaquine on cardiac output in patients with hypovolemic shock has not been reported. Methods: Trans-thoracic echocardiography was utilized to measure stroke volume (SV), cardiac output (CO), left ventricular outflow tract-velocity time integral (LVOT-VTI), left ventricular outflow tract diameter (LVOTd), heart rate (HR), left ventricular ejection fraction (LVEF), left ventricular fractional shortening (FS) and inferior vena cava (IVC) diameter before (0 min) and after centhaquine (0.01 mg/kg, iv infusion over 60 min) treatment (60 min, 120 min, and 300 min) in 12 randomly selected patients with hypovolemic shock enrolled in a prospective, multicenter, open-label phase IV clinical study (NCT05956418) of centhaquine in patients with hypovolemic shock. Results: A significant increase in SV (mL) was observed after 60, 120, and 300 minutes of centhaquine treatment. CO (mL/min) increased significantly at 120 and 300 min despite a decrease in HR at these times. A significant increase in IVC diameter and LVOT-VTI (mL) at these time points was observed, which indicated increased venous return. The LVEF and FS did not change, while the mean arterial pressure (MAP, mmHg) increased in patients after 120 and 300 minutes of centhaquine treatment. Positive correlations between IVC diameter and SV (R2 = 0.9556) and between IVC diameter and MAP (R2 = 0.8928) were observed, which indicated the effect of centhaquine mediated increase in venous return on SV, CO, and MAP. Conclusions: Centhaquine mediated increase in venous return appears to play a critical role in enhancing SV, CO, and MAP in patients with hypovolemic shock; these changes could be pivotal for reducing shock-mediated circulatory failure, promoting tissue perfusion, and improving patient outcomes. Trial registration: The phase IV trial reported in this study has Clinical Trials Registry, India; ctri.icmr.org.in, CTRI/2021/01/030263; clinicaltrials.gov, NCT05956418.
{"title":"Centhaquine Increases Stroke Volume and Cardiac Output in Patients with Hypovolemic Shock","authors":"Aman Khanna, Krish Vaidya, Dharmesh Shah, Amaresh K. Ranjan, Anil Gulati","doi":"10.1101/2024.03.27.24304929","DOIUrl":"https://doi.org/10.1101/2024.03.27.24304929","url":null,"abstract":"Background: Centhaquine is a resuscitative agent that acts on alpha-2B adrenergic receptors to enhance venous return in hypovolemic shock. The effect of centhaquine on cardiac output in patients with hypovolemic shock has not been reported.\u0000Methods: Trans-thoracic echocardiography was utilized to measure stroke volume (SV), cardiac output (CO), left ventricular outflow tract-velocity time integral (LVOT-VTI), left ventricular outflow tract diameter (LVOTd), heart rate (HR), left ventricular ejection fraction (LVEF), left ventricular fractional shortening (FS) and inferior vena cava (IVC) diameter before (0 min) and after centhaquine (0.01 mg/kg, iv infusion over 60 min) treatment (60 min, 120 min, and 300 min) in 12 randomly selected patients with hypovolemic shock enrolled in a prospective, multicenter, open-label phase IV clinical study (NCT05956418) of centhaquine in patients with hypovolemic shock.\u0000Results: A significant increase in SV (mL) was observed after 60, 120, and 300 minutes of centhaquine treatment. CO (mL/min) increased significantly at 120 and 300 min despite a decrease in HR at these times. A significant increase in IVC diameter and LVOT-VTI (mL) at these time points was observed, which indicated increased venous return. The LVEF and FS did not change, while the mean arterial pressure (MAP, mmHg) increased in patients after 120 and 300 minutes of centhaquine treatment. Positive correlations between IVC diameter and SV (R2 = 0.9556) and between IVC diameter and MAP (R2 = 0.8928) were observed, which indicated the effect of centhaquine mediated increase in venous return on SV, CO, and MAP.\u0000Conclusions: Centhaquine mediated increase in venous return appears to play a critical role in enhancing SV, CO, and MAP in patients with hypovolemic shock; these changes could be pivotal for reducing shock-mediated circulatory failure, promoting tissue perfusion, and improving patient outcomes.\u0000Trial registration: The phase IV trial reported in this study has Clinical Trials Registry, India; ctri.icmr.org.in, CTRI/2021/01/030263; clinicaltrials.gov, NCT05956418.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"140 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140325541","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}
Pub Date : 2024-03-27DOI: 10.1101/2024.03.26.24304926
Jariya Sereeyotin, Christopher Yarnell, Sangeeta Mehta
Purpose This study aimed to compare sedation management during and after intubation in the emergency department (ED) versus the intensive care unit (ICU). Methods This was a single-center retrospective cohort study of adults intubated in the ED or in the ICU and received mechanical ventilation between January 2018 and February 2022. We collected data from the electronic medical record. The primary outcome was duration from intubation to first documentation of light sedation, defined as a Sedation Agitation Scale score (SAS) of 3-4. Results The study included 264 patients, with 95 (36%) intubated in the ED and 169 (64%) in the ICU. Regarding anesthetic agents used for intubation, ketamine was the most commonly used drug in the ED and was used more frequently than in the ICU (61% vs 40%, p=0.001). Propofol was the predominant sedative used in the ICU, with a higher prevalence compared to the ED (50% vs 33%, p=0.01). Additionally, benzodiazepines and fentanyl were more frequently used in the ICU (39% vs 6%, p<0.001 and 68% vs 9.5%, p<0.001, respectively). Within 24 hours after intubation, 68% (65/95) ED patients and 82% (138/169) patients intubated in ICU achieved light sedation, with median durations of 13.5 hours and 10.5 hours. Patient location in the ED at intubation was associated with decreased probability of achieving light sedation at 24 hours (adjusted odds ratio 0.64, p=0.04). Conclusion Critically ill patients intubated in the ED are at risk of deeper sedation and a longer time to achieve light sedation compared to patients intubated in the ICU.
{"title":"Sedation practices in patients intubated in the emergency department compared to the intensive care unit.","authors":"Jariya Sereeyotin, Christopher Yarnell, Sangeeta Mehta","doi":"10.1101/2024.03.26.24304926","DOIUrl":"https://doi.org/10.1101/2024.03.26.24304926","url":null,"abstract":"Purpose\u0000This study aimed to compare sedation management during and after intubation in the emergency department (ED) versus the intensive care unit (ICU).\u0000Methods\u0000This was a single-center retrospective cohort study of adults intubated in the ED or in the ICU and received mechanical ventilation between January 2018 and February 2022. We collected data from the electronic medical record. The primary outcome was duration from intubation to first documentation of light sedation, defined as a Sedation Agitation Scale score (SAS) of 3-4.\u0000Results\u0000The study included 264 patients, with 95 (36%) intubated in the ED and 169 (64%) in the ICU. Regarding anesthetic agents used for intubation, ketamine was the most commonly used drug in the ED and was used more frequently than in the ICU (61% vs 40%, p=0.001). Propofol was the predominant sedative used in the ICU, with a higher prevalence compared to the ED (50% vs 33%, p=0.01). Additionally, benzodiazepines and fentanyl were more frequently used in the ICU (39% vs 6%, p<0.001 and 68% vs 9.5%, p<0.001, respectively). Within 24 hours after intubation, 68% (65/95) ED patients and 82% (138/169) patients intubated in ICU achieved light sedation, with median durations of 13.5 hours and 10.5 hours. Patient location in the ED at intubation was associated with decreased probability of achieving light sedation at 24 hours (adjusted odds ratio 0.64, p=0.04).\u0000Conclusion\u0000Critically ill patients intubated in the ED are at risk of deeper sedation and a longer time to achieve light sedation compared to patients intubated in the ICU.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140313531","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}
Pub Date : 2024-03-22DOI: 10.1101/2024.03.20.24304639
Charlotte Maschke, Laouen Belloli, Dragana Manasova, Jacobo D. Sitt, Stefanie Blain-Moraes
In the search for EEG markers of human consciousness, alpha power has long been considered a reliable marker which is fundamental for the assessment of unresponsive patients from all etiologies. However, recent evidence questioned the role of alpha power as a marker of consciousness and proposed the spectral exponent and spatial gradient as more robust and generalizable indexes. In this study, we analyzed a large-scale dataset of 260 unresponsive patients and investigated etiology-specific markers of level of consciousness, responsiveness and capacity to recover. We compare a set of candidate EEG makers: 1) absolute, relative and flattened alpha power; 2) spatial ratios; 3) the spectral exponent; and 4) signal complexity. Our results support the claim that alpha power is an etiology-specific marker, which has higher diagnostic value for anoxic patients. Meanwhile, the spectral slope showed diagnostic value for non-anoxic patients only. Changes in relative power and signal complexity were largely attributable to changes in the spectral slope. Grouping unresponsive patients from different etiologies together can confound or obscure the diagnostic value of different EEG markers of consciousness. Our study highlights the importance of analyzing different etiologies independently and emphasizes the need to develop clinical markers which better account for inter-individual and etiology-dependent differences.
{"title":"The role of etiology in the identification of clinical markers of consciousness: comparing EEG alpha power, complexity, and spectral exponent","authors":"Charlotte Maschke, Laouen Belloli, Dragana Manasova, Jacobo D. Sitt, Stefanie Blain-Moraes","doi":"10.1101/2024.03.20.24304639","DOIUrl":"https://doi.org/10.1101/2024.03.20.24304639","url":null,"abstract":"In the search for EEG markers of human consciousness, alpha power has long been considered a reliable marker which is fundamental for the assessment of unresponsive patients from all etiologies. However, recent evidence questioned the role of alpha power as a marker of consciousness and proposed the spectral exponent and spatial gradient as more robust and generalizable indexes. In this study, we analyzed a large-scale dataset of 260 unresponsive patients and investigated etiology-specific markers of level of consciousness, responsiveness and capacity to recover. We compare a set of candidate EEG makers: 1) absolute, relative and flattened alpha power; 2) spatial ratios; 3) the spectral exponent; and 4) signal complexity. Our results support the claim that alpha power is an etiology-specific marker, which has higher diagnostic value for anoxic patients. Meanwhile, the spectral slope showed diagnostic value for non-anoxic patients only. Changes in relative power and signal complexity were largely attributable to changes in the spectral slope. Grouping unresponsive patients from different etiologies together can confound or obscure the diagnostic value of different EEG markers of consciousness. Our study highlights the importance of analyzing different etiologies independently and emphasizes the need to develop clinical markers which better account for inter-individual and etiology-dependent differences.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140198112","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}
Pub Date : 2024-03-22DOI: 10.1101/2024.03.20.24304599
Son Ngoc Do, Tuan Quoc Dang, Chinh Quoc Luong, My Ha Nguyen, Dung Thi Pham, Viet Khoi Nguyen, Tan Dang Do, Thai Quoc Nguyen, Vuong Minh Nong, Khoi Hong Vo, Tan Cong Nguyen, Nhung Hong Khuat, Quynh Thi Pham, Dat Tien Hoang, Anh Diep Nguyen, Phuong Minh Nguyen, Duong Dai Cao, Dung Thuy Pham, Dung Tuan Dang, Dat Tuan Nguyen, Vinh Duc Nguyen, Thuan Quang Le, Hung Duc Ngo, Dung Van Nguyen, Thach The Pham, Dung Tien Nguyen, Nguyen Trung Nguyen, Nhung Thi Huynh, Nga Thu Phan, Cuong Duy Nguyen, Thom Thi Vu, Cuong Duy Do, Chi Van Nguyen, Giap Van Vu, Co Xuan Dao
Background Evaluating the prognosis of COVID-19 patients who may be at risk of mortality using the simple chest X-ray (CXR) severity scoring systems provides valuable insights for treatment decisions. This study aimed to assess how well the simplified Radiographic Assessment of Lung Edema (RALE) score could predict the death of critically ill COVID-19 patients in Vietnam. Methods From July 30 to October 15, 2021, we conducted a cross-sectional study on critically ill COVID-19 adult patients at an intensive care centre in Vietnam. We calculated the areas under the receiver operator characteristic (ROC) curve (AUROC) to determine how well the simplified RALE score could predict hospital mortality. In a frontal CXR, the simplified RALE score assigns a score to each lung, ranging from 0 to 4. The overall severity score is the sum of points from both lungs, with a maximum possible score of 8. We also utilized ROC curve analysis to find the best cut-off value for this score. Finally, we utilized logistic regression to identify the association of simplified RALE score with hospital mortality. Results Of 105 patients, 40.0% were men, the median age was 61.0 years (Q1-Q3: 52.0-71.0), and 79.0% of patients died in the hospital. Most patients exhibited bilateral lung opacities on their admission CXRs (99.0%; 100/102), with the highest occurrence of opacity distribution spanning three (18.3%; 19/104) to four quadrants of the lungs (74.0%; 77/104) and a high median simplified RALE score of 8.0 (Q1-Q3: 6.0-8.0). The simplified RALE score (AUROC: 0.747 [95% CI: 0.617-0.877]; cut-off value >=5.5; sensitivity: 93.9%; specificity: 45.5%; PAUROC <0.001) demonstrated a good discriminatory ability in predicting hospital mortality. After adjusting for confounding factors such as age, gender, Charlson Comorbidity Index, serum interleukin-6 level upon admission, and admission severity scoring systems, the simplified RALE score of >=5.5 (adjusted OR: 18.437; 95% CI: 3.215-105.741; p =0.001) was independently associated with an increased risk of hospital mortality. Conclusions This study focused on a highly selected cohort of critically ill COVID-19 patients with a high simplified RALE score and a high mortality rate. Beyond its good discriminatory ability in predicting hospital mortality, the simplified RALE score also emerged as an independent predictor of hospital mortality.
{"title":"Predictive validity of the simplified Radiographic Assessment of Lung Edema score for the mortality in critically ill COVID-19 patients with the B.1.617.2 (Delta) variant in Vietnam: a single-centre, cross-sectional study","authors":"Son Ngoc Do, Tuan Quoc Dang, Chinh Quoc Luong, My Ha Nguyen, Dung Thi Pham, Viet Khoi Nguyen, Tan Dang Do, Thai Quoc Nguyen, Vuong Minh Nong, Khoi Hong Vo, Tan Cong Nguyen, Nhung Hong Khuat, Quynh Thi Pham, Dat Tien Hoang, Anh Diep Nguyen, Phuong Minh Nguyen, Duong Dai Cao, Dung Thuy Pham, Dung Tuan Dang, Dat Tuan Nguyen, Vinh Duc Nguyen, Thuan Quang Le, Hung Duc Ngo, Dung Van Nguyen, Thach The Pham, Dung Tien Nguyen, Nguyen Trung Nguyen, Nhung Thi Huynh, Nga Thu Phan, Cuong Duy Nguyen, Thom Thi Vu, Cuong Duy Do, Chi Van Nguyen, Giap Van Vu, Co Xuan Dao","doi":"10.1101/2024.03.20.24304599","DOIUrl":"https://doi.org/10.1101/2024.03.20.24304599","url":null,"abstract":"Background Evaluating the prognosis of COVID-19 patients who may be at risk of mortality using the simple chest X-ray (CXR) severity scoring systems provides valuable insights for treatment decisions. This study aimed to assess how well the simplified Radiographic Assessment of Lung Edema (RALE) score could predict the death of critically ill COVID-19 patients in Vietnam. Methods From July 30 to October 15, 2021, we conducted a cross-sectional study on critically ill COVID-19 adult patients at an intensive care centre in Vietnam. We calculated the areas under the receiver operator characteristic (ROC) curve (AUROC) to determine how well the simplified RALE score could predict hospital mortality. In a frontal CXR, the simplified RALE score assigns a score to each lung, ranging from 0 to 4. The overall severity score is the sum of points from both lungs, with a maximum possible score of 8. We also utilized ROC curve analysis to find the best cut-off value for this score. Finally, we utilized logistic regression to identify the association of simplified RALE score with hospital mortality. Results Of 105 patients, 40.0% were men, the median age was 61.0 years (Q1-Q3: 52.0-71.0), and 79.0% of patients died in the hospital. Most patients exhibited bilateral lung opacities on their admission CXRs (99.0%; 100/102), with the highest occurrence of opacity distribution spanning three (18.3%; 19/104) to four quadrants of the lungs (74.0%; 77/104) and a high median simplified RALE score of 8.0 (Q1-Q3: 6.0-8.0). The simplified RALE score (AUROC: 0.747 [95% CI: 0.617-0.877]; cut-off value >=5.5; sensitivity: 93.9%; specificity: 45.5%; PAUROC <0.001) demonstrated a good discriminatory ability in predicting hospital mortality. After adjusting for confounding factors such as age, gender, Charlson Comorbidity Index, serum interleukin-6 level upon admission, and admission severity scoring systems, the simplified RALE score of >=5.5 (adjusted OR: 18.437; 95% CI: 3.215-105.741; p =0.001) was independently associated with an increased risk of hospital mortality. Conclusions This study focused on a highly selected cohort of critically ill COVID-19 patients with a high simplified RALE score and a high mortality rate. Beyond its good discriminatory ability in predicting hospital mortality, the simplified RALE score also emerged as an independent predictor of hospital mortality.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140198110","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}
Pub Date : 2024-03-19DOI: 10.1101/2024.03.18.24304462
Matthew M. Churpek, Kyle A. Carey, Ashley Snyder, Christopher J. Winslow, Emily R. Gilbert, Nirav S. Shah, Brian W. Patterson, Majid Afshar, Alan Weiss, Devendra N. Amin, Deborah J. Rhodes, Dana P. Edelson
Rationale: Early detection of clinical deterioration using early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective internal validation, and were not tested in important patient subgroups. Objectives: To develop a gradient boosted machine model (eCARTv5) for identifying clinical deterioration and then validate externally, test prospectively, and evaluate across patient subgroups. Methods: All adult patients hospitalized on the wards in seven hospitals from 2008-2022 were used to develop eCARTv5, with demographics, vital signs, clinician documentation, and laboratory values utilized to predict intensive care unit transfer or death in the next 24 hours. The model was externally validated retrospectively in 21 hospitals from 2009-2023 and prospectively in 10 hospitals from February to May 2023. eCARTv5 was compared to the Modified Early Warning Score (MEWS) and the National Early Warning Score (NEWS) using the area under the receiver operating characteristic curve (AUROC). Measurements and Main Results: The development cohort included 901,491 admissions, the retrospective validation cohort included 1,769,461 admissions, and the prospective validation cohort included 46,330 admissions. In retrospective validation, eCART had the highest AUROC (0.835; 95%CI 0.834, 0.835), followed by NEWS (0.766 (95%CI 0.766, 0.767)), and MEWS (0.704 (95%CI 0.703, 0.704)). eCART′s performance remained high (AUROC ≥ 0.80) across a range of patient demographics, clinical conditions, and during prospective validation. Conclusions: We developed eCARTv5, which accurately identifies early clinical deterioration in hospitalized ward patients. Our model performed better than the NEWS and MEWS retrospectively, prospectively, and across a range of subgroups.
{"title":"Multicenter Development and Prospective Validation of eCARTv5: A Gradient Boosted Machine Learning Early Warning Score","authors":"Matthew M. Churpek, Kyle A. Carey, Ashley Snyder, Christopher J. Winslow, Emily R. Gilbert, Nirav S. Shah, Brian W. Patterson, Majid Afshar, Alan Weiss, Devendra N. Amin, Deborah J. Rhodes, Dana P. Edelson","doi":"10.1101/2024.03.18.24304462","DOIUrl":"https://doi.org/10.1101/2024.03.18.24304462","url":null,"abstract":"Rationale: Early detection of clinical deterioration using early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective internal validation, and were not tested in important patient subgroups.\u0000Objectives: To develop a gradient boosted machine model (eCARTv5) for identifying clinical deterioration and then validate externally, test prospectively, and evaluate across patient subgroups. Methods: All adult patients hospitalized on the wards in seven hospitals from 2008-2022 were used to develop eCARTv5, with demographics, vital signs, clinician documentation, and laboratory values utilized to predict intensive care unit transfer or death in the next 24 hours. The model was externally validated retrospectively in 21 hospitals from 2009-2023 and prospectively in 10 hospitals from February to May 2023. eCARTv5 was compared to the Modified Early Warning Score (MEWS) and the National Early Warning Score (NEWS) using the area under the receiver operating characteristic curve (AUROC). Measurements and Main Results: The development cohort included 901,491 admissions, the retrospective validation cohort included 1,769,461 admissions, and the prospective validation cohort included 46,330 admissions. In retrospective validation, eCART had the highest AUROC (0.835; 95%CI 0.834, 0.835), followed by NEWS (0.766 (95%CI 0.766, 0.767)), and MEWS (0.704 (95%CI 0.703, 0.704)). eCART′s performance remained high (AUROC ≥ 0.80) across a range of patient demographics, clinical conditions, and during prospective validation.\u0000Conclusions: We developed eCARTv5, which accurately identifies early clinical deterioration in hospitalized ward patients. Our model performed better than the NEWS and MEWS retrospectively, prospectively, and across a range of subgroups.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"100 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140168871","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}
Pub Date : 2024-03-18DOI: 10.1101/2024.03.17.24304443
Marie-Laure Charpignon, Leo Anthony Celi, Marisa Cobanaj, Rene Eber, Amelia Fiske, Jack Gallifant, Chenyu Li, Gurucharan Lingamallu, Anton Petushkov, Robin Pierce
The recent imperative by the National Institutes of Health to share scientific data publicly underscores a significant shift in academic research. Effective as of January 2023, it emphasizes that transparency in data collection and dedicated efforts towards data sharing are prerequisites for translational research, from the lab to the bedside. Given the role of data access in mitigating potential bias in clinical models, we hypothesize that researchers who leverage open-access datasets rather than privately-owned ones are more diverse. In this brief report, we proposed to test this hypothesis in the transdisciplinary and expanding field of artificial intelligence (AI) for critical care. Specifically, we compared the diversity among authors of publications leveraging open datasets, such as the commonly used MIMIC and eICU databases, with that among authors of publications relying exclusively on private datasets, unavailable to other research investigators (e.g., electronic health records from ICU patients accessible only to Mayo Clinic analysts). To measure the extent of author diversity, we characterized gender balance as well as the presence of researchers from low- and middle-income countries (LMIC) and minority-serving institutions (MSI). Our comparative analysis revealed a greater contribution of authors from LMICs and MSIs among researchers leveraging open critical care datasets than among those relying exclusively on private data resources. The participation of women was similar between the two groups, albeit slightly larger in the former. Notably, although over 70% of all articles included at least one author inferred to be a woman, less than 25% had a woman as a first or last author. Importantly, we found that the proportion of authors from LMICs was substantially higher in the treatment than in the control group (10.1% vs. 6.2%, p<0.001), including as first and last authors. Moreover, we found that the proportion of US-based authors affiliated with a MSI was 1.5 times higher among articles in the treatment than in the control group, suggesting that open data resources attract a larger pool of participants from minority groups (8.6% vs. 5.6%, p<0.001).Thus, our study highlights the valuable contribution of the Open Data strategy to underrepresented groups, while also quantifying persisting gender gaps in academic and clinical research at the intersection of computer science and healthcare. In doing so, we hope our work points to the importance of extending open data practices in deliberate and systematic ways.
美国国立卫生研究院（National Institutes of Health）最近要求公开共享科学数据，这凸显了学术研究的重大转变。从 2023 年 1 月开始生效的这一规定强调，数据收集的透明度和为数据共享所做的不懈努力是转化研究（从实验室到床边）的先决条件。鉴于数据访问在减少临床模型中潜在偏差方面的作用，我们假设，利用开放访问数据集而不是私有数据集的研究人员更加多元化。在这份简短的报告中，我们提议在跨学科和不断扩展的重症监护人工智能（AI）领域验证这一假设。具体来说，我们比较了利用开放数据集（如常用的 MIMIC 和 eICU 数据库）发表文章的作者与完全依赖私人数据集（如只有梅奥诊所分析师才能访问的 ICU 患者电子健康记录）发表文章的作者之间的多样性。为了衡量作者的多样性程度，我们对性别平衡以及来自中低收入国家（LMIC）和少数民族服务机构（MSI）的研究人员进行了分析。我们的比较分析表明，在利用开放式重症监护数据集的研究人员中，来自中低收入国家（LMIC）和少数族裔服务机构（MSI）的作者比那些完全依赖于私有数据资源的研究人员有更大的贡献。两组研究人员中女性的参与度相似，只是前者略高。值得注意的是，尽管超过 70% 的文章中至少有一位作者被推断为女性，但只有不到 25% 的文章的第一或最后作者为女性。重要的是，我们发现治疗组中来自低收入国家的作者比例大大高于对照组（10.1% vs. 6.2%，p<0.001），包括第一作者和最后作者。此外，我们还发现，在治疗组的文章中，隶属于 MSI 的美国作者比例是对照组的 1.5 倍，这表明开放数据资源吸引了更多来自少数群体的参与者（8.6% vs. 5.6%，p<0.001）。因此，我们的研究强调了开放数据战略对代表性不足群体的宝贵贡献，同时也量化了计算机科学与医疗保健交叉领域的学术和临床研究中持续存在的性别差距。因此，我们希望我们的工作能指出以有意识和系统化的方式扩展开放数据实践的重要性。
{"title":"Diversity and inclusion: A hidden additional benefit of Open Data","authors":"Marie-Laure Charpignon, Leo Anthony Celi, Marisa Cobanaj, Rene Eber, Amelia Fiske, Jack Gallifant, Chenyu Li, Gurucharan Lingamallu, Anton Petushkov, Robin Pierce","doi":"10.1101/2024.03.17.24304443","DOIUrl":"https://doi.org/10.1101/2024.03.17.24304443","url":null,"abstract":"The recent imperative by the National Institutes of Health to share scientific data publicly underscores a significant shift in academic research. Effective as of January 2023, it emphasizes that transparency in data collection and dedicated efforts towards data sharing are prerequisites for translational research, from the lab to the bedside. Given the role of data access in mitigating potential bias in clinical models, we hypothesize that researchers who leverage open-access datasets rather than privately-owned ones are more diverse. In this brief report, we proposed to test this hypothesis in the transdisciplinary and expanding field of artificial intelligence (AI) for critical care. Specifically, we compared the diversity among authors of publications leveraging open datasets, such as the commonly used MIMIC and eICU databases, with that among authors of publications relying exclusively on private datasets, unavailable to other research investigators (e.g., electronic health records from ICU patients accessible only to Mayo Clinic analysts). To measure the extent of author diversity, we characterized gender balance as well as the presence of researchers from low- and middle-income countries (LMIC) and minority-serving institutions (MSI). Our comparative analysis revealed a greater contribution of authors from LMICs and MSIs among researchers leveraging open critical care datasets than among those relying exclusively on private data resources. The participation of women was similar between the two groups, albeit slightly larger in the former. Notably, although over 70% of all articles included at least one author inferred to be a woman, less than 25% had a woman as a first or last author. Importantly, we found that the proportion of authors from LMICs was substantially higher in the treatment than in the control group (10.1% vs. 6.2%, p<0.001), including as first and last authors. Moreover, we found that the proportion of US-based authors affiliated with a MSI was 1.5 times higher among articles in the treatment than in the control group, suggesting that open data resources attract a larger pool of participants from minority groups (8.6% vs. 5.6%, p<0.001).Thus, our study highlights the valuable contribution of the Open Data strategy to underrepresented groups, while also quantifying persisting gender gaps in academic and clinical research at the intersection of computer science and healthcare. In doing so, we hope our work points to the importance of extending open data practices in deliberate and systematic ways.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140168868","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}
Pub Date : 2024-03-15DOI: 10.1101/2024.03.14.24304230
Yukun Tan, Merve Dede, Vakul Mohanty, Jinzhuang Dou, Holly Hill, Elmer Bernstam, Ken Chen
Background: Advances in artificial intelligence (AI) have realized the potential of revolutionizing healthcare, such as predicting disease progression via longitudinal inspection of Electronic Health Records (EHRs) and lab tests from patients admitted to Intensive Care Units (ICU). Although substantial literature exists addressing broad subjects, including the prediction of mortality, length-of-stay, and readmission, studies focusing on forecasting Acute Kidney Injury (AKI), specifically dialysis anticipation like Continuous Renal Replacement Therapy (CRRT) are scarce. The technicality of how to implement AI remains elusive. Objective: This study aims to elucidate the important factors and methods that are required to develop effective predictive models of AKI and CRRT for patients admitted to ICU, using EHRs in the Medical Information Mart for Intensive Care (MIMIC) database. Methods: We conducted a comprehensive comparative analysis of established predictive models, considering both time-series measurements and clinical notes from MIMIC-IV databases. Subsequently, we proposed a novel multi-modal model which integrates embeddings of top-performing unimodal models, including Long Short-Term Memory (LSTM) and BioMedBERT, and leverages both unstructured clinical notes and structured time series measurements derived from EHRs to enable the early prediction of AKI and CRRT. Results: Our multimodal model achieved a lead time of at least 12 hours ahead of clinical manifestation, with an Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.888 for AKI and 0.997 for CRRT, as well as an Area Under the Precision Recall Curve (AUPRC) of 0.727 for AKI and 0.840 for CRRT, respectively, which significantly outperformed the baseline models. Additionally, we performed a SHapley Additive exPlanation (SHAP) analysis using the expected gradients algorithm, which highlighted important, previously underappreciated predictive features for AKI and CRRT. Conclusion: Our study revealed the importance and the technicality of applying longitudinal, multimodal modeling to improve early prediction of AKI and CRRT, offering insights for timely interventions. The performance and interpretability of our model indicate its potential for further assessment towards clinical applications, to ultimately optimize AKI management and enhance patient outcomes.
背景：人工智能（AI）的进步实现了彻底改变医疗保健的潜力，例如通过纵向检查电子健康记录（EHR）和重症监护病房（ICU）病人的实验室检查来预测疾病进展。虽然已有大量文献涉及死亡率、住院时间和再入院率预测等广泛主题，但侧重于预测急性肾损伤（AKI），特别是连续肾脏替代疗法（CRRT）等透析预期的研究却很少。如何实施人工智能的技术性问题仍然难以捉摸：本研究旨在利用重症监护医学信息市场（MIMIC）数据库中的电子病历，阐明为重症监护室住院患者开发 AKI 和 CRRT 有效预测模型所需的重要因素和方法：我们对已建立的预测模型进行了全面的比较分析，同时考虑了 MIMIC-IV 数据库中的时间序列测量结果和临床记录。随后，我们提出了一个新颖的多模态模型，该模型整合了包括长短期记忆（LSTM）和 BioMedBERT 在内的顶级单模态模型的嵌入，并利用非结构化临床笔记和来自电子病历的结构化时间序列测量结果来实现对 AKI 和 CRRT 的早期预测：我们的多模态模型可在临床表现出现前至少提前 12 小时进行预测，AKI 和 CRRT 的接收者工作特征曲线下面积（AUROC）分别为 0.888 和 0.997，AKI 和 CRRT 的精确度召回曲线下面积（AUPRC）分别为 0.727 和 0.840，明显优于基线模型。此外，我们还使用预期梯度算法进行了SHAPLE Additive exPlanation（SHAP）分析，突出显示了以前未被重视的AKI和CRRT的重要预测特征：我们的研究揭示了应用纵向多模式建模改善 AKI 和 CRRT 早期预测的重要性和技术性，为及时干预提供了启示。我们模型的性能和可解释性表明，它具有进一步评估临床应用的潜力，最终可优化 AKI 管理并改善患者预后。
{"title":"Forecasting Acute Kidney Injury and Resource Utilization in ICU patients using longitudinal, multimodal models","authors":"Yukun Tan, Merve Dede, Vakul Mohanty, Jinzhuang Dou, Holly Hill, Elmer Bernstam, Ken Chen","doi":"10.1101/2024.03.14.24304230","DOIUrl":"https://doi.org/10.1101/2024.03.14.24304230","url":null,"abstract":"Background: Advances in artificial intelligence (AI) have realized the potential of revolutionizing healthcare, such as predicting disease progression via longitudinal inspection of Electronic Health Records (EHRs) and lab tests from patients admitted to Intensive Care Units (ICU). Although substantial literature exists addressing broad subjects, including the prediction of mortality, length-of-stay, and readmission, studies focusing on forecasting Acute Kidney Injury (AKI), specifically dialysis anticipation like Continuous Renal Replacement Therapy (CRRT) are scarce. The technicality of how to implement AI remains elusive.\u0000Objective: This study aims to elucidate the important factors and methods that are required to develop effective predictive models of AKI and CRRT for patients admitted to ICU, using EHRs in the Medical Information Mart for Intensive Care (MIMIC) database.\u0000Methods: We conducted a comprehensive comparative analysis of established predictive models, considering both time-series measurements and clinical notes from MIMIC-IV databases. Subsequently, we proposed a novel multi-modal model which integrates embeddings of top-performing unimodal models, including Long Short-Term Memory (LSTM) and BioMedBERT, and leverages both unstructured clinical notes and structured time series measurements derived from EHRs to enable the early prediction of AKI and CRRT.\u0000Results: Our multimodal model achieved a lead time of at least 12 hours ahead of clinical manifestation, with an Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.888 for AKI and 0.997 for CRRT, as well as an Area Under the Precision Recall Curve (AUPRC) of 0.727 for AKI and 0.840 for CRRT, respectively, which significantly outperformed the baseline models. Additionally, we performed a SHapley Additive exPlanation (SHAP) analysis using the expected gradients algorithm, which highlighted important, previously underappreciated predictive features for AKI and CRRT.\u0000Conclusion: Our study revealed the importance and the technicality of applying longitudinal, multimodal modeling to improve early prediction of AKI and CRRT, offering insights for timely interventions. The performance and interpretability of our model indicate its potential for further assessment towards clinical applications, to ultimately optimize AKI management and enhance patient outcomes.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"2013 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140155654","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}
Pub Date : 2024-03-15DOI: 10.1101/2024.03.14.24303591
Clodagh E Beattie, Matt Thomas, Borislava Borislavova, Harry A Smith, Michael Ambler, Paul White, Kati Hayes, Danielle Milne, Aravind V Ramesh, Javier T Gonzalez, James A Betts, Anthony E Pickering
Introduction: Over half of patients who spend >48 hours in the intensive care unit (ICU) are fed via a nasogastric (NG) tube. Current guidance recommends continuous delivery of feed throughout the day and night. Emerging evidence from healthy human studies shows that NG feeding in an intermittent pattern (rather than continuous) promotes phasic hormonal, digestive and metabolic responses that are important for effective nutrition. It is not yet known whether this will translate to the critically ill population. Here we present the protocol for a proof-of-concept study comparing diurnal intermittent versus continuous feeding for patients in the intensive care unit. Methods and Analysis: The study is a single-centre, prospective, randomised, open-label trial comparing intermittent enteral nutrition with the current standard practice of continuous enteral feeding. It aims to recruit participants (n=30) needing enteral nutrition via an NG tube for >24 hours who will be randomised to a diurnal intermittent or a continuous feeding regime with equivalent nutritional value. The primary outcome is peak plasma insulin / c-peptide within 3 hours of delivering the morning bolus feed on the second study day, compared to that seen in the continuous feed delivery group at the same timepoint. Secondary outcomes include feasibility, tolerability, efficacy and metabolic / hormonal profiles. Ethics and Dissemination: This trial has been registered prospectively with the Clinical Trials Registry (clinicaltrials.gov - NCT06115044). We obtained ethical approval from the Wales Research Ethics Committee 3 prior to data collection (reference 23/WA/0297). We will publish the results of this study in an open-access peer-reviewed journal.
导言：在重症监护室（ICU）中度过 48 小时的患者中，有一半以上是通过鼻胃管喂食的。目前的指南建议全天候持续喂食。来自健康人体研究的新证据显示，间歇性（而非持续性）鼻胃管喂食可促进阶段性激素、消化和新陈代谢反应，这对有效营养非常重要。目前尚不清楚这是否适用于重症患者。在此，我们将介绍一项概念验证研究的方案，比较重症监护病房患者的昼夜间歇喂养与持续喂养。方法与分析：该研究是一项单中心、前瞻性、随机、开放标签试验，比较间歇性肠内营养与当前持续性肠内喂养的标准做法。研究旨在招募需要通过 NG 管进行 24 小时肠内营养的参与者（30 人），他们将被随机分配到营养价值相当的昼夜间歇喂养或持续喂养方案中。主要结果是在第二个研究日早晨给药后 3 小时内血浆胰岛素/c-肽达到峰值，并与连续给药组在同一时间点的血浆胰岛素/c-肽峰值进行比较。次要结果包括可行性、耐受性、疗效和代谢/激素概况。伦理与传播：本试验已在临床试验注册中心（clinicaltrials.gov - NCT06115044）进行了前瞻性注册。在数据收集之前，我们获得了威尔士研究伦理委员会（Wales Research Ethics Committee 3）的伦理批准（参考文献 23/WA/0297）。我们将在公开发行的同行评审期刊上发表这项研究的结果。
{"title":"Does Intermittent Nutrition Enterally Normalise hormonal and metabolic responses to feeding in critically ill adults? A protocol for the DINE-Normal proof-of-concept randomised parallel group study.","authors":"Clodagh E Beattie, Matt Thomas, Borislava Borislavova, Harry A Smith, Michael Ambler, Paul White, Kati Hayes, Danielle Milne, Aravind V Ramesh, Javier T Gonzalez, James A Betts, Anthony E Pickering","doi":"10.1101/2024.03.14.24303591","DOIUrl":"https://doi.org/10.1101/2024.03.14.24303591","url":null,"abstract":"Introduction:\u0000Over half of patients who spend >48 hours in the intensive care unit (ICU) are fed via a nasogastric (NG) tube. Current guidance recommends continuous delivery of feed throughout the day and night. Emerging evidence from healthy human studies shows that NG feeding in an intermittent pattern (rather than continuous) promotes phasic hormonal, digestive and metabolic responses that are important for effective nutrition. It is not yet known whether this will translate to the critically ill population. Here we present the protocol for a proof-of-concept study comparing diurnal intermittent versus continuous feeding for patients in the intensive care unit. Methods and Analysis:\u0000The study is a single-centre, prospective, randomised, open-label trial comparing intermittent enteral nutrition with the current standard practice of continuous enteral feeding. It aims to recruit participants (n=30) needing enteral nutrition via an NG tube for >24 hours who will be randomised to a diurnal intermittent or a continuous feeding regime with equivalent nutritional value. The primary outcome is peak plasma insulin / c-peptide within 3 hours of delivering the morning bolus feed on the second study day, compared to that seen in the continuous feed delivery group at the same timepoint. Secondary outcomes include feasibility, tolerability, efficacy and metabolic / hormonal profiles. Ethics and Dissemination:\u0000This trial has been registered prospectively with the Clinical Trials Registry (clinicaltrials.gov - NCT06115044). We obtained ethical approval from the Wales Research Ethics Committee 3 prior to data collection (reference 23/WA/0297). We will publish the results of this study in an open-access peer-reviewed journal.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140155660","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}
Pub Date : 2024-03-15DOI: 10.1101/2024.03.13.24304233
Elie Sarraf, Alireza Vafaei Sadr, Vida Abedi, Anthony Bonavia
Background: The Sequential Organ Failure Assessment (SOFA) score is an established tool for monitoring organ failure and defining sepsis. However, its predictive power for sepsis mortality may not account for the full spectrum of influential factors. Recent literature highlights the potential impact of socioeconomic and demographic factors on sepsis outcomes. Objective: This study assessed the prognostic value of SOFA scores relative to demographic and social health determinants in predicting sepsis mortality, and evaluated whether a combined model enhances predictive accuracy. Methods: We utilized the Medical Information Mart for Intensive Care (MIMIC)-IV database for retrospective data and the Penn State Health (PSH) cohort for prospective external validation. SOFA scores, social/demographic data, and the Charlson Comorbidity Index were used to train a Random Forest model using the MIMIC-IV dataset, and then to externally validate it using the PSH dataset. Findings: Of 32,970 sepsis patients in the MIMIC-IV dataset, 6,824 (20.7%) died within 30 days. The model incorporating demographic, socioeconomic, and comorbidity data with SOFA scores showed improved predictive accuracy over SOFA parameters alone. Day 2 SOFA components were highly predictive, with additional factors like age, weight, and comorbidity enhancing prognostic precision. External validation demonstrated consistency in the model's performance, with delta SOFA between days 1 and 3 emerging as a strong mortality predictor. Conclusion: Integrating patient-specific information with clinical measures significantly enhances the predictive accuracy for sepsis mortality. Our findings suggest the need for a multidimensional prognostic framework, considering both clinical and non-clinical patient information for a more accurate sepsis outcome prediction.
{"title":"Integrating Social Determinants of Health with SOFA Scoring to Enhance Mortality Prediction in Septic Patients: A Multidimensional Prognostic Model","authors":"Elie Sarraf, Alireza Vafaei Sadr, Vida Abedi, Anthony Bonavia","doi":"10.1101/2024.03.13.24304233","DOIUrl":"https://doi.org/10.1101/2024.03.13.24304233","url":null,"abstract":"Background: The Sequential Organ Failure Assessment (SOFA) score is an established tool for monitoring organ failure and defining sepsis. However, its predictive power for sepsis mortality may not account for the full spectrum of influential factors. Recent literature highlights the potential impact of socioeconomic and demographic factors on sepsis outcomes. Objective: This study assessed the prognostic value of SOFA scores relative to demographic and social health determinants in predicting sepsis mortality, and evaluated whether a combined model enhances predictive accuracy. Methods: We utilized the Medical Information Mart for Intensive Care (MIMIC)-IV database for retrospective data and the Penn State Health (PSH) cohort for prospective external validation. SOFA scores, social/demographic data, and the Charlson Comorbidity Index were used to train a Random Forest model using the MIMIC-IV dataset, and then to externally validate it using the PSH dataset. Findings: Of 32,970 sepsis patients in the MIMIC-IV dataset, 6,824 (20.7%) died within 30 days. The model incorporating demographic, socioeconomic, and comorbidity data with SOFA scores showed improved predictive accuracy over SOFA parameters alone. Day 2 SOFA components were highly predictive, with additional factors like age, weight, and comorbidity enhancing prognostic precision. External validation demonstrated consistency in the model's performance, with delta SOFA between days 1 and 3 emerging as a strong mortality predictor. Conclusion: Integrating patient-specific information with clinical measures significantly enhances the predictive accuracy for sepsis mortality. Our findings suggest the need for a multidimensional prognostic framework, considering both clinical and non-clinical patient information for a more accurate sepsis outcome prediction.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140155807","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}
Pub Date : 2024-03-13DOI: 10.1101/2024.03.11.24304075
Nicolas de Prost, Etienne Audureau, Antoine Guillon, Lynda Handala, Sebastien Preau, Aurelie Guigon, Fabrice Uhel, Quentin Le Hingrat, Flora Delamaire, Claire Grolhier, Fabienne Tamion, Alice Moisan, Cedric Darreau, Jean Thomin, Damien Contou, Amandine Henry, Thomas Daix, Sebastien Hantz, Clement Saccheri, Valerie Giordanengo, Tai Pham, Amal Chaghouri, Pierre Bay, JeanMichel Pawlotsky, Slim Fourati
A notable increase in severe cases of COVID-19, with significant hospitalizations due to the emergence and spread of JN.1 was observed worldwide in late 2023 and early 2024. During the study period (November 2022-January 2024), 56 JN.1- and 126 XBB-infected patients were prospectively enrolled in 40 French intensive care units. JN.1-infected patients were more likely to be obese (35.7% vs 20.8%; p=0.033) and less frequently immunosuppressed than others (20.4% vs 41.4%; p=0.010). JN.1-infected patients required invasive mechanical ventilation support in 29.1%, 87.5% of them received dexamethasone, 14.5% tocilizumab and none received monoclonal antibodies. Day-28 mortality of JN.1-infected patients was 14.6%.
{"title":"Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron variant JN.1 in critically ill COVID-19 patients: a prospective, multicenter cohort study","authors":"Nicolas de Prost, Etienne Audureau, Antoine Guillon, Lynda Handala, Sebastien Preau, Aurelie Guigon, Fabrice Uhel, Quentin Le Hingrat, Flora Delamaire, Claire Grolhier, Fabienne Tamion, Alice Moisan, Cedric Darreau, Jean Thomin, Damien Contou, Amandine Henry, Thomas Daix, Sebastien Hantz, Clement Saccheri, Valerie Giordanengo, Tai Pham, Amal Chaghouri, Pierre Bay, JeanMichel Pawlotsky, Slim Fourati","doi":"10.1101/2024.03.11.24304075","DOIUrl":"https://doi.org/10.1101/2024.03.11.24304075","url":null,"abstract":"A notable increase in severe cases of COVID-19, with significant hospitalizations due to the emergence and spread of JN.1 was observed worldwide in late 2023 and early 2024. During the study period (November 2022-January 2024), 56 JN.1- and 126 XBB-infected patients were prospectively enrolled in 40 French intensive care units. JN.1-infected patients were more likely to be obese (35.7% vs 20.8%; p=0.033) and less frequently immunosuppressed than others (20.4% vs 41.4%; p=0.010). JN.1-infected patients required invasive mechanical ventilation support in 29.1%, 87.5% of them received dexamethasone, 14.5% tocilizumab and none received monoclonal antibodies. Day-28 mortality of JN.1-infected patients was 14.6%.","PeriodicalId":501249,"journal":{"name":"medRxiv - Intensive Care and Critical Care Medicine","volume":"113 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140126757","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}
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