Pub Date : 2025-07-01DOI: 10.1016/j.jointm.2024.12.006
Christine Chow , Rasheed Durowoju , Carlos Alviar , Gregory W Barsness , Howard A Cooper , Lori B Daniels , Xuan Ding , Shahab Ghafghazi , Umesh Gidwani , Michael Goldfarb , Dustin Hillerson , Jason N Katz , Paul Marano , Jeong-Gun Park , Matthew Pierce , Scott W Rose , Robert O Roswell , Sean van Diepen , Anjali Wagle , Erin A Bohula , Younghoon Kwon
Background
Anemia is common in critically ill patients and is associated with poor outcomes. We investigated the prevalence of anemia and its association with in-hospital outcomes among patients admitted to cardiac intensive care units (CICUs) and subgroups within this population.
Methods
The Critical Care Cardiology Trials Network (CCCTN) is a multicenter network of tertiary CICUs in North America. CICU admissions with available baseline hemoglobin (Hgb) between 2017 and 2023 were included in this analysis. Patients were stratified by Hgb levels (Hgb <8 g/dL, 8 g/dL ≤ Hgb <10 g/dL, 10 g/dL ≤ Hgb <12 g/dL, 12 g/dL ≤ Hgb <14 g/dL, and ≥14 g/dL). The ≥14 g/dL group was used for reference. The association of Hgb level and in-hospital mortality was examined by multivariable logistic regression.
Results
Among 28,585 patient admissions (median age 67 years, 36.7 % female), the median Hgb was 12.1 g/dL (interquartile range: 10.1–13.9), with 48.3 % of patients who meet criteria for anemia (Hgb <12 g/dL). The adjusted relative odds of in-hospital mortality was highest for patients with Hgb <8 g/dL (1.60, 95 % confidence interval [CI]: 1.35 to 1.89, P < 0.0001), followed by patients with 8 g/dL≤ Hgb <10 g/dL (adjusted relative odds =1.51, 95 % CI: 1.32 to 1.73, P < 0.0001), and patients with Hgb 10 g/dL≤ Hgb<12 g/dL (adjusted relative odds=1.24, 95 % CI: 1.09 to 1.41, P=0.0012). This association was present among those with non-acute coronary syndrome (ACS) cardiogenic shock (n=4255) and those with non-cardiogenic shock ACS (n=7194).
Conclusions
Anemia was present in nearly half of patients admitted to CICUs. Lower admission Hgb is independently associated with higher in-hospital mortality in a graded relationship among patients with cardiac critical illness.
{"title":"Anemia as a potent marker of in-hospital mortality in patients admitted to the cardiac intensive care unit: Data from the Critical Care Cardiology Trials Network (CCCTN) Registry","authors":"Christine Chow , Rasheed Durowoju , Carlos Alviar , Gregory W Barsness , Howard A Cooper , Lori B Daniels , Xuan Ding , Shahab Ghafghazi , Umesh Gidwani , Michael Goldfarb , Dustin Hillerson , Jason N Katz , Paul Marano , Jeong-Gun Park , Matthew Pierce , Scott W Rose , Robert O Roswell , Sean van Diepen , Anjali Wagle , Erin A Bohula , Younghoon Kwon","doi":"10.1016/j.jointm.2024.12.006","DOIUrl":"10.1016/j.jointm.2024.12.006","url":null,"abstract":"<div><h3>Background</h3><div>Anemia is common in critically ill patients and is associated with poor outcomes. We investigated the prevalence of anemia and its association with in-hospital outcomes among patients admitted to cardiac intensive care units (CICUs) and subgroups within this population.</div></div><div><h3>Methods</h3><div>The Critical Care Cardiology Trials Network (CCCTN) is a multicenter network of tertiary CICUs in North America. CICU admissions with available baseline hemoglobin (Hgb) between 2017 and 2023 were included in this analysis. Patients were stratified by Hgb levels (Hgb <8 g/dL, 8 g/dL ≤ Hgb <10 g/dL, 10 g/dL ≤ Hgb <12 g/dL, 12 g/dL ≤ Hgb <14 g/dL, and ≥14 g/dL). The ≥14 g/dL group was used for reference. The association of Hgb level and in-hospital mortality was examined by multivariable logistic regression.</div></div><div><h3>Results</h3><div>Among 28,585 patient admissions (median age 67 years, 36.7 % female), the median Hgb was 12.1 g/dL (interquartile range: 10.1–13.9), with 48.3 % of patients who meet criteria for anemia (Hgb <12 g/dL). The adjusted relative odds of in-hospital mortality was highest for patients with Hgb <8 g/dL (1.60, 95 % confidence interval [CI]: 1.35 to 1.89, <em>P</em> < 0.0001), followed by patients with 8 g/dL≤ Hgb <10 g/dL (adjusted relative odds =1.51, 95 % CI: 1.32 to 1.73, <em>P</em> < 0.0001), and patients with Hgb 10 g/dL≤ Hgb<12 g/dL (adjusted relative odds=1.24, 95 % CI: 1.09 to 1.41, <em>P</em>=0.0012). This association was present among those with non-acute coronary syndrome (ACS) cardiogenic shock (<em>n</em>=4255) and those with non-cardiogenic shock ACS (<em>n</em>=7194).</div></div><div><h3>Conclusions</h3><div>Anemia was present in nearly half of patients admitted to CICUs. Lower admission Hgb is independently associated with higher in-hospital mortality in a graded relationship among patients with cardiac critical illness.</div></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 3","pages":"Pages 262-268"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522361","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 : 2025-07-01DOI: 10.1016/j.jointm.2025.03.002
Yingyi Yang , Rui Kang , Huiting Zhou , Daolin Tang
{"title":"The glyoxalase system: A new target for inflammatory diseases","authors":"Yingyi Yang , Rui Kang , Huiting Zhou , Daolin Tang","doi":"10.1016/j.jointm.2025.03.002","DOIUrl":"10.1016/j.jointm.2025.03.002","url":null,"abstract":"","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 3","pages":"Pages 216-218"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522611","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 : 2025-07-01DOI: 10.1016/j.jointm.2024.12.007
Vincent Labbé , Stephane Ederhy , David Legouis , Jérémie Joffre , Keyvan Razazi , Oumar Sy , Frank Chemouni , Armand Mekontso Dessap , Muriel Fartoukh , Ariel Cohen , FAST Study Group
{"title":"CHA2DS2-VASc scores to predict left atrial/left atrial appendage abnormalities in patients with sepsis-induced atrial fibrillation: A preliminary investigation","authors":"Vincent Labbé , Stephane Ederhy , David Legouis , Jérémie Joffre , Keyvan Razazi , Oumar Sy , Frank Chemouni , Armand Mekontso Dessap , Muriel Fartoukh , Ariel Cohen , FAST Study Group","doi":"10.1016/j.jointm.2024.12.007","DOIUrl":"10.1016/j.jointm.2024.12.007","url":null,"abstract":"","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 3","pages":"Pages 288-291"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522364","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 : 2025-02-08DOI: 10.1016/j.jointm.2024.12.008
Jinyu Peng , Yun Li , Chao Liu , Zhi Mao , Hongjun Kang , Feihu Zhou
Background
Multiple organ dysfunction syndrome (MODS) is a critical complication in trauma-induced sepsis patients and is associated with a high mortality rate. This study aimed to develop and validate predictive models for MODS in this patient population using a nomogram and machine learning approaches.
Methods
This retrospective cohort study utilized data from the Medical Information Mart for Intensive Care-IV 2.2 database, focusing on trauma patients diagnosed with sepsis within the first day of intensive care unit (ICU) admission. Predictive variables were extracted from the initial 24 h of ICU data. The dataset (2008–2019) was divided into a training set (2008–2016) and a temporal validation set (2017–2019). Feature selection was conducted using the Boruta algorithm. Predictive models were developed and validated using a nomogram and various machine learning techniques. Model performance was evaluated based on discrimination, calibration, and decision curve analysis.
Results
Among 1295 trauma patients with sepsis, 349 (26.95%) developed MODS. The 28-day mortality rates were 11.21% for non-MODS patients and 23.82% for MODS patients. Key predictors of MODS included the simplified acute physiology score II score, use of mechanical ventilation, and vasopressor administration. In temporal validation, all models significantly outperformed traditional scoring systems (all P <0.05). The nomogram achieved an area under the curve (AUC) of 0.757 (95% confidence interval [CI]: 0.700 to 0.814), while the random forest model demonstrated the highest performance with an AUC of 0.769 (95% CI: 0.712 to 0.826). Calibration plots showed excellent agreement between predicted and observed probabilities, and decision curve analysis indicated a consistently higher net benefit for the newly developed models.
Conclusion
The nomogram and machine learning models provide enhanced predictive accuracy for MODS in trauma-induced sepsis patients compared to traditional scoring systems. These tools, accessible via web-based applications, have the potential to improve early risk stratification and guide clinical decision-making, ultimately enhancing outcomes for trauma patients. Further external validation is recommended to confirm their generalizability.
背景：多器官功能障碍综合征（MODS）是创伤性脓毒症患者的重要并发症，死亡率高。本研究旨在利用nomogram和机器学习方法开发并验证该患者群体MODS的预测模型。方法本回顾性队列研究利用重症监护医学信息市场- iv - 2.2数据库的数据，重点研究重症监护病房（ICU）入院第一天诊断为败血症的创伤患者。从ICU的最初24小时数据中提取预测变量。数据集（2008-2019）分为训练集（2008-2016）和时间验证集（2017-2019）。采用Boruta算法进行特征选择。使用nomogram和各种机器学习技术开发并验证了预测模型。基于判别、校准和决策曲线分析对模型性能进行评估。结果1295例创伤脓毒症患者中，349例（26.95%）发生MODS。非MODS患者28天死亡率为11.21%，MODS患者为23.82%。MODS的主要预测因素包括简化急性生理评分、机械通气的使用和血管加压药的使用。在时间验证中，所有模型都显著优于传统评分系统（均P <；0.05）。模态图的曲线下面积（AUC）为0.757(95%可信区间[CI]: 0.700至0.814)，而随机森林模型的AUC为0.769 (95% CI: 0.712至0.826)，表现出最高的性能。校正图显示预测概率和观测概率非常吻合，决策曲线分析表明新开发模型的净效益始终较高。结论与传统评分系统相比，nomogram和machine learning模型可提高创伤性败血症患者MODS的预测准确性。这些工具可通过基于网络的应用程序访问，具有改善早期风险分层和指导临床决策的潜力，最终提高创伤患者的预后。建议进一步进行外部验证以确认其通用性。
{"title":"Predicting multiple organ dysfunction syndrome in trauma-induced sepsis: Nomogram and machine learning approaches","authors":"Jinyu Peng , Yun Li , Chao Liu , Zhi Mao , Hongjun Kang , Feihu Zhou","doi":"10.1016/j.jointm.2024.12.008","DOIUrl":"10.1016/j.jointm.2024.12.008","url":null,"abstract":"<div><h3>Background</h3><div>Multiple organ dysfunction syndrome (MODS) is a critical complication in trauma-induced sepsis patients and is associated with a high mortality rate. This study aimed to develop and validate predictive models for MODS in this patient population using a nomogram and machine learning approaches.</div></div><div><h3>Methods</h3><div>This retrospective cohort study utilized data from the Medical Information Mart for Intensive Care-IV 2.2 database, focusing on trauma patients diagnosed with sepsis within the first day of intensive care unit (ICU) admission. Predictive variables were extracted from the initial 24 h of ICU data. The dataset (2008–2019) was divided into a training set (2008–2016) and a temporal validation set (2017–2019). Feature selection was conducted using the Boruta algorithm. Predictive models were developed and validated using a nomogram and various machine learning techniques. Model performance was evaluated based on discrimination, calibration, and decision curve analysis.</div></div><div><h3>Results</h3><div>Among 1295 trauma patients with sepsis, 349 (26.95%) developed MODS. The 28-day mortality rates were 11.21% for non-MODS patients and 23.82% for MODS patients. Key predictors of MODS included the simplified acute physiology score II score, use of mechanical ventilation, and vasopressor administration. In temporal validation, all models significantly outperformed traditional scoring systems (all <em>P</em> <0.05). The nomogram achieved an area under the curve (AUC) of 0.757 (95% confidence interval [CI]: 0.700 to 0.814), while the random forest model demonstrated the highest performance with an AUC of 0.769 (95% CI: 0.712 to 0.826). Calibration plots showed excellent agreement between predicted and observed probabilities, and decision curve analysis indicated a consistently higher net benefit for the newly developed models.</div></div><div><h3>Conclusion</h3><div>The nomogram and machine learning models provide enhanced predictive accuracy for MODS in trauma-induced sepsis patients compared to traditional scoring systems. These tools, accessible via web-based applications, have the potential to improve early risk stratification and guide clinical decision-making, ultimately enhancing outcomes for trauma patients. Further external validation is recommended to confirm their generalizability.</div></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 2","pages":"Pages 193-201"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jointm.2024.07.001
Laurent Camous , Nicolas Paulo , Frederic Martino , Sylvaine Bastian , Marc Valette , Jean-David Pommier
{"title":"Causes of fulminant tropical probable myocarditis: A retrospective cohort study in the French West Indies","authors":"Laurent Camous , Nicolas Paulo , Frederic Martino , Sylvaine Bastian , Marc Valette , Jean-David Pommier","doi":"10.1016/j.jointm.2024.07.001","DOIUrl":"10.1016/j.jointm.2024.07.001","url":null,"abstract":"","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 1","pages":"Pages 111-112"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11763240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143054388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jointm.2024.04.003
Lingjuan Liu , Dingji Hu , Tong Hao , Shanshan Chen , Lei Chen , Yike Zhu , Chenhui Jin , Jing Wu , Haoya Fu , Haibo Qiu , Yi Yang , Songqiao Liu
Background
Extracorporeal membrane oxygenation (ECMO) has been proven to be a support method and technology for patients with cardiopulmonary failure. However, the transport of patients under ECMO support is challenging given the high-risk technical maneuvers and patient-care concerns involved. Herein, we examined the safety of ECMO during the transport of critically ill patients and its impact on mortality rates, to provide more secure and effective transport strategies in clinical practice.
Method
To assess the safety of ECMO patient transport, this study conducted a retrospective analysis on critically ill adults who required ECMO support and transport at the intensive care unit (ICU) center between 2017 and 2023. The study utilized standard ECMO transport protocols and conducted a comprehensive statistical analysis of the collected clinical data and transport processes. The 28-day survival rate for ECMO patients was determined using Kaplan–Meier analysis, while logistic regression identified prognostic factors.
Result
Out of 303 patients supported with ECMO, 111 (36.6%) were transported. 69.4% of the transport group were male, mean age was (42.0±17.0) years, mean body mass index was (24.4±4.6) kg/m2, and veno-arterial-ECMO accounted for 52.5%. The median transportation distance was 190 (interquartile range [IQR]: 70–260) km, and the longest distance was 8100 km. The median transit time was 180 (IQR: 100–260) min, and the maximum duration was 1720 min. No severe adverse events including death or mechanical failure occurred during transportation. The 28-day survival rate was 64.7% (n=196) and ICU survival rate was 56.1% (n=170) for the entire cohort; whereas, the 28-day survival rate was 72.1% (n=80) and ICU survival rate was 66.7% (n=74) in the transport group. A non-significant difference in 28-day survival was observed between the two groups after propensity score matching (P=0.56). Additionally, we found that acute physiology and chronic health evaluation II score (odds ratio [OR]=1.06, P <0.01), lactate levels (>5 mmol/L, OR=2.80, P=0.01), and renal replacement therapy initiation (OR=3.03, P <0.01) were associated with increased mortality risk.
Conclusion
Transporting patients on ECMO between medical facilities is a safe procedure that does not increase patient mortality rates, provided it is orchestrated and executed by proficient transport teams. The prognostic outcome for these patients is predominantly influenced by their pre-existing medical conditions or by complications that may develop during the course of ECMO therapy. These results form the basis for the creation of specialized ECMO network hubs within healthcare regions.
{"title":"Outcomes and risk factors of transported patients with extracorporeal membrane oxygenation: An ECMO center experience","authors":"Lingjuan Liu , Dingji Hu , Tong Hao , Shanshan Chen , Lei Chen , Yike Zhu , Chenhui Jin , Jing Wu , Haoya Fu , Haibo Qiu , Yi Yang , Songqiao Liu","doi":"10.1016/j.jointm.2024.04.003","DOIUrl":"10.1016/j.jointm.2024.04.003","url":null,"abstract":"<div><h3>Background</h3><div>Extracorporeal membrane oxygenation (ECMO) has been proven to be a support method and technology for patients with cardiopulmonary failure. However, the transport of patients under ECMO support is challenging given the high-risk technical maneuvers and patient-care concerns involved. Herein, we examined the safety of ECMO during the transport of critically ill patients and its impact on mortality rates, to provide more secure and effective transport strategies in clinical practice.</div></div><div><h3>Method</h3><div>To assess the safety of ECMO patient transport, this study conducted a retrospective analysis on critically ill adults who required ECMO support and transport at the intensive care unit (ICU) center between 2017 and 2023. The study utilized standard ECMO transport protocols and conducted a comprehensive statistical analysis of the collected clinical data and transport processes. The 28-day survival rate for ECMO patients was determined using Kaplan–Meier analysis, while logistic regression identified prognostic factors.</div></div><div><h3>Result</h3><div>Out of 303 patients supported with ECMO, 111 (36.6%) were transported. 69.4% of the transport group were male, mean age was (42.0±17.0) years, mean body mass index was (24.4±4.6) kg/m<sup>2</sup>, and veno-arterial-ECMO accounted for 52.5%. The median transportation distance was 190 (interquartile range [IQR]: 70–260) km, and the longest distance was 8100 km. The median transit time was 180 (IQR: 100–260) min, and the maximum duration was 1720 min. No severe adverse events including death or mechanical failure occurred during transportation. The 28-day survival rate was 64.7% (<em>n</em>=196) and ICU survival rate was 56.1% (<em>n</em>=170) for the entire cohort; whereas, the 28-day survival rate was 72.1% (<em>n</em>=80) and ICU survival rate was 66.7% (<em>n</em>=74) in the transport group. A non-significant difference in 28-day survival was observed between the two groups after propensity score matching (<em>P</em>=0.56). Additionally, we found that acute physiology and chronic health evaluation II score (odds ratio [OR]=1.06, <em>P</em> <0.01), lactate levels (>5 mmol/L, OR=2.80, <em>P</em>=0.01), and renal replacement therapy initiation (OR=3.03, <em>P</em> <0.01) were associated with increased mortality risk.</div></div><div><h3>Conclusion</h3><div>Transporting patients on ECMO between medical facilities is a safe procedure that does not increase patient mortality rates, provided it is orchestrated and executed by proficient transport teams. The prognostic outcome for these patients is predominantly influenced by their pre-existing medical conditions or by complications that may develop during the course of ECMO therapy. These results form the basis for the creation of specialized ECMO network hubs within healthcare regions.</div></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 1","pages":"Pages 35-42"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141396556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jointm.2024.06.002
Yan Xia , Qiancheng Xu , Zhiyuan Guo , Huijuan Zhang , Yingya Cao , Yupeng Qi , Qun Chen , Weihua Lu
Background
The purpose is to formulate a modified screening protocol for acute respiratory distress syndrome (ARDS) in patients with respiratory support based on saturation of pulse oximetry (SpO2) and inspired oxygen concentration (FiO2).
Methods
This prospective observational study was conducted from August to October 2020 at the Department of Critical Care Medicine of Yijishan Hospital Affiliated with Wannan Medical College. All patients admitted during the study period and required arterial blood gas analysis and electrocardiogram monitoring were included in this study. Patients with contraindications to arterial puncture, methemoglobinemia, carbon monoxide poisoning, and other factors that could affect data collection were excluded. The demographic and clinical data, immediate percutaneous SpO2, FiO2, arterial oxygen partial pressure (PaO2), and respiratory rate were recorded; and the SpO2/FiO2 ratio (SFR) and PaO2/FiO2 ratio (PFR) values were calculated according to the above information. The patients were divided into two cohorts by random number table: the establishment cohort and the verification cohort. In the established part, data were divided into group H and group N according to whether SpO2 >97 %. For group H (SpO2 ≤97 %), the regression equation was established between SFR and PFR. For group N (SpO2 >97 %), the correlation between each observation data and PFR was analyzed. Then, a new diagnostic process was established, and the reliability was verified with the Berlin definition set as the gold standard for diagnosis and classification.
Results
There were 341 patients were included. Among them, 161 patients were used to establish the model, and 180 patients were used to verify the validity of the model. In this new diagnosis progress, when SpO2 ≤97 %, if SFR ≤352, ARDS may exist; when SpO2 >97 %, if FiO2min >39 %, there may be ARDS. The sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of the new diagnosis progress for ARDS were 91.1 %, 76.7 %, 89.6 %, 79.6 %, and 83.9 %, respectively.
Conclusion
The SpO2/FiO2 ratio demonstrates notable sensitivity and specificity in diagnosing ARDS, presenting as a credible alternative to PFR.
Trail Registration Chinese Clinical Trial Registry Identifier: ChiCTR2000029217
{"title":"A modified screening protocol for ARDS in patients with respiratory support based on SpO2 and FiO2: A single-center prospective, observational study","authors":"Yan Xia , Qiancheng Xu , Zhiyuan Guo , Huijuan Zhang , Yingya Cao , Yupeng Qi , Qun Chen , Weihua Lu","doi":"10.1016/j.jointm.2024.06.002","DOIUrl":"10.1016/j.jointm.2024.06.002","url":null,"abstract":"<div><h3>Background</h3><div>The purpose is to formulate a modified screening protocol for acute respiratory distress syndrome (ARDS) in patients with respiratory support based on saturation of pulse oximetry (SpO<sub>2</sub>) and inspired oxygen concentration (FiO<sub>2</sub>).</div></div><div><h3>Methods</h3><div>This prospective observational study was conducted from August to October 2020 at the Department of Critical Care Medicine of Yijishan Hospital Affiliated with Wannan Medical College. All patients admitted during the study period and required arterial blood gas analysis and electrocardiogram monitoring were included in this study. Patients with contraindications to arterial puncture, methemoglobinemia, carbon monoxide poisoning, and other factors that could affect data collection were excluded. The demographic and clinical data, immediate percutaneous SpO<sub>2</sub>, FiO<sub>2</sub>, arterial oxygen partial pressure (PaO<sub>2</sub>), and respiratory rate were recorded; and the SpO<sub>2</sub>/FiO<sub>2</sub> ratio (SFR) and PaO<sub>2</sub>/FiO<sub>2</sub> ratio (PFR) values were calculated according to the above information. The patients were divided into two cohorts by random number table: the establishment cohort and the verification cohort. In the established part, data were divided into group H and group N according to whether SpO<sub>2</sub> >97 %. For group H (SpO<sub>2</sub> ≤97 %), the regression equation was established between SFR and PFR. For group N (SpO<sub>2</sub> >97 %), the correlation between each observation data and PFR was analyzed. Then, a new diagnostic process was established, and the reliability was verified with the Berlin definition set as the gold standard for diagnosis and classification.</div></div><div><h3>Results</h3><div>There were 341 patients were included. Among them, 161 patients were used to establish the model, and 180 patients were used to verify the validity of the model. In this new diagnosis progress, when SpO<sub>2</sub> ≤97 %, if SFR ≤352, ARDS may exist; when SpO<sub>2</sub> >97 %, if FiO<sub>2min</sub> >39 %, there may be ARDS. The sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of the new diagnosis progress for ARDS were 91.1 %, 76.7 %, 89.6 %, 79.6 %, and 83.9 %, respectively.</div></div><div><h3>Conclusion</h3><div>The SpO<sub>2</sub>/FiO<sub>2</sub> ratio demonstrates notable sensitivity and specificity in diagnosing ARDS, presenting as a credible alternative to PFR.</div><div><strong>Trail Registration</strong> Chinese Clinical Trial Registry Identifier: ChiCTR2000029217</div></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 1","pages":"Pages 51-57"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11763540/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143054384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jointm.2024.07.002
Daniel De Backer , Dechang Chen
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Pub Date : 2025-01-01DOI: 10.1016/j.jointm.2024.04.001
David Furfaro , Xiaoyu Che , Wenhao Gou , Matthew J. Cummings , Nischay Mishra , Daniel Brodie , Thomas Briese , Oliver Fiehn , W. Ian Lipkin , Max R. O'Donnell
{"title":"Metabolomic profiling and prognostication in COVID-19 acute respiratory distress syndrome","authors":"David Furfaro , Xiaoyu Che , Wenhao Gou , Matthew J. Cummings , Nischay Mishra , Daniel Brodie , Thomas Briese , Oliver Fiehn , W. Ian Lipkin , Max R. O'Donnell","doi":"10.1016/j.jointm.2024.04.001","DOIUrl":"10.1016/j.jointm.2024.04.001","url":null,"abstract":"","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 1","pages":"Pages 108-110"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141037971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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