Pub Date : 2024-04-05DOI: 10.1101/2024.04.03.24305306
Qinqin Li, Li Yao, Tingshu Wang, Tingrui Wang, Yan Liu
Introduction With the gradual improvement of medical treatment and nursing, more and more patients are successfully transferred out of the ICU. However, intensive care unit (ICU) survivors often experience long-term physical, cognitive, and psychological problems, and their family members also experience physical and psychological dysfunction, summarized as post-intensive care syndrome (PICS), affecting their health-related quality of life. Post-ICU follow-up can improve post-ICU syndrome in patients and their families, but the optimal mode of post-ICU follow-up remains uncertain. The purpose of this study was to build a follow-up model of ICU patients based on symptom management theory.
{"title":"Construction and empirical of ICU patient follow-up model based on symptom management theory: a quasi-randomized controlled trial study protocol","authors":"Qinqin Li, Li Yao, Tingshu Wang, Tingrui Wang, Yan Liu","doi":"10.1101/2024.04.03.24305306","DOIUrl":"https://doi.org/10.1101/2024.04.03.24305306","url":null,"abstract":"<strong>Introduction</strong> With the gradual improvement of medical treatment and nursing, more and more patients are successfully transferred out of the ICU. However, intensive care unit (ICU) survivors often experience long-term physical, cognitive, and psychological problems, and their family members also experience physical and psychological dysfunction, summarized as post-intensive care syndrome (PICS), affecting their health-related quality of life. Post-ICU follow-up can improve post-ICU syndrome in patients and their families, but the optimal mode of post-ICU follow-up remains uncertain. The purpose of this study was to build a follow-up model of ICU patients based on symptom management theory.","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140601430","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: 10.1101/2024.03.13.24304236
Martin Gerdin Warnberg, Trauma life support training Effectiveness Research Network (TERN) collaborators
Introduction Trauma life support training programmes aim to improve trauma outcomes but there is no evidence from controlled trials to show that they work. We conducted a pilot study to assess the feasibility of conducting a cluster randomised controlled trial comparing the effect of Advanced Trauma Life Support (ATLS) and Primary Trauma Care (PTC) with standard care on patient outcomes. Methods and analysis We piloted a pragmatic three-armed parallel, cluster randomised, controlled trial in tertiary care hospitals across metropolitan areas in India. We included adult trauma patients and residents managing these patients. Two hospitals were randomised to ATLS, two to PTC, and three to standard care. The feasibility outcomes were consent rate, lost to follow up rate, pass rate, missing data rates, and differences in distribution between observed and data extracted from medical records. We conducted community consultations in parallel with the pilot trial. Ethics and dissemination We obtained ethical approval from all participating hospitals. Results Between April 2022 and February 2023 we included 376 patients and 21 residents. The percentage of patients who consented to follow up was 77% and the percentage of residents who consented to training was 100%. The lost to follow up rate was 14%. The pass rate was 100%. The missing data rate ranged from 0 to 98. Data collected through observations were similar to data extracted from medical records, but there was more missing data in the extracted data. Conclusions Conducting a full-scale cluster randomised controlled trial comparing the effects of ATLS, PTC, and standard care on patient outcomes should be feasible after incorporating key lessons from this pilot.
{"title":"Effects of Trauma Life Support Training on Patient Outcomes: A Pilot Cluster Randomised Trial","authors":"Martin Gerdin Warnberg, Trauma life support training Effectiveness Research Network (TERN) collaborators","doi":"10.1101/2024.03.13.24304236","DOIUrl":"https://doi.org/10.1101/2024.03.13.24304236","url":null,"abstract":"Introduction Trauma life support training programmes aim to improve trauma outcomes but there is no evidence from controlled trials to show that they work. We conducted a pilot study to assess the feasibility of conducting a cluster randomised controlled trial comparing the effect of Advanced Trauma Life Support (ATLS) and Primary Trauma Care (PTC) with standard care on patient outcomes. Methods and analysis We piloted a pragmatic three-armed parallel, cluster randomised, controlled trial in tertiary care hospitals across metropolitan areas in India. We included adult trauma patients and residents managing these patients. Two hospitals were randomised to ATLS, two to PTC, and three to standard care. The feasibility outcomes were consent rate, lost to follow up rate, pass rate, missing data rates, and differences in distribution between observed and data extracted from medical records. We conducted community consultations in parallel with the pilot trial. Ethics and dissemination We obtained ethical approval from all participating hospitals. Results Between April 2022 and February 2023 we included 376 patients and 21 residents. The percentage of patients who consented to follow up was 77% and the percentage of residents who consented to training was 100%. The lost to follow up rate was 14%. The pass rate was 100%. The missing data rate ranged from 0 to 98. Data collected through observations were similar to data extracted from medical records, but there was more missing data in the extracted data. Conclusions Conducting a full-scale cluster randomised controlled trial comparing the effects of ATLS, PTC, and standard care on patient outcomes should be feasible after incorporating key lessons from this pilot.","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140147532","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: 10.1101/2024.03.14.24304309
Chantae Garland, Nhayan Abdulla, Donghyun Lee, Rae Spiwak, Sarvesh Logsetty, Jordan Nantais
Background Alcohol use is a contributing factor in many cases of traumatic injury. There is conflicting evidence on the impact of alcohol use at the time of physical trauma on severity of injury and hospital course. Similarly, the significance of alcohol use disorder on outcomes in hospitalized trauma patients is unclear. This scoping review aims to provide a concise overview of the current literature surrounding peri-trauma alcohol use and alcohol use disorder on injury severity, in-hospital complications, patient outcomes, and long-term health impact of alcohol use in trauma. We will also explore the associated healthcare costs of this patient population. Methods A systematic search of the following databases MEDLINE, EMBASE, and Cochrane Library will be completed to extract all studies that meet our inclusion criteria from January 2000 onwards. Case reports will be excluded. Two reviewers will screen all citations, abstracts, and full text articles. A third reviewer will act as tiebreaker at each stage of the screening process. A narrative synthesis without meta-analysis will be conducted and assessed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Discussion This review will contribute to the literature by providing a concise overview of the current data on the impact of alcohol on outcomes following trauma. We will explore the overall themes in the literature, limitations, and future directions to focus forthcoming research in this patient population.
背景在许多外伤病例中，饮酒是一个诱因。关于身体创伤时饮酒对损伤严重程度和住院过程的影响，目前还没有相互矛盾的证据。同样，酒精使用障碍对住院创伤患者预后的影响也不明确。本范围综述旨在简要概述目前有关创伤期饮酒和饮酒障碍对损伤严重程度、院内并发症、患者预后以及创伤期饮酒对健康的长期影响的文献。我们还将探讨这一患者群体的相关医疗成本。方法将对以下数据库进行系统检索：MEDLINE、EMBASE 和 Cochrane Library，以提取 2000 年 1 月以来符合我们纳入标准的所有研究。病例报告将被排除在外。两名审稿人将筛选所有引文、摘要和全文。第三位审稿人将在筛选过程的每个阶段担任裁定人。我们将根据 "系统综述和Meta分析的首选报告项目"（Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews，PRISMA-ScR）指南进行不含荟萃分析的叙述性综述和评估。我们将探讨文献中的总体主题、局限性以及未来的研究方向，以关注这一患者群体。
{"title":"The Impact of Alcohol Misuse in Trauma Patients: A Scoping Review Protocol","authors":"Chantae Garland, Nhayan Abdulla, Donghyun Lee, Rae Spiwak, Sarvesh Logsetty, Jordan Nantais","doi":"10.1101/2024.03.14.24304309","DOIUrl":"https://doi.org/10.1101/2024.03.14.24304309","url":null,"abstract":"Background\u0000Alcohol use is a contributing factor in many cases of traumatic injury. There is conflicting evidence on the impact of alcohol use at the time of physical trauma on severity of injury and hospital course. Similarly, the significance of alcohol use disorder on outcomes in hospitalized trauma patients is unclear. This scoping review aims to provide a concise overview of the current literature surrounding peri-trauma alcohol use and alcohol use disorder on injury severity, in-hospital complications, patient outcomes, and long-term health impact of alcohol use in trauma. We will also explore the associated healthcare costs of this patient population.\u0000Methods\u0000A systematic search of the following databases MEDLINE, EMBASE, and Cochrane Library will be completed to extract all studies that meet our inclusion criteria from January 2000 onwards. Case reports will be excluded. Two reviewers will screen all citations, abstracts, and full text articles. A third reviewer will act as tiebreaker at each stage of the screening process. A narrative synthesis without meta-analysis will be conducted and assessed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines.\u0000Discussion\u0000This review will contribute to the literature by providing a concise overview of the current data on the impact of alcohol on outcomes following trauma. We will explore the overall themes in the literature, limitations, and future directions to focus forthcoming research in this patient population.","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140147614","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: 10.1101/2024.03.14.24304275
Carl Otto Schell, Raphael Kayambankadzanja, Abigail Beane, Andreas Wellhagen, Chamira Kodippily, Anna Hvarfner, Grace Banda-Katha, Nalayini Jegathesan, Christoffer Hintze, Wageesha Wijesiriwardana, Martin Gerdin Warnberg, Mtisunge Kachingwe, Petronella Bjurling-Sjoberg, Annie Kalibwe Mkandawire, Hampus Sjostedt, Surenthirakumaran Rajendra, Cecilia Stalsby Lundborg, Miklos Lipcsey, Lisa Kurland, Rashan Haniffa, Tim Baker
Key PointsQuestion: What is the burden of critical illness in hospitals in different global settings, and where are critically ill patients being cared for? Findings: Among 3652 hospitalized patients in countries of different socio-economic levels (Malawi, Sri Lanka, and Sweden) we found a point-prevalence of critical illness of 12.0% (95% CI, 11.0-13.1), with a hospital mortality of 18.7% (95% CI, 15.3-22.6). The odds ratio of death of critically ill compared to non-critically ill patients was 7.5 (95% CI, 5.4-10.2). Of the critically ill patients 3.9 % (95% CI, 2.4-6.1) were cared for in Intensive Care Units (ICUs). Meaning: Critical illness is common in hospitals and has a high mortality. Ensuring that feasible critical care interventions are implemented throughout hospitals including in general wards where more than nine in ten critically ill patients are cared for, has potential to improve outcomes across all medical specialties. AbstractImportance: Large unmet needs of critical care have been identified globally, but evidence to guide policy priorities is scarce. Available studies into the burden of critical illness have important limitations. Objective: To assess the adult burden of critical illness in hospitals across global settings. Design, Setting, and Participants: This was a prospective, observational, international, hospital-based, point-prevalence and cohort study in Malawi, Sri Lanka, and Sweden. On specific days, all adult in-patients in the eight study hospitals were examined for the presence of critical illness and followed up for hospital mortality. Exposure: Patients with one or more severely deranged vital sign were classified as critically ill. Main Outcomes and Measures: The primary study outcomes were the point-prevalence of critical illness and 30-day in-hospital mortality. In addition, we assessed the proportion of critically ill patients who were cared for in Intensive Care Units (ICU)s, and the association between critical illness and 30-day in-hospital mortality. Results: Among 3652 hospitalized patients in countries of different socio-economic levels we found a point-prevalence of critical illness of 12.0% (95% CI, 11.0-13.1), with a hospital mortality of 18.7% (95% CI, 15.3-22.6). The odds ratio of death of critically ill compared to non-critically ill patients was 7.5 (95% CI, 5.4-10.2). Of the critically ill patients 3.9 % (95% CI, 2.4-6.1) were cared for in ICUs. Conclusions and Relevance: The study has revealed a substantial burden of critical illness in hospitals from different global settings. One in eight hospital in-patients were critically ill, 19% of them died in hospital, and 96% of the critically ill patients were cared for outside ICUs. Implementing feasible, low-cost, critical care in general wards
{"title":"The hospital burden of critical illness across global settings: a point-prevalence and cohort study in Malawi, Sri Lanka and Sweden.","authors":"Carl Otto Schell, Raphael Kayambankadzanja, Abigail Beane, Andreas Wellhagen, Chamira Kodippily, Anna Hvarfner, Grace Banda-Katha, Nalayini Jegathesan, Christoffer Hintze, Wageesha Wijesiriwardana, Martin Gerdin Warnberg, Mtisunge Kachingwe, Petronella Bjurling-Sjoberg, Annie Kalibwe Mkandawire, Hampus Sjostedt, Surenthirakumaran Rajendra, Cecilia Stalsby Lundborg, Miklos Lipcsey, Lisa Kurland, Rashan Haniffa, Tim Baker","doi":"10.1101/2024.03.14.24304275","DOIUrl":"https://doi.org/10.1101/2024.03.14.24304275","url":null,"abstract":"<strong>Key Points</strong>\u0000<strong>Question:</strong> What is the burden of critical illness in hospitals in different global settings, and where are critically ill patients being cared for? <strong>Findings:</strong> Among 3652 hospitalized patients in countries of different socio-economic levels (Malawi, Sri Lanka, and Sweden) we found a point-prevalence of critical illness of 12.0% (95% CI, 11.0-13.1), with a hospital mortality of 18.7% (95% CI, 15.3-22.6). The odds ratio of death of critically ill compared to non-critically ill patients was 7.5 (95% CI, 5.4-10.2). Of the critically ill patients 3.9 % (95% CI, 2.4-6.1) were cared for in Intensive Care Units (ICUs). <strong>Meaning:</strong> Critical illness is common in hospitals and has a high mortality. Ensuring that feasible critical care interventions are implemented throughout hospitals including in general wards where more than nine in ten critically ill patients are cared for, has potential to improve outcomes across all medical specialties. <strong>Abstract</strong>\u0000<strong>Importance:</strong> Large unmet needs of critical care have been identified globally, but evidence to guide policy priorities is scarce. Available studies into the burden of critical illness have important limitations. <strong>Objective:</strong> To assess the adult burden of critical illness in hospitals across global settings. <strong>Design, Setting, and Participants:</strong> This was a prospective, observational, international, hospital-based, point-prevalence and cohort study in Malawi, Sri Lanka, and Sweden. On specific days, all adult in-patients in the eight study hospitals were examined for the presence of critical illness and followed up for hospital mortality. <strong>Exposure:</strong> Patients with one or more severely deranged vital sign were classified as critically ill. <strong>Main Outcomes and Measures:</strong> The primary study outcomes were the point-prevalence of critical illness and 30-day in-hospital mortality. In addition, we assessed the proportion of critically ill patients who were cared for in Intensive Care Units (ICU)s, and the association between critical illness and 30-day in-hospital mortality. <strong>Results:</strong> Among 3652 hospitalized patients in countries of different socio-economic levels we found a point-prevalence of critical illness of 12.0% (95% CI, 11.0-13.1), with a hospital mortality of 18.7% (95% CI, 15.3-22.6). The odds ratio of death of critically ill compared to non-critically ill patients was 7.5 (95% CI, 5.4-10.2). Of the critically ill patients 3.9 % (95% CI, 2.4-6.1) were cared for in ICUs. <strong>Conclusions and Relevance:</strong> The study has revealed a substantial burden of critical illness in hospitals from different global settings. One in eight hospital in-patients were critically ill, 19% of them died in hospital, and 96% of the critically ill patients were cared for outside ICUs. Implementing feasible, low-cost, critical care in general wards ","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140147613","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 : 2024-03-08DOI: 10.1101/2024.03.06.24303847
Ayush Doshi, Thomas Hartka
The injury severity classifications generated from the Abbreviated Injury Scale (AIS) provide information that allows for standardized comparisons in the field of trauma injury research. However, the majority of injuries are coded in International Classification of Diseases (ICD) and lack this severity information. A system to predict injury severity classifications from ICD codes would be beneficial as manually coding in AIS can be time-intensive or even impossible for some retrospective cases. It has been previously shown that the encoder-decoder-based neural machine translation (NMT) model is more accurate than a one-to-one mapping of ICD codes to AIS. The objective of this study is to compare the accuracy of two architectures, feedforward neural networks (FFNN) and NMT, in predicting Injury Severity Score (ISS) and ISS ≥16 classification. Both architectures were tested in direct conversion from ICD codes to ISS score and indirect conversion through AIS for a total of four models. Trauma cases from the U.S. National Trauma Data Bank were used to develop and test the four models as the injuries were coded in both ICD and AIS. 2,031,793 trauma cases from 2017-2018 were used to train and validate the models while 1,091,792 cases from 2019 were used to test and compare them. The results showed that indirect conversion through AIS using an NMT was the most accurate in predicting the exact ISS score, followed by direct conversion with FFNN, direct conversion with NMT, and lastly indirect conversion with FFNN, with statistically significant differences in performance on all pairwise comparisons. The rankings were similar when comparing the accuracy of predicting ISS ≥16 classification, however the differences were smaller. The NMT architecture continues to demonstrate notable accuracy in predicting exact ISS scores, but a simpler FFNN approach may be preferred in specific situations, such as if only ISS ≥16 classification is needed or large-scale computational resources are unavailable.
由简易伤害量表（AIS）生成的伤害严重程度分类提供了在创伤伤害研究领域进行标准化比较的信息。然而，大多数伤害都是按照国际疾病分类（ICD）进行编码的，缺乏这种严重程度信息。根据 ICD 编码预测损伤严重程度分类的系统将大有裨益，因为在 AIS 中手动编码可能会耗费大量时间，对于某些回顾性病例来说甚至是不可能的。以前的研究表明，基于编码器-解码器的神经机器翻译（NMT）模型比 ICD 代码与 AIS 的一对一映射更准确。本研究的目的是比较前馈神经网络（FFNN）和 NMT 这两种架构在预测损伤严重程度评分（ISS）和 ISS ≥16 分类方面的准确性。这两种架构都在从 ICD 代码直接转换到 ISS 分数和通过 AIS 间接转换的过程中进行了测试，总共有四个模型。美国国家创伤数据库中的创伤病例被用于开发和测试这四种模型，因为这些创伤病例的编码既有 ICD 编码，也有 AIS 编码。2017-2018年的2,031,793个创伤病例用于训练和验证模型，2019年的1,091,792个病例用于测试和比较模型。结果显示，使用 NMT 通过 AIS 间接转换预测 ISS 精确得分的准确度最高，其次是使用 FFNN 直接转换、使用 NMT 直接转换，最后是使用 FFNN 间接转换，所有成对比较的性能差异均有统计学意义。在比较预测 ISS≥16 分类的准确性时，排名情况类似，但差异较小。NMT 架构在预测准确的 ISS 分数方面继续表现出显著的准确性，但在特定情况下，如仅需要 ISS ≥16 分类或无法获得大规模计算资源时，可能更倾向于使用更简单的 FFNN 方法。
{"title":"Comparison of Deep Learning Approaches for Conversion of International Classification of Diseases Codes to the Abbreviated Injury Scale","authors":"Ayush Doshi, Thomas Hartka","doi":"10.1101/2024.03.06.24303847","DOIUrl":"https://doi.org/10.1101/2024.03.06.24303847","url":null,"abstract":"The injury severity classifications generated from the Abbreviated Injury Scale (AIS) provide information that allows for standardized comparisons in the field of trauma injury research. However, the majority of injuries are coded in International Classification of Diseases (ICD) and lack this severity information. A system to predict injury severity classifications from ICD codes would be beneficial as manually coding in AIS can be time-intensive or even impossible for some retrospective cases. It has been previously shown that the encoder-decoder-based neural machine translation (NMT) model is more accurate than a one-to-one mapping of ICD codes to AIS. The objective of this study is to compare the accuracy of two architectures, feedforward neural networks (FFNN) and NMT, in predicting Injury Severity Score (ISS) and ISS ≥16 classification. Both architectures were tested in direct conversion from ICD codes to ISS score and indirect conversion through AIS for a total of four models. Trauma cases from the U.S. National Trauma Data Bank were used to develop and test the four models as the injuries were coded in both ICD and AIS. 2,031,793 trauma cases from 2017-2018 were used to train and validate the models while 1,091,792 cases from 2019 were used to test and compare them. The results showed that indirect conversion through AIS using an NMT was the most accurate in predicting the exact ISS score, followed by direct conversion with FFNN, direct conversion with NMT, and lastly indirect conversion with FFNN, with statistically significant differences in performance on all pairwise comparisons. The rankings were similar when comparing the accuracy of predicting ISS ≥16 classification, however the differences were smaller. The NMT architecture continues to demonstrate notable accuracy in predicting exact ISS scores, but a simpler FFNN approach may be preferred in specific situations, such as if only ISS ≥16 classification is needed or large-scale computational resources are unavailable.","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"103 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140073597","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 : 2024-03-07DOI: 10.1101/2024.03.05.24303814
Li Li, Xiao-xi Tian, Gui-long Feng, Bing Chen
Abstract Introduction: Heparin-binding protein is an inflammatory factor with predictive value and participates in the inflammatory response through antibacterial effects, chemotaxis, and increased vascular permeability. The role of heparin-binding protein in sepsis has been progressively demonstrated, but few studies have been conducted in the context of multiple trauma combined with bacterial infections. This study aims to investigate the predictive value of heparin-binding protein for bacterial infections in patients with severe multiple trauma. Materials and methods: Patients with multiple trauma in the emergency intensive care unit were selected for the study, and plasma heparin-binding protein concentrations and other laboratory parameters were measured within 48 hours of admission to the hospital. A two-sample comparison and univariate logistic regression analysis were used to investigate the relationship between heparin-binding protein and bacterial infection in multiple trauma patients. A multifactor logistic regression model was constructed, and the ROC curve was plotted. Results: Ninety-seven patients with multiple-trauma were included in the study, 43 with bacterial infection and 54 without infection. According to data analysis, heparin-binding protein was higher in the infected group than in the control group [(32.00±3.20) ng/mL vs. (18.52±1.33) ng/mL]. Univariate logistic regression analysis shows that heparin-binding protein is related to bacterial infection (OR=1.10, Z=3.91, 95%CI:1.05~1.15, P=0.001). Multivariate logistic regression equations showed that patients were 1.12 times more likely to have bacterial infections for each value of heparin-binding protein increase, holding neutrophils and PCT constant. ROC analysis shows that heparin-binding protein combined with neutrophils and PCT has better predictive value for bacterial infection [AUC=0.935, 95%CI:0.870~0.977]. Conclusions: Heparin-binding protein may predict bacterial infection in patients with severe multiple trauma. Combining heparin-binding protein, PCT, and neutrophils may improve bacterial infection prediction.
{"title":"The predictive value of heparin-binding protein for bacterial infections in patients with severe multiple trauma","authors":"Li Li, Xiao-xi Tian, Gui-long Feng, Bing Chen","doi":"10.1101/2024.03.05.24303814","DOIUrl":"https://doi.org/10.1101/2024.03.05.24303814","url":null,"abstract":"Abstract\u0000Introduction: Heparin-binding protein is an inflammatory factor with predictive value and participates in the inflammatory response through antibacterial effects, chemotaxis, and increased vascular permeability. The role of heparin-binding protein in sepsis has been progressively demonstrated, but few studies have been conducted in the context of multiple trauma combined with bacterial infections. This study aims to investigate the predictive value of heparin-binding protein for bacterial infections in patients with severe multiple trauma.\u0000Materials and methods: Patients with multiple trauma in the emergency intensive care unit were selected for the study, and plasma heparin-binding protein concentrations and other laboratory parameters were measured within 48 hours of admission to the hospital. A two-sample comparison and univariate logistic regression analysis were used to investigate the relationship between heparin-binding protein and bacterial infection in multiple trauma patients. A multifactor logistic regression model was constructed, and the ROC curve was plotted.\u0000Results: Ninety-seven patients with multiple-trauma were included in the study, 43 with bacterial infection and 54 without infection. According to data analysis, heparin-binding protein was higher in the infected group than in the control group [(32.00±3.20) ng/mL vs. (18.52±1.33) ng/mL]. Univariate logistic regression analysis shows that heparin-binding protein is related to bacterial infection (OR=1.10, Z=3.91, 95%CI:1.05~1.15, P=0.001). Multivariate logistic regression equations showed that patients were 1.12 times more likely to have bacterial infections for each value of heparin-binding protein increase, holding neutrophils and PCT constant. ROC analysis shows that heparin-binding protein combined with neutrophils and PCT has better predictive value for bacterial infection [AUC=0.935, 95%CI:0.870~0.977].\u0000Conclusions: Heparin-binding protein may predict bacterial infection in patients with severe multiple trauma. Combining heparin-binding protein, PCT, and neutrophils may improve bacterial infection prediction.","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"301 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140056733","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 : 2024-03-04DOI: 10.1101/2024.03.04.24303562
Robert Ohle
Objectives: Identify highrisk clinical characteristics for a serious cause of vertigo in patients presenting to the emergency department. Design: Multicentre prospective cohort study over 3 years. Setting: Three university affiliated tertiary care emergency departments. Participants: Patients presenting with vertigo, dizziness or imbalance. A total of 2078 of 2618 potentially eligible patients (79.4%) were enrolled (mean age 77.1 years; 59% women). Main outcome measurements: An adjudicated serious diagnosis defined as stroke, transient ischemic attack, vertebral artery dissection or brain tumour. Results: Serious events occurred in 111 (5.3%) patients. We used logistic regression to create a 7 item prediction model: male, age over 65, hypertension, diabetes, motor/sensory deficits, cerebellar signs/symptoms and benign paroxysmal positional vertigo diagnosis (C statistic 0.96, 95% confidence interval [CI] 0.92 0.98). The risk of a serious diagnosis ranged from 0% for a score of <5, 2.1% for a score of 5-8, and 41% for a score >8. Sensitivity for a serious diagnosis was 100% (95% CI, 97.1 100%) and specificity 72.1% (95% CI, 70.1 74%) for a score <5. Conclusions: The Sudbury Vertigo Risk Score identifies the risk of a serious diagnosis as a cause of a patient's vertigo and can assist physicians in guiding further investigation, consultation and treatment decisions, improving resource utilization and reducing missed diagnoses.
{"title":"Development of a clinical risk score to risk stratify for a serious cause of vertigo: A prospective cohort study","authors":"Robert Ohle","doi":"10.1101/2024.03.04.24303562","DOIUrl":"https://doi.org/10.1101/2024.03.04.24303562","url":null,"abstract":"Objectives: Identify highrisk clinical characteristics for a serious cause of vertigo in patients presenting to the emergency department. Design: Multicentre prospective cohort study over 3 years.\u0000Setting: Three university affiliated tertiary care emergency departments.\u0000Participants: Patients presenting with vertigo, dizziness or imbalance. A total of 2078 of 2618 potentially eligible patients (79.4%) were enrolled (mean age 77.1 years; 59% women). Main outcome measurements: An adjudicated serious diagnosis defined as stroke, transient ischemic attack, vertebral artery dissection or brain tumour.\u0000Results: Serious events occurred in 111 (5.3%) patients. We used logistic regression to create a 7 item prediction model: male, age over 65, hypertension, diabetes, motor/sensory deficits, cerebellar signs/symptoms and benign paroxysmal positional vertigo diagnosis (C statistic 0.96, 95% confidence interval [CI] 0.92 0.98). The risk of a serious diagnosis ranged from 0% for a score of <5, 2.1% for a score of 5-8, and 41% for a score >8. Sensitivity for a serious diagnosis was 100% (95% CI, 97.1 100%) and specificity 72.1% (95% CI, 70.1 74%) for a score <5. Conclusions: The Sudbury Vertigo Risk Score identifies the risk of a serious diagnosis as a cause of a patient's vertigo and can assist physicians in guiding further investigation, consultation and treatment decisions, improving resource utilization and reducing missed diagnoses.","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140037120","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 : 2024-02-27DOI: 10.1101/2024.02.23.24303213
Brian W Patterson, Daniel J Hekman, Frank Liao, Azita Hamedani, Manish N Shah, Majid Afshar
Objective: Numerous studies have identified information overload as a key issue for electronic health records (EHRs). This study describes the amount of text data across all notes available to emergency physicians in the EHR, trended over the time since EHR establishment. Materials and Methods: We conducted a retrospective analysis of EHR data from a large healthcare system, examining the number of notes and corresponding number of total words and total tokens across all notes available to physicians during patient encounters in the emergency department (ED). We assessed the change in these metrics over a 17-year period between 2006 and 2023. Results: The study cohort included 730,968 ED visits made by 293,559 unique patients and a total note count of 132,574,964. The median note count for all encounters in 2006 was 7 (IQR: 3 - 18), accounting for 1,894 words (IQR: 538 - 5,864). By the last full year of the study period in 2022, the median number of notes had grown to 380 (IQR: 93 - 1,008), representing 61,591 words (IQR: 13,621 - 174,152). Note and word counts were higher for admitted patients. Conclusion: The volume of notes available for review by providers has increased by over 30-fold in the 17 years since the implementation of the EHR at a large health system. The task of reviewing these notes has become correspondingly more difficult. These data point to the critical need for new strategies and tools for filtering, synthesizing, and summarizing information to achieve the promise of the medical record.
{"title":"Call Me Dr. Ishmael: Trends in Electronic Health Record Notes Available at ED Visits and Admissions","authors":"Brian W Patterson, Daniel J Hekman, Frank Liao, Azita Hamedani, Manish N Shah, Majid Afshar","doi":"10.1101/2024.02.23.24303213","DOIUrl":"https://doi.org/10.1101/2024.02.23.24303213","url":null,"abstract":"Objective: Numerous studies have identified information overload as a key issue for electronic health records (EHRs). This study describes the amount of text data across all notes available to emergency physicians in the EHR, trended over the time since EHR establishment. Materials and Methods: We conducted a retrospective analysis of EHR data from a large healthcare system, examining the number of notes and corresponding number of total words and total tokens across all notes available to physicians during patient encounters in the emergency department (ED). We assessed the change in these metrics over a 17-year period between 2006 and 2023.\u0000Results: The study cohort included 730,968 ED visits made by 293,559 unique patients and a total note count of 132,574,964. The median note count for all encounters in 2006 was 7 (IQR: 3 - 18), accounting for 1,894 words (IQR: 538 - 5,864). By the last full year of the study period in 2022, the median number of notes had grown to 380 (IQR: 93 - 1,008), representing 61,591 words (IQR: 13,621 - 174,152). Note and word counts were higher for admitted patients.\u0000Conclusion: The volume of notes available for review by providers has increased by over 30-fold in the 17 years since the implementation of the EHR at a large health system. The task of reviewing these notes has become correspondingly more difficult. These data point to the critical need for new strategies and tools for filtering, synthesizing, and summarizing information to achieve the promise of the medical record.","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140003159","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 : 2024-02-27DOI: 10.1101/2024.02.25.24303349
Berihu Assefa, Yemane Gebremedhin Tesfay, Benyam Bahta Gebrehiwot, Frehiwot Worku, Dirijit Mamo Alemu, Menbeu Sultan Mohammed, Mohammed Kalifa Nuguse
Background: Worldwide, 13.3 million people experience Acute Kidney Injury (AKI) each year. 85% of individuals impacted are thought to reside in underdeveloped nations. AKI continues to be one of the most widespread diseases in the world, although little is known about its clinical profile or outcome. The ability to pinpoint particular causes enables the implementation of targeted therapy and the development of preventative measures. The main goal of this study was to identify the patterns and outcomes of patients with AKI in the emergency department of Saint Paul's Hospital Millennium Medical College (SPHMMC). Method and materials: A cross-sectional study was conducted at the emergency department of SPHMMC in Addis Ababa, Ethiopia, from June 1-2021 to June 1-2022. Google Forms was used to collect the data, which was then cleaned up in Microsoft Excel before being sent to SPSS version 25 for analysis. To evaluate demographic, clinical profile, and outcome determinants, descriptive statistics, and binary logistic regression analysis were utilized. A paired samples T-test was used to compare the patient's laboratory findings at admission and discharge. Results: Among the 222 AKI patients included in the study 110 (49.5%) were males and 112 (50.5%) were females. The mean age of presentation was 48+18 years old. The majority of patients were from Addis Ababa (41.4%) and the Oromia region (40.5%). The most common causes of AKI were infections (26.2%), acute glomerulonephritis (20.4%), volume depletion (18.5%), and obstructive uropathy (16.6%). Uremic encephalopathy, infection, malignancy, potassium at discharge from emergency, and low initial Glasgow coma scale (GCS) significantly contributed to the death. The presence of nephrotoxic antibiotics, infection, and hyponatremia significantly contributed to the admission rate to the wards and intensive care unit (ICU). Conclusion: In conclusion, infection is the dominant cause and mortality predictor of AKI at SPHMMC. The majority of patients with infections were sepsis (78.1%), pyelonephritis (11.4%), and pneumonia (10.3%). Early initiation of antibiotics in the emergency is better for a good outcome.
背景：全世界每年有 1330 万人发生急性肾损伤 (AKI)。85%的患者被认为居住在不发达国家。AKI 仍然是世界上最普遍的疾病之一，但人们对其临床概况或预后却知之甚少。本研究的主要目的是确定圣保罗医院千禧医学院（SPHMMC）急诊科 AKI 患者的模式和预后：这项横断面研究于 2021 年 6 月 1 日至 2022 年 6 月 1 日在埃塞俄比亚亚的斯亚贝巴的圣保罗医院千禧医学院急诊科进行。研究人员使用谷歌表格收集数据，然后用 Microsoft Excel 对数据进行清理，再将其发送到 SPSS 25 版本中进行分析。为了评估人口统计学、临床概况和结果决定因素，使用了描述性统计和二元逻辑回归分析。采用配对样本 T 检验比较患者入院和出院时的化验结果：在纳入研究的 222 名 AKI 患者中，110 名（49.5%）为男性，112 名（50.5%）为女性。平均发病年龄为 48+18 岁。大多数患者来自亚的斯亚贝巴（41.4%）和奥罗莫地区（40.5%）。导致急性肾脏病最常见的原因是感染（26.2%）、急性肾小球肾炎（20.4%）、容量耗竭（18.5%）和梗阻性尿病（16.6%）。尿毒症性脑病、感染、恶性肿瘤、急诊出院时血钾、初始格拉斯哥昏迷量表（GCS）偏低是导致死亡的重要原因。肾毒性抗生素、感染和低钠血症的存在明显增加了病房和重症监护室（ICU）的入院率：总之，感染是导致新加坡太平洋医疗中心急性肾损伤的主要原因，也是导致死亡的主要因素。大多数感染患者为败血症（78.1%）、肾盂肾炎（11.4%）和肺炎（10.3%）。在急诊中尽早使用抗生素更有利于获得良好的治疗效果。
{"title":"Clinical Pattern and Outcome of Patients with Acute Kidney Injury in the Emergency Department of Saint Paul`s Hospital Millennium Medical College: A Cross-Sectional Study","authors":"Berihu Assefa, Yemane Gebremedhin Tesfay, Benyam Bahta Gebrehiwot, Frehiwot Worku, Dirijit Mamo Alemu, Menbeu Sultan Mohammed, Mohammed Kalifa Nuguse","doi":"10.1101/2024.02.25.24303349","DOIUrl":"https://doi.org/10.1101/2024.02.25.24303349","url":null,"abstract":"Background: Worldwide, 13.3 million people experience Acute Kidney Injury (AKI) each year. 85% of individuals impacted are thought to reside in underdeveloped nations. AKI continues to be one of the most widespread diseases in the world, although little is known about its clinical profile or outcome. The ability to pinpoint particular causes enables the implementation of targeted therapy and the development of preventative measures.\u0000The main goal of this study was to identify the patterns and outcomes of patients with AKI in the emergency department of Saint Paul's Hospital Millennium Medical College (SPHMMC).\u0000Method and materials: A cross-sectional study was conducted at the emergency department of SPHMMC in Addis Ababa, Ethiopia, from June 1-2021 to June 1-2022. Google Forms was used to collect the data, which was then cleaned up in Microsoft Excel before being sent to SPSS version 25 for analysis. To evaluate demographic, clinical profile, and outcome determinants, descriptive statistics, and binary logistic regression analysis were utilized. A paired samples T-test was used to compare the patient's laboratory findings at admission and discharge.\u0000Results: Among the 222 AKI patients included in the study 110 (49.5%) were males and 112 (50.5%) were females. The mean age of presentation was 48+18 years old. The majority of patients were from Addis Ababa (41.4%) and the Oromia region (40.5%). The most common causes of AKI were infections (26.2%), acute glomerulonephritis (20.4%), volume depletion (18.5%), and obstructive uropathy (16.6%). Uremic encephalopathy, infection, malignancy, potassium at discharge from emergency, and low initial Glasgow coma scale (GCS) significantly contributed to the death. The presence of nephrotoxic antibiotics, infection, and hyponatremia significantly contributed to the admission rate to the wards and intensive care unit (ICU).\u0000Conclusion: In conclusion, infection is the dominant cause and mortality predictor of AKI at SPHMMC. The majority of patients with infections were sepsis (78.1%), pyelonephritis (11.4%), and pneumonia (10.3%). Early initiation of antibiotics in the emergency is better for a good outcome.","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"90 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139980182","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 : 2024-02-24DOI: 10.1101/2024.02.23.24303253
Christopher Smith, Joseph Phillips, Carl Powell, Anthony Sheehan, Mary O Sullivan, Nigel Rees
Background: Cardiopulmonary resuscitation (CPR) and defibrillation at least doubles survival to hospital discharge following out-of-hospital cardiac arrest. Members of the public can perform both before the ambulance service arrives. However, bystanders use a public-access Automated External Defibrillator (AED) in around 5% of cases. Using Unmanned Aerial Vehicles (drones) to deliver AEDs may overcome many of the barriers preventing public-access AED use. We investigated how quickly and easily bystanders performing CPR could use drone-delivered AEDs. Methods: We developed an AED-capable drone between May and November 2020. In July and September 2021, we conducted eighteen out-of-hospital cardiac arrest simulations. A single participant found a simulated patient inside a building and made a 999-call to a Welsh Ambulance Services NHS Trust call-handler. Once cardiac arrest was confirmed during the 999-call a nearby drone launched, reached hovering altitude and delivered the AED immediately outside the building. The participant retrieved the AED when instructed to do so, attached it to the patient and delivered a single shock. The primary outcome was hands-off CPR time. We investigated ease of AED retrieval via a questionnaire adapted from the System Usability Scale and explored participant behaviours via brief post-simulation interviews and reviews of audio (999-call) and video recordings of the simulation. Results: Hands-off CPR time was (median) 109s (interquartile range 87-130s). Participants spent 19s (16-22s) away from the patients side when retrieving the AED. They found it easy to use the AED but often sought reassurance from the call-handler that it was appropriate for them to retrieve it. Conclusion: Participants found it easy to retrieve and use an AED delivered by drone in simulated out-of-hospital cardiac arrests. Hands-off CPR time was potentially clinically relevant in this lone bystander simulation, but there was only a small increase in hands-off time caused by retrieval of the drone-delivered AED.
{"title":"Drone-delivered Automated External Defibrillators for out-of-hospital cardiac arrest. A simulation study.","authors":"Christopher Smith, Joseph Phillips, Carl Powell, Anthony Sheehan, Mary O Sullivan, Nigel Rees","doi":"10.1101/2024.02.23.24303253","DOIUrl":"https://doi.org/10.1101/2024.02.23.24303253","url":null,"abstract":"Background: Cardiopulmonary resuscitation (CPR) and defibrillation at least doubles survival to hospital discharge following out-of-hospital cardiac arrest. Members of the public can perform both before the ambulance service arrives. However, bystanders use a public-access Automated External Defibrillator (AED) in around 5% of cases. Using Unmanned Aerial Vehicles (drones) to deliver AEDs may overcome many of the barriers preventing public-access AED use. We investigated how quickly and easily bystanders performing CPR could use drone-delivered AEDs. Methods: We developed an AED-capable drone between May and November 2020. In July and September 2021, we conducted eighteen out-of-hospital cardiac arrest simulations. A single participant found a simulated patient inside a building and made a 999-call to a Welsh Ambulance Services NHS Trust call-handler. Once cardiac arrest was confirmed during the 999-call a nearby drone launched, reached hovering altitude and delivered the AED immediately outside the building. The participant retrieved the AED when instructed to do so, attached it to the patient and delivered a single shock. The primary outcome was hands-off CPR time. We investigated ease of AED retrieval via a questionnaire adapted from the System Usability Scale and explored participant behaviours via brief post-simulation interviews and reviews of audio (999-call) and video recordings of the simulation. Results: Hands-off CPR time was (median) 109s (interquartile range 87-130s). Participants spent 19s (16-22s) away from the patients side when retrieving the AED. They found it easy to use the AED but often sought reassurance from the call-handler that it was appropriate for them to retrieve it. Conclusion: Participants found it easy to retrieve and use an AED delivered by drone in simulated out-of-hospital cardiac arrests. Hands-off CPR time was potentially clinically relevant in this lone bystander simulation, but there was only a small increase in hands-off time caused by retrieval of the drone-delivered AED.","PeriodicalId":501290,"journal":{"name":"medRxiv - Emergency Medicine","volume":"196 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953158","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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