1 10 14 https://repository.horizon.ac.id/files/original/dad6cedc2cb9f3d8b24f6da7b388a8c4.PDF babfe7d752c3cd2ea37f3c5a9b9d4de2 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A prediction model for massive hemorrhage in trauma: a retrospective observational study Subject The topic of the resource Trauma, Massive hemorrhage, LASSO, Prediction model, Assisted diagnosis Description An account of the resource Background: Massive hemorrhage is the main cause of preventable death after trauma. This study aimed to estab�lish prediction models for early diagnosis of massive hemorrhage in trauma. Methods: Using the trauma database of Chinese PLA General Hospital, two logistic regression (LR) models were ft to predict the risk of massive hemorrhage in trauma. Sixty-two potential predictive variables, including clinical symptoms, vital signs, laboratory tests, and imaging results, were included in this study. Variable selection was done using the least absolute shrinkage and selection operator (LASSO) method. The frst model was constructed based on LASSO feature selection results. The second model was constructed based on the frst vital sign recordings of trauma patients after admission. Finally, a web calculator was developed for clinical use. Results: A total of 2353 patients were included in this study. There were 377 (16.02%) patients with massive hemor�rhage. The selected predictive variables were heart rate (OR: 1.01; 95% CI: 1.01–1.02; P<0.001), pulse pressure (OR: 0.99; 95% CI: 0.98–0.99; P=0.004), base excess (OR: 0.90; 95% CI: 0.87–0.93; P<0.001), hemoglobin (OR: 0.95; 95% CI: 0.95–0.96; P<0.001), displaced pelvic fracture (OR: 2.13; 95% CI: 1.48–3.06; P<0.001), and a positive computed tomogra�phy scan or positive focused assessment with sonography for trauma (OR: 1.62; 95% CI: 1.21–2.18; P=0.001). Model 1, which was developed based on LASSO feature selection results and LR, displayed excellent discrimination (AUC: 0.894; 95% CI: 0.875–0.912), good calibration (P=0.405), and clinical utility. In addition, the predictive power of model 1 was better than that of model 2 (AUC: 0.718; 95% CI: 0.679–0.757). Model 1 was deployed as a public web tool (http://82. 156.217.249:8080/). Conclusions: Our study developed and validated prediction models to assist medical staf in the early diagnosis of massive hemorrhage in trauma. An open web calculator was developed to facilitate the practical application of the research results. Creator An entity primarily responsible for making the resource Chengyu Guo, Minghui Gong, Lei Ji, Fei Pan, Hui Han, Chunping Li and Tanshi Li Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:180 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Assisted diagnosis Jurnal Internasional Keperawatan LASSO Massive hemorrhage Prediction model Trauma https://repository.horizon.ac.id/files/original/2bbf6057571f25d7cb042231907d4e48.PDF 44d4137dadfdac9d884db691a3b93aef Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Association between variables measured in the ambulance and in-hospital mortality among adult patients with and without infection: a prospective cohort study Subject The topic of the resource Mortality, Infection, Sepsis, Emergency medical services, Prehospital, Emergency care Description An account of the resource Background: Patients presenting with infection to the ambulance are common, but risk factors for poor outcome are not known. The primary aim of the current study was to study the association between variables measured in the ambulance and mortality among adult patients with and without infection. The secondary aim was to study the association between these variables and mortality in a subgroup of patients who developed sepsis within 36 h. Methods: Prospective cohort study of 553 ambulance patients with, and 318 patients without infection, performed in Stockholm during 2017–2018. The association between 21 variables (8 keywords related to medical history, 6 vital signs, 4 blood tests, and age, gender, comorbidity) and in-hospital mortality was analysed using logistic regression. Results: Among patients with infection, inability of the patient to answer questions relating to certain symptoms such as pain and gastrointestinal symptoms was signifcantly associated with mortality in univariable analysis, in addition to oxygen saturation<94%, heart rate>110 /min, Glasgow Coma Scale (GCS)<15, soluble urokinase Plasminogen Activator Receptor (suPAR) 4.0–7.9 ng/mL, suPAR≥8.0 ng/mL and a Charlson comorbidity score≥5. suPAR≥8.0 ng/mL remained signifcant in multivariable analysis (OR 25.4; 95% CI, 3.2–199.8). Among patients without infection, suPAR≥8.0 ng/mL and a Charlson comorbidity score≥5 were signifcantly associated with mortality in uni‑ variable analysis, while suPAR≥8.0 ng/mL remained signifcant in multivariable analysis (OR 56.1; 95% CI, 4.5–700.0). Among patients who developed sepsis, inability to answer questions relating to pain remained signifcant in multi‑ variable analysis (OR 13.2; 95% CI, 2.2–78.9), in addition to suPAR≥8.0 ng/mL (OR 16.1; 95% CI, 2.0–128.6). Conclusions: suPAR≥8.0 ng/mL was associated with mortality in patients presenting to the ambulance both with and without infection and in those who developed sepsis. Furthermore, the inability of the ambulance patient with an infection to answer questions relating to specifc symptoms was associated with a surprisingly high mortality. These results suggest that suPAR and medical history are valuable tools with which to identify patients at risk of poor outcome in the ambulance and could potentially signal the need of enhanced attention. Trial registration: ClinicalTrials.gov, NCT03249597. Registered 15 August 2017—Retrospectively registered, https:// clinicaltrials.gov/ct2/show/NCT03249597 Creator An entity primarily responsible for making the resource Ulrika Margareta Wallgren, Hans Järnbert‑Pettersson, Jan Sjölin and Lisa Kurland Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:185 Contributor An entity responsible for making contributions to the resource Fajar Bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Emergency care Emergency medical services infection Jurnal Internasional Keperawatan mortality Prehospital sepsis https://repository.horizon.ac.id/files/original/a1abab22063fa2b62fbabaf16223c696.PDF e515f46188e33e906ff94ed126768bd9 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Early prediction model of brain death in out-of-hospital cardiac arrest patients: a single-center retrospective and internal validation analysis Subject The topic of the resource Brain death, Out-of-hospital cardiac arrest, Cardiopulmonary resuscitation, Organ donation, Prediction model Description An account of the resource Background: A shortage of donor organs amid high demand for transplantable organs is a worldwide problem, and an increase in organ donation would be welcomed by the global healthcare system. Patients with brain death (BD) are potential organ donors, and early prediction of patients with BD may facilitate the process of organ procurement. Therefore, we developed a model for the early prediction of BD in patients who survived the initial phase of out-of�hospital cardiac arrest (OHCA). Methods: We retrospectively analyzed data of patients aged<80 years who experienced OHCA with a return of spontaneous circulation (ROSC) and were admitted to our hospital between 2006 and 2018. We categorized patients into either a non-BD or BD group. Demographic and laboratory data on ED admission were used for stepwise logistic regression analysis. Prediction scores of BD after OHCA were based on β-coefcients of prognostic factors identifed in the multivariable logistic model. Results: Overall, 419 OHCA patients with ROSC were admitted to our hospital during the study period. Seventy�seven patients showed BD (18.3%). Age and etiology of OHCA were signifcantly diferent between the groups. Logis�tic regression analysis confrmed that age, low-fow time, pH, and etiology were independent predictors of BD. The area under the receiver operating characteristic curve for this model was 0.831 (95% confdence interval, 0.786–0.876). Conclusions: We developed and internally validated a new prediction model for BD after OHCA, which could aid in the early identifcation of potential organ donors for early donor organ procurement. Creator An entity primarily responsible for making the resource Yuki Itagaki , Mineji Hayakawa, Kunihiko Maekawa, Akira Kodate, Koyo Moriki, Yuki Takahashi and Hisako Sageshima Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:177 Contributor An entity responsible for making contributions to the resource Fajar Bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Brain death Cardiopulmonary resuscitation Jurnal Internasional Keperawatan Organ donation Out-of-hospital Cardiac Arrest Prediction model https://repository.horizon.ac.id/files/original/d708210b70f367d9a960797b0d7b0045.PDF 4b043ef11dd19cb7e999eebaad562d9d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Factors infuencing conveyance of older adults with minor head injury by paramedics to the emergency department: a multiple methods study Subject The topic of the resource Head Injury, Minor, Injuries, Head, Aged 65+, Paramedic, Emergency Medical Services, Interview, Decision Making Description An account of the resource Background: Head injury (HI) in older adults due to low-energy falls result in a substantial number of emergency department (ED) attendances. However, mortality associated with minor HI is very low. Reducing conveyance to hospital is important for older adults and is a priority for the National Health Service (NHS). Therefore, paramedics are required to make accurate decisions regarding conveyance to the ED. This study used routine data and semi�structured interviews to explore the factors that infuence paramedic decision-making when considering whether to convey an adult aged 65 years and over with a minor HI to the ED. Methods: Semi-structured telephone interviews were completed with ten UK paramedics from a single EMS (ambu�lance) provider organisation. Interviews explored the factors infuencing the paramedics’ conveyance decision-mak�ing in adults aged 65 years and over with a minor HI. Data were initially analysed inductively to develop a thematic framework. A retrospective analysis of ambulance service data was also completed to determine the scope and scale of the issue in Southwest England. An in-depth audit of 100 conveyed patient records was used to determine the proportion of patients conveyed to the ED who met National Institute for Health and Care Excellence (NICE) and Joint Royal Colleges Ambulance Liaison Committee (JRCALC) guidelines. Results: In 2019 South Western Ambulance Service NHS Foundation Trust (SWASFT) attended 15,650 emergency calls to patients aged 65 and over with minor HI, with 70.5% conveyed to ED. 81% of conveyed patients met NICE and JRCALC guideline criteria for conveyance, with the remainder conveyed due to wound care or other medical concerns. The framework developed from the interviews comprised four themes: resources; patient factors; conse�quences; paramedic factors. Important factors included: the patient’s social situation; guidelines; clinical support avail�ability; the history and presentation of the patient; risk. Conclusion: This study examined paramedic conveyance decisions for older people with minor HI. It identifed mul�tiple infuencing factors, highlighting the complex nature of these decisions, and may serve as a basis for developing an intervention to safely decrease ED conveyance in this patient group Creator An entity primarily responsible for making the resource Helen Nicholson, Sarah Voss, Sarah Black, Hazel Taylor, David Williams and Jonathan Benger Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:184 Contributor An entity responsible for making contributions to the resource Fajar Bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Aged 65+ Decision Making Emergency Medical Services, Head Head Injury Injuries Interview Jurnal Internasional Keperawatan Minor Paramedic https://repository.horizon.ac.id/files/original/9925f36a16fc58b39c2fd4fd20612a52.PDF e742614b25bddd3560d4384772c382f5 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource High-risk diagnosis combinations in patients undergoing interhospital transfer: a retrospective observational study Subject The topic of the resource Electronic health records, Transportation of patients, Machine learning, Emergency helicopter, Helicopter ambulance Description An account of the resource Background: There is limited research on individual patient characteristics, alone or in combination, that contribute to the higher levels of mortality in post-transfer patients. The purpose of this work is to identify signifcant combina�tions of diagnoses that identify subgroups of post-interhospital transfer patients experiencing the highest levels of mortality. Methods: This was a retrospective cross-sectional study using structured electronic health record data from a regional health system between 2010–2017. We employed a machine learning approach, association rules mining using the Apriori algorithm to identify diagnosis combinations. The study population includes all patients aged 21 and older that were transferred within our health system from a community hospital to one of three main receiving hospitals. Results: Overall, 8893 patients were included in the analysis. Patients experiencing mortality post-transfer were on average older (70.5 vs 62.6 years) and on average had more diagnoses in 5 of the 6 diagnostic subcategories. Within the diagnostic subcategories, most diagnoses were comorbidities and active medical problems, with hypertension, atrial fbrillation, and acute respiratory failure being the most common. Several combinations of diagnoses identifed patients that exceeded 50% post-interhospital transfer mortality. Conclusions: Comorbid burden, in combination with active medical problems, were most predictive for those experiencing the highest rates of mortality. Further improving patient level prognostication can facilitate informed decision making between providers and patients to shift the paradigm from transferring all patients to higher level care to only transferring those who will beneft or desire continued care, and reduce futile transfers. Creator An entity primarily responsible for making the resource Andrew P. Reimer, Nicholas K. Schiltz and Siran M. Koroukian Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:187 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Electronic health records Emergency helicopter Helicopter ambulance Jurnal Internasional Keperawatan machine learning Transportation of patients https://repository.horizon.ac.id/files/original/9739ddaf1490673e834938accbf64d4f.PDF 1f60528144bd9be32916c1cc4ffc105f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Overcrowding analysis in emergency department through indexes: a single center study Subject The topic of the resource Emergency Department, Overcrowding, EDWIN Index, NEDOCS Index Description An account of the resource Introduction: Overcrowding in the Emergency Department (ED) is one of the major issues that must be addressed in order to improve the services provided in emergency circumstances and to optimize their quality. As a result, in order to help the patients and professionals engaged, hospital organizations must implement remedial and preventa�tive measures. Overcrowding has a number of consequences, including inadequate treatment and longer hospital stays; as a result, mortality and the average duration of stay in critical care units both rise. In the literature, a number of indicators have been used to measure ED congestion. EDWIN, NEDOCS and READI scales are considered the most efcient ones, each of which is based on diferent parameters regarding the patient management in the ED. Methods: In this work, EDWIN Index and NEDOCS Index have been calculated every hour for a month period from February 9th to March 9th, 2020 and for a month period from March 10th to April 9th, 2020. The choice of the period is related to the date of the establishment of the lockdown in Italy due to the spread of Coronavirus; in fact on 9 March 2020 the Italian government issued the frst decree regarding the urgent provisions in relation to the COVID- 19 emergency. Besides, the Pearson correlation coefcient has been used to evaluate how much the EDWIN and NEDOCS indexes are linearly dependent. Results: EDWIN index follows a trend consistent with the situation of the frst lockdown period in Italy, defned by extreme limitations imposed by Covid-19 pandemic. The 8:00–20:00 time frame was the most congested, with peak values between 8:00 and 12:00. on the contrary, in NEDOCS index doesn’t show a trend similar to the EDWIN one, resulting less reliable. The Pearson correlation coefcient between the two scales is 0,317. Conclusion: In this study, the EDWIN Index and the NEDOCS Index were compared and correlated in order to assess their efcacy, applying them to the case study of the Emergency Department of “San Giovanni di Dio e Ruggi d’Aragona” University Hospital during the Covid-19 pandemic. The EDWIN scale turned out to be the most realistic model in relation to the actual crowding of the ED subject of our study. Besides, the two scales didn’t show a signif�cant correlation value. Creator An entity primarily responsible for making the resource Ylenia Colella, Danilo Di Laura, Anna Borrelli, Maria Triassi, Francesco Amato and Giovanni Improta Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:181 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text EDWIN Index Emergency department Jurnal Internasional Keperawatan NEDOCS Index Overcrowding https://repository.horizon.ac.id/files/original/eda0d75b1287fa4353d0a77f67f76e7d.PDF 1732e46365e095c5d7235c850a5d53a5 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Patient and hospital characteristics predict prolonged emergency department length of stay and in-hospital mortality: a nationwide analysis in Korea Subject The topic of the resource Emergency department, Critical care, Intensive care unit, Length of stay, In-hospital mortality Description An account of the resource Background: Prolonged emergency department length of stay (EDLOS) in critically ill patients leads to increased mortality. This nationwide study investigated patient and hospital characteristics associated with prolonged EDLOS and in-hospital mortality in adult patients admitted from the emergency department (ED) to the intensive care unit (ICU). Methods: We conducted a retrospective cohort study using data from the National Emergency Department Infor‑ mation System. Prolonged EDLOS was defned as an EDLOS of≥6 h. We constructed multivariate logistic regression models of patient and hospital variables as predictors of prolonged EDLOS and in-hospital mortality. Results: Between 2016 and 2019, 657,622 adult patients were admitted to the ICU from the ED, representing 2.4% of all ED presentations. The median EDLOS of the overall study population was 3.3 h (interquartile range, 1.9–6.1 h) and 25.3% of patients had a prolonged EDLOS. Patient characteristics associated with prolonged EDLOS included night�time ED presentation and Charlson comorbidity index (CCI) score of 1 or higher. Hospital characteristics associated with prolonged EDLOS included a greater number of stafed beds and a higher ED level. Prolonged EDLOS was associ‑ ated with in-hospital mortality after adjustment for selected confounders (adjusted odds ratio: 1.18, 95% confdence interval: 1.16–1.20). Patient characteristics associated with in-hospital mortality included age≥65 years, transferred-in, artifcially ventilated in the ED, assignment of initial triage to more urgency, and CCI score of 1 or higher. Hospital char‑ acteristics associated with in-hospital mortality included a lesser number of stafed beds and a lower ED level. Conclusions: In this nationwide study, 25.3% of adult patients admitted to the ICU from the ED had a prolonged EDLOS, which in turn was signifcantly associated with an increased in-hospital mortality risk. Hospital characteris‑ tics, including the number of stafed beds and the ED level, were associated with prolonged EDLOS and in-hospital mortality Creator An entity primarily responsible for making the resource Kyung‑Shin Lee, Hye Sook Min, Jae Young Moon, Daesung Lim, Younghwan Kim, Eunsil Ko, You Sun Kim, Joohae Kim, Jeehye Lee and Ho Kyung Sung Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:183 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Critical care Emergency department in-hospital mortality Intensive care unit Jurnal Internasional Keperawatan Length of stay https://repository.horizon.ac.id/files/original/74efc7db05401e4ca4590b40c836b22d.PDF 909ec37f107aa00e5a117303a636c51b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Perceived human factors from the perspective of paramedics – a qualitative interview study Subject The topic of the resource Emergency medical services, Ergonomics, Paramedic, Work environment, Prehospital emergency care Description An account of the resource Background: The work environment in prehospital emergency medical care setting is dynamic and complex and includes many stressors. However, little is known about the perceived human factors from the perspective of para�medics. In this study, we investigated, from the perspective of paramedics, what are the human factors, and how are they linked to prehospital emergency medical care? Methods: Data were collected through semi-structured interviews (n=15) with Finnish paramedics. The material was analyzed using inductive content analysis. Results: Three main categories of human factors were identifed. The frst main category consisted of factors related to work which were divided into two generic categories: “Challenging organizational work environment” and “Chang�ing external work environment.” The second main category comprised factors related to paramedics themselves and were divided into three generic categories: “Issues linked to personality,” “Personal experiences”, and “Factors resulting from personal features.” The third main category described that paramedics have difculties in understanding and describing human factors. Conclusion: This study revealed numerous factors that can afect paramedics’ work in the EMS setting. Increased knowledge about human factors in the EMS setting provides organizations with the opportunity to develop pro�cedures that can support paramedics’ cognitive and physical work. Human factors in diferent situations can be addressed to improve occupational and patient safety Creator An entity primarily responsible for making the resource Anna Poranen, Anne Kouvonen and Hilla Nordquist Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:178 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource english Type The nature or genre of the resource Text Emergency medical services Ergonomics Jurnal Internasional Keperawatan Paramedic Prehospital emergency care Work environment https://repository.horizon.ac.id/files/original/0dbee654497b052849b1607afd652725.PDF 909ec37f107aa00e5a117303a636c51b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Predicting hypoglycemia after treatment of hyperkalemia with insulin and glucose (Glu-K60 score) Subject The topic of the resource Hyperkalemia, Hypoglycemia, Insulin, Prediction Description An account of the resource Background: Hyperkalemia can lead to fatal cardiac arrhythmias. Ten units of intravenous (IV) regular insulin with 25 g of glucose is the mainstay for treating hyperkalemia. However, the most important complication of this treatment is hypoglycemia. We aimed to develop a scoring model to predict hypoglycemia after the treatment of hyperkalemia. Methods: A retrospective study was conducted at a university-based hospital between January 2013 and June 2021. We included the hyperkalemic patients (>5.3 mmol/L) who were≥18 years old and treated with 10 units of IV regular insulin with 25 g of glucose. Incomplete data on posttreatment blood glucose, pregnancy, and diabetes mellitus were excluded. Endpoint was posttreatment hypoglycemia (≤70 mg/dL or≤3.9 mmol/L). Multivariable logistic regres�sion was used to establish a full model and a subsequently reduced model using the backward elimination method. We demonstrated the model performance using the area under the receiver operating characteristic curve (AuROC), calibration plot, and Hosmer–Lemeshow goodness-of-ft test. Internal validation was done with a bootstrap sampling procedure with 1000 replicates. Model optimism was estimated. Results: Three hundred and eighty-fve patients were included, with 97 posttreatment hypoglycemia (25.2%). The predictive model comprised the following three criteria: age>60 years old, pretreatment blood glucose≤100 mg/ dL (≤5.6 mmol/L), and pretreatment potassium>6 mmol/L. The AuROC of this model was 0.671 (95% confdence interval [CI] 0.608 to 0.735). The calibration plot demonstrated consistency with the original data. Hosmer–Lemeshow goodness-of-ft test showed no evidence of lack-of-ft (p 0.792); therefore, the model was also ft to the original data. Internal validation via bootstrap sampling showed a consistent AuROC of 0.670 (95% CI 0.660 to 0.670) with minimal model optimism. A high risk for posttreatment hypoglycemia was indicated if the patient met at least one of those criteria. Sensitivity and specifcity were 95.9% and 14.9%, respectively. Conclusion: High risk was indicated when at least one of the criteria was met: age>60 years old, pretreatment blood glucose≤100 mg/dL (≤5.6 mmol/L), and pretreatment potassium>6 mmol/L. Blood glucose levels should frequently check in the high-risk group. Trial registration: TCTR20210225002 (www.thaiclinicaltrials.org). Creator An entity primarily responsible for making the resource Weerapriya Kijprasert, Nilanut Tarudeeyathaworn, Chananthita Loketkrawee, Thidarat Pimpaporn, Pornpiyapat Pattarasettaseranee and Theerapon Tangsuwanaruk Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:179 Contributor An entity responsible for making contributions to the resource Fajar Bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Hyperkalemia Hypoglycemia insulin Jurnal Internasional Keperawatan Prediction https://repository.horizon.ac.id/files/original/d4cc251dcaf8283d45bd0656cca29cc7.PDF 225cd425a5ce3500b6b4388a77d4bc25 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 22 ISSUE 3 NOVEMBER 2022 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Role of CD8+ T cell exhaustion in the progression and prognosis of acute respiratory distress syndrome induced by sepsis: a prospective bservational study Subject The topic of the resource Sepsis, Acute respiratory distress syndrome, CD8+ T cell exhaustion, Coinhibitory receptors, Prognosis Description An account of the resource Background: CD8+ T cells are important for protective immunity against intracellular pathogens. Excessive amounts of antigen and/or infammatory signals often lead to the gradual deterioration of CD8+ T cell function, a state called “exhaustion”. However, the association between CD8+ T cell exhaustion and acute respiratory distress syndrome (ARDS) has not been studied. This study was conducted to elucidate how CD8+ T cells and inhibitory receptors were related to the clinical prognosis of ARDS. Methods: A prospective observational study in an emergency department enrolled patients who were diagnosed with sepsis-associated ARDS according to the sepsis-3 criteria and Berlin defnition. Peripheral blood samples were collected within 24h post recruitment. CD8+ T cell count, proliferation ratio, cytokine secretion, and the expression of coinhibitory receptors were assayed. Results: Sixty-two patients with ARDS met the inclusion criteria. CD8+ T cell counts and proliferation rates were dramatically decreased in non-surviving ARDS patients. Increasing programmed cell death 1 (PD-1) expression on the CD8+ T cell surface was seen in patients with worse organ function, while an increasing level of T cell immunoglobu�lin mucin-3 (Tim-3) was associated with a longer duration of the shock. Kaplan–Meier analysis showed that low CD8+ T cell percentages and increased inhibitory molecule expression were signifcantly associated with a worse survival rate. Conclusions: CD8+ T cells and coinhibitory receptors are promising independent prognostic markers of sepsis�induced ARDS, and increased CD8+ T cell exhaustion is signifcantly correlated with poor prognosis. Creator An entity primarily responsible for making the resource Lei Yan, Yumei Chen, Yi Han and Chaoyang Tong Publisher An entity responsible for making the resource available BMC Emergency Medicine Date A point or period of time associated with an event in the lifecycle of the resource (2022) 22:182 Contributor An entity responsible for making contributions to the resource Fajar Bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Acute respiratory distress syndrome CD8+ T cell exhaustion Coinhibitory receptors Jurnal Internasional Keperawatan prognosis sepsis