Purpose The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury.Early recognition of patients is an important case of such decisi...Purpose The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury.Early recognition of patients is an important case of such decision-making with risk of worse prognosis.This article is to answer if clinical and paraclinical signs can predict the critical conditions of injured patients after traumatic injury resuscitation.Methods The study included 1107 trauma patients,16 years and older.The patients were trauma victims of Levels I and II triage and admitted to the Rajaee(Emtiaz)Trauma Hospital,Shiraz,in 2014–2015.The cross-industry process for data mining methodology and modeling was used for assessing the best early clinical and paraclinical variables to predict the patients’prognosis.Five modeling methods including the support vector machine,K-nearest neighbor algorithms,Bagging and Adaboost,and the neural network were compared by some evaluation criteria.Results Learning algorithms can predict the deterioration of injured patients by monitoring the Bagging and SVM models with 99%accuracy.The most-fitted variables were Glasgow Coma Scale score,base deficit,and diastolic blood pressure especially after initial resuscitation in the algorithms for overall outcome predictions.Conclusion Data mining could help in triage,initial treatment,and further decision-making for outcome measures in trauma patients.Clinical and paraclinical variables after resuscitation could predict short-term outcomes much better than variables on arrival.With artificial intelligence modeling system,diastolic blood pressure after resuscitation has a greater association with predicting early mortality rather than systolic blood pressure after resuscitation.Artificial intelligence monitoring may have a role in trauma care and should be further investigated.展开更多
Propose:In this study,we re-assessed the criteria defined by the radiological society of North America(RSNA)to determine novel radiological findings helping the physicians differentiating COVID-19 from pulmonary contu...Propose:In this study,we re-assessed the criteria defined by the radiological society of North America(RSNA)to determine novel radiological findings helping the physicians differentiating COVID-19 from pulmonary contusion.Methods:All trauma patients with blunt chest wall trauma and subsequent pulmonary contusion,COVID-19-related signs and symptoms before the trauma were enrolled in this retrospective study from February to May 2020.Included patients(Group P)were then classified into two groups based on polymerase chain reaction tests(Group Pa for positive patients and Pb for negative ones).Moreover,44 patients from the prepandemic period(Group PP)were enrolled.They were matched to Group P regarding age,sex,and trauma-related scores.Two radiologists blindly reviewed the CT images of all enrolled patients according to criteria defined by the RSNA criteria.The radiological findings were compared between Group P and Group PP;statistically significant ones were re-evaluated between Group Pa and Group Pb thereafter.Finally,the sensitivity and specificity of each significant findings were calculated.The Chi-square test was used to compare the radiologica丨findings between Group P and Group PP.Results:In the Group PP,73.7%of all ground-glass opacities(GGOs)and 80%of all multiple bilateral GGOs were detected(p<0.001 and p=0.25,respectively).Single bilateral GGOs were only seen among the Group PP.The Chi-square tests showed that the prevalence of diffused GGOs,multiple unilateral GGOs,multiple consolidations,and multiple bilateral consolidations were significantly higher in the Group P(p=0.001,0.01,0.003,and 0.003,respectively).However,GGOs with irregular borders and single consolidations were more significant among the Group PP(p=0.01 and 0.003,respectively).Of note,reticular distortions and subpleural spares were exclusively detected in the Group PP.Conclusion:We concluded that the criteria set by RSNA for the diagnosis of COVID-19 are not appropriate in trauma patients.The clinical signs and symptoms are not always useful either.The presence of multiple unilateral GGOs,diffused GGOs,and multiple bilateral consolidations favor COVID-19 with 88%,97.62%,and 77.7%diagnostic accuracy.展开更多
文摘Purpose The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury.Early recognition of patients is an important case of such decision-making with risk of worse prognosis.This article is to answer if clinical and paraclinical signs can predict the critical conditions of injured patients after traumatic injury resuscitation.Methods The study included 1107 trauma patients,16 years and older.The patients were trauma victims of Levels I and II triage and admitted to the Rajaee(Emtiaz)Trauma Hospital,Shiraz,in 2014–2015.The cross-industry process for data mining methodology and modeling was used for assessing the best early clinical and paraclinical variables to predict the patients’prognosis.Five modeling methods including the support vector machine,K-nearest neighbor algorithms,Bagging and Adaboost,and the neural network were compared by some evaluation criteria.Results Learning algorithms can predict the deterioration of injured patients by monitoring the Bagging and SVM models with 99%accuracy.The most-fitted variables were Glasgow Coma Scale score,base deficit,and diastolic blood pressure especially after initial resuscitation in the algorithms for overall outcome predictions.Conclusion Data mining could help in triage,initial treatment,and further decision-making for outcome measures in trauma patients.Clinical and paraclinical variables after resuscitation could predict short-term outcomes much better than variables on arrival.With artificial intelligence modeling system,diastolic blood pressure after resuscitation has a greater association with predicting early mortality rather than systolic blood pressure after resuscitation.Artificial intelligence monitoring may have a role in trauma care and should be further investigated.
文摘Propose:In this study,we re-assessed the criteria defined by the radiological society of North America(RSNA)to determine novel radiological findings helping the physicians differentiating COVID-19 from pulmonary contusion.Methods:All trauma patients with blunt chest wall trauma and subsequent pulmonary contusion,COVID-19-related signs and symptoms before the trauma were enrolled in this retrospective study from February to May 2020.Included patients(Group P)were then classified into two groups based on polymerase chain reaction tests(Group Pa for positive patients and Pb for negative ones).Moreover,44 patients from the prepandemic period(Group PP)were enrolled.They were matched to Group P regarding age,sex,and trauma-related scores.Two radiologists blindly reviewed the CT images of all enrolled patients according to criteria defined by the RSNA criteria.The radiological findings were compared between Group P and Group PP;statistically significant ones were re-evaluated between Group Pa and Group Pb thereafter.Finally,the sensitivity and specificity of each significant findings were calculated.The Chi-square test was used to compare the radiologica丨findings between Group P and Group PP.Results:In the Group PP,73.7%of all ground-glass opacities(GGOs)and 80%of all multiple bilateral GGOs were detected(p<0.001 and p=0.25,respectively).Single bilateral GGOs were only seen among the Group PP.The Chi-square tests showed that the prevalence of diffused GGOs,multiple unilateral GGOs,multiple consolidations,and multiple bilateral consolidations were significantly higher in the Group P(p=0.001,0.01,0.003,and 0.003,respectively).However,GGOs with irregular borders and single consolidations were more significant among the Group PP(p=0.01 and 0.003,respectively).Of note,reticular distortions and subpleural spares were exclusively detected in the Group PP.Conclusion:We concluded that the criteria set by RSNA for the diagnosis of COVID-19 are not appropriate in trauma patients.The clinical signs and symptoms are not always useful either.The presence of multiple unilateral GGOs,diffused GGOs,and multiple bilateral consolidations favor COVID-19 with 88%,97.62%,and 77.7%diagnostic accuracy.