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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.
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Objective: to compare the healing process of pressure ulcers treated with cryopreserved human amniotic membrane allograft and routine pressure ulcer care in our hospital
Methods: from January 2012 to December 2013, in a prospective randomized clinical trial [IRCT201612041335N2], 24 patients with second and third stage of pressure ulcers were enrolled in this study. All patients needed split thickness skin grafts for pressure ulcer-wound coverage. Selected patients had symmetric ulcers on both upper and lower extremities. The patients were randomly divided into two groups: amnion and control. In the amnion group, the ulcer was covered with cryopreserved amniotic membrane and in the control group it was treated with local Dilantin powder application. The duration and success rate of complete healing was compared between the two groups
Results: the study group was composed of 24 pressure ulcers in 24 patients [19 males and 5 females] with a mean age of 44+/-12.70 years. The demographic characteristics, ulcer area, and underlying diseases were similar in both groups. The early sign of response, such as decrease in wound discharge, was detected 12-14 days after biological dressing. Complete pressure ulcer healing occurred only in the amnion group [p<0.001]. Partial healing was significantly higher in the amnion group [p<0.03]. Healing time in this group was faster than that the control group [20 days versus 54 days]. No major complication was recorded with amniotic membrane dressing
Conclusion: cryopreserved amniotic membrane is an effective biologic dressing that promotes reepithelialization in pressure ulcers