Abstract：ObjectiveTo evaluate the clinical value of breathing force index and fast and shallow breathing index in predicting offline capacity and weaning conditions in the ICU patients receiving mechanical ventilation.MethodsA total of 57 patients with chronic obstructive pulmonary disease(COPD)who were admitted to ICU in our hospital and given mechanical ventilation and successful weaning from March 2015 to March 2017 were selected.Then 57 patients with COPD who were given mechanical ventilation during the same period but the weaning was failed were selected.The patients were respectively assigned to the study group and the control group.The existing ventilator in our hospital was adopted to measure the two indices of breathing force index and fast and shallow breathing index in the study subjects of both groups,and the measurement results of the two indices and the positive rate of results were compared.ResultsThe breathing force index in the study group was significantly higher than that in the control group,and the difference between groups was significant(P＜0.05);the fast and shallow breathing index was lower than that in the control group,and the difference was significant(P＜0.05).The positive rate of breathing force index and fast and shallow breathing index positive rate of the difference was significant between the groups(P＜0.05).ConclusionIn the ICU patients receiving mechanical ventilation,the breathing force index for the patients with successful weaning is significantly higher than that in the failed ones,and the fast and shallow of breathing index is significantly lower than that in the failed ones.Clinically,according to this feature,a more objective and accurate judgment of whether the patient is in compliance with the conditions of weaning during the treatment can be made.
占根生;张满良;李丽荣;张倩玮. 呼吸频率、顺应性、氧合、呼吸用力指数预测ICU患者脱机能力的临床研究[J]. 中国当代医药, 2017, 24(32): 17-19.
ZHAN Gen-sheng;ZHANG Man-liang;LI Li-rong;ZHANG Qian-wei. Clinical study on respiratory rate，compliance，oxygenation and breathing force index in predicting offline capability in ICU patients. 中国当代医药, 2017, 24(32): 17-19.
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