創(chuàng)傷后膿毒癥護理預(yù)警評估系統(tǒng)軟件的研發(fā)
發(fā)布時間:2018-06-03 08:41
本文選題:創(chuàng)傷 + 膿毒癥 ; 參考:《第三軍醫(yī)大學(xué)》2017年碩士論文
【摘要】:研究目的1.從感染角度分析創(chuàng)傷患者并發(fā)膿毒癥的危險因素。2.確立基于危險因素的創(chuàng)傷后膿毒癥集束化預(yù)防護理措施。3.研發(fā)創(chuàng)傷后膿毒癥護理預(yù)警評估系統(tǒng)軟件。資料與方法1.收集2012-2015年227例重慶市大坪醫(yī)院ICU創(chuàng)傷后感染患者資料,采用SPSS及Excel軟件,通過T檢驗、×2檢驗、Logistic回歸分析、ROC曲線分析等,得出創(chuàng)傷后膿毒癥危險因素,據(jù)Logistic分析結(jié)果構(gòu)建創(chuàng)傷后膿毒癥預(yù)警公式,據(jù)ROC分析結(jié)果構(gòu)建創(chuàng)傷后膿毒癥風(fēng)險評估量表。2.收集2012-2016年475例重慶市大坪醫(yī)院創(chuàng)傷患者資料,通過描述性統(tǒng)計、預(yù)測價值分析等對創(chuàng)傷后膿毒癥風(fēng)險評估表用于創(chuàng)傷后膿毒癥預(yù)警的有效性進行驗證,包括靈敏度、特異度、陽性預(yù)測值、陰性預(yù)測值等。3.采用文獻閱讀法、小組討論法、臨床實踐法初步擬定創(chuàng)傷后膿毒癥集束化護理預(yù)防措施條目,經(jīng)專家咨詢使其最終確定。4.采用Python軟件編輯工具,對創(chuàng)傷后膿毒癥風(fēng)險評估表及創(chuàng)傷后膿毒癥集束化護理預(yù)防措施的具體內(nèi)容進行信息化編程,從而構(gòu)建創(chuàng)傷后膿毒癥護理預(yù)警評估系統(tǒng)軟件。研究結(jié)果1.明確創(chuàng)傷后膿毒癥危險因素,包括7個,即:入院SOFA評分、入院時功能障礙系統(tǒng)個數(shù)、入科24 h內(nèi)血p H值、入科24h脈壓差平均值、葡萄球菌屬感染、創(chuàng)面感染、有創(chuàng)機械通氣持續(xù)時間。預(yù)警公式為:創(chuàng)傷后膿毒癥風(fēng)險評分=入院SOFA評分+0.5×入院功能障礙系統(tǒng)個數(shù)+入科24小時內(nèi)血PH+0.5×入科24小時內(nèi)脈壓差平均值+1.5×葡萄球菌屬感染+1.5×創(chuàng)面感染+0.5×有創(chuàng)機械通氣持續(xù)時間。由ROC曲線分析得,創(chuàng)傷后膿毒癥風(fēng)險評分≥5.8即為高;颊。2.兩輪專家咨詢最終確立了基于創(chuàng)傷后膿毒癥危險因素的集束化預(yù)防護理措施包括:創(chuàng)傷后膿毒癥護理預(yù)警評估;密切監(jiān)測生命體征、PH等;細(xì)菌培養(yǎng)中的護理;創(chuàng)面感染護理;機械通氣相關(guān)感染的預(yù)防護理。3.研發(fā)了創(chuàng)傷后膿毒癥護理預(yù)警評估軟件,采用475例患者資料對其用于創(chuàng)傷患者膿毒癥預(yù)測的有效性進行驗證,結(jié)果顯示,靈敏度為75.48%、特異度為81.65%、陽性預(yù)測值為76.21%、陰性預(yù)測值為81.04%、漏預(yù)測率為10.74%(51/475)、錯預(yù)測率為10.32%(49/475)。結(jié)論創(chuàng)傷后膿毒癥的發(fā)生,創(chuàng)傷是誘因,感染是前提。本課題從感染角度出發(fā)分析創(chuàng)傷后膿毒癥的危險因素,并經(jīng)專家咨詢確立基于危險因素的集束化預(yù)防護理措施,最終研發(fā)了創(chuàng)傷后膿毒癥護理預(yù)警評估系統(tǒng)軟件,本軟件方便簡潔、對創(chuàng)傷后膿毒癥具有良好預(yù)測效果、且適宜護理人員使用,值得在臨床推廣。
[Abstract]:Objective 1. From the point of view of infection, the risk factors of sepsis in trauma patients were analyzed. 2. 2. Establish risk factors based on post-traumatic sepsis cluster preventive nursing measures. 3. Research and development of post-traumatic sepsis nursing early warning evaluation system software. Data and methods 1. The data of 227 patients with post-traumatic infection of ICU in Daping Hospital of Chongqing from 2012 to 2015 were collected. The risk factors of post-traumatic sepsis were obtained by SPSS and Excel software. The risk factors of post-traumatic sepsis were analyzed by T test and Logistic regression analysis. According to the results of Logistic analysis, the formula of post-traumatic sepsis warning was constructed, and the posttraumatic sepsis risk assessment scale. 2. 2 was constructed according to the results of ROC analysis. The data of 475 trauma patients in Daping Hospital of Chongqing from 2012 to 2016 were collected. The effectiveness of post-traumatic sepsis risk assessment table was verified by descriptive statistics and predictive value analysis, including sensitivity and specificity. Positive predictive value, negative predictive value, etc. The methods of literature reading, group discussion and clinical practice were used to draw up the items of cluster nursing measures for post-traumatic sepsis. The risk assessment table of post-traumatic sepsis and the specific contents of the post-traumatic sepsis cluster nursing prevention measures were programmed with Python software editing tool, and the pre-warning evaluation system software of post-traumatic sepsis nursing was constructed. Results 1. Seven risk factors of posttraumatic sepsis were identified, including admission SOFA score, the number of dysfunction system at admission, the blood pH value within 24 hours, the mean 24 h pulse pressure difference, the infection of staphylococcus and the infection of wound. Duration of invasive mechanical ventilation. The warning formula is as follows: posttraumatic sepsis risk score = admission SOFA score 0. 5 脳 number of admission dysfunction system within 24 hours blood PH 0. 5 脳 mean pulse pressure difference within 24 hours, mean 1.5 脳 Staphylococcus infection 1. 5 脳 wound sensation 0.5 脳 duration of invasive mechanical ventilation. According to the analysis of ROC curve, the risk score of posttraumatic sepsis 鈮,
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