目的 考察金黃色葡萄球菌耐藥率與抗菌藥物使用強(qiáng)度（AUD）的相關(guān)性，建立可用于預(yù)測(cè)金黃色葡萄球菌耐藥率的回歸模型。方法 回顧性分析2014年第1季度至2020年第4季度信陽(yáng)市中心醫(yī)院金黃色葡萄球菌耐藥率監(jiān)測(cè)數(shù)據(jù)以及同期抗菌藥物AUD數(shù)據(jù)。采用2014年第1季度至2019年第4季度數(shù)據(jù)作為試驗(yàn)樣本數(shù)據(jù)，采用線性相關(guān)性分析法分析兩者的相關(guān)性。以耐藥率為因變量，抗菌藥物AUD為自變量，對(duì)相關(guān)性顯著的變量建立線性回歸模型。以2020年第1季度至2020年第4季度數(shù)據(jù)為考核樣本，應(yīng)用所建立的回歸模型預(yù)測(cè)金黃色葡萄球菌耐藥率，并與同期耐藥率實(shí)際值對(duì)比以驗(yàn)證模型預(yù)測(cè)的有效性。結(jié)果 金黃色葡萄球菌對(duì)大部分抗菌藥物耐藥率隨時(shí)間呈下降趨勢(shì)（P<0.05），對(duì)紅霉素和阿奇霉素耐藥率隨時(shí)間無(wú)顯著變化趨勢(shì)。金黃色葡萄球菌對(duì)慶大霉素耐藥率與頭孢唑林AUD呈正相關(guān)（r=0.431，P=0.036），與阿奇霉素AUD呈正相關(guān)（r=0.523，P=0.009），與左氧氟沙星AUD呈正相關(guān)（r=0.606，P=0.002）。對(duì)左氧氟沙星耐藥率與頭孢唑林AUD呈正相關(guān)（r=0.447，P=0.029），與左氧氟沙星AUD呈正相關(guān)（r=0.482，P=0.017）。耐甲氧西林金黃色葡萄球菌（MRSA）檢出率與左氧氟沙星AUD呈正相關(guān)（r=0.639，P=0.001）。分別對(duì)慶大霉素耐藥率、左氧氟沙星耐藥率、MRSA檢出率建立一元或多元線性回歸模型，結(jié)果顯示模型均通過(guò)顯著性檢驗(yàn)（F₁=7.416，P₁=0.004；F₂=6.317，P₂=0.007；F₃=11.65，P₃=0.002）。將2020年第1季度至2020年第4季度抗菌藥物AUD數(shù)據(jù)代入相應(yīng)的回歸模型，得到的耐藥率預(yù)測(cè)值在實(shí)際值上下浮動(dòng)，耐藥率實(shí)際值均處于95%預(yù)測(cè)區(qū)間以內(nèi)。結(jié)論 信陽(yáng)市中心醫(yī)院金黃色葡萄球菌耐藥率與抗菌藥物AUD存在相關(guān)性，所建立的線性回歸模型可初步反映兩者的量化關(guān)系，可對(duì)耐藥率進(jìn)行有效預(yù)測(cè)。

Objective The correlation between Staphylococcus aureus drug resistance rate and antibiotic use intensity (AUD) was investigated, and a regression model for predicting staphylococcus aureus drug resistance rate was established. Methods The monitoring data of Staphylococcus aureus drug resistance rate in Xinyang Central Hospital from the first quarter of 2014 to the fourth quarter of 2020 and AUD data of antibiotics in the same period were retrospectively analyzed. The data from the first quarter of 2014 to the fourth quarter of 2019 were used as the test sample data, and the correlation between them was analyzed by linear correlation analysis. Taking drug resistance rate as dependent variable and antibiotic AUD as independent variable, a linear regression model was established for variables with significant correlation. Taking the data from the first quarter of 2020 to the fourth quarter of 2020 as the evaluation sample, the established regression model was used to predict the drug resistance rate of Staphylococcus aureus, and compared with the actual drug resistance rate of the same period to verify the validity of the model prediction. Results The drug resistance rates of Staphylococcus aureus to most antibacterial drugs showed a decreasing trend over time (P < 0.05), while the drug resistance rates to erythromycin and azithromycin showed no significant trend over time. The drug resistance rate of Staphylococcus aureus to gentamicin was positively correlated with cefazolin AUD (r=0.431, P=0.036), azithromycin AUD (r=0.523, P=0.009), levofloxacin AUD (r=0.606, P=0.002). The drug resistance rate to levofloxacin was positively correlated with cefazolin AUD (r=0.447, P=0.029), and with levofloxacin AUD (r=0.482, P=0.017). The detection rate of methicillin- resistant Staphylococcus aureus (MRSA) was positively correlated with levofloxacin AUD (r=0.639, P=0.001). Unitary or multiple linear regression models were established for gentamicin resistance rate, levofloxacin resistance rate, and MRSA detection rate, respectively, and the results showed that the models passed the significance test (F₁=7.416, P₁=0.004; F₂=6.317, P₂=0.007; F₃=11.65, P₃=0.002). The AUD data of antibiotics from the first quarter of 2020 to the fourth quarter of 2020 were substituted into the corresponding regression model, and the predicted values of drug resistance rate obtained fluctuated around the actual values, and the actual values of drug resistance rate were all within the 95% prediction range. Conclusion The drug resistance rate of Staphylococcus aureus in Xinyang Central Hospital was correlated with AUD. The established linear regression model could preliminarily reflect the quantitative relationship between the two and effectively predict the drug resistance rate.

R978.1