糖尿病患者用药依从性是关系到血糖控制好坏的关键因素之一,提高患者的用药依从性能够提高患者的血糖达标率、减少微循环病变和慢性并发症的发生[1-2]。然而,糖尿病患者用药依从性不高仍是临床亟需重视并待以解决的重要问题。DiMatteo[3]在调查1948—1998年50年间对慢性病患者用药依从性报道的研究中得出结论,糖尿病和失眠用药的依从性在所有报道的17种常见慢性疾病中最低,糖尿病患者平均用药依从性高的仅占67.5%。Rolnick等[4]在一项对患者用药依从性的调查中发现,糖尿病患者的用药依从率仅为51%,处于所调查8个病种的较低水平。与国外的研究报道类似,我国糖尿病患者的用药依从性也不乐观。李洪超等[5]在对我国5个城市的社区2型糖尿病患者为期1年的随访调查中指出,我国社区2型糖尿病患者的用药依从率非常不理想,用药依从性差的比率高达76.5%。与此同时,我国临床研究中采用的用药依从性评估工具多为Morisky用药依从性量表,评估方法过于单一,缺乏特异性的评估方法及相互应证[6-9]。更为重要的是,我国在用药依从性评估工具的使用上缺乏针对特定人群、特定目的所采用针对性评估工具的经验;采用的用药依从性评估工具未对糖尿病患者进行信效度验证,甚至自行临时设计量表进行评价,这均会直接影响研究结果的可靠性[10-11]。目前,用药依从性评价虽然已有多种工具可供选择,如8项Morisky用药依从性量表(Eight-item Morisky Medication Adherence Scale,MMAS-8)、药物依从性报告量表(Medication Adherence Report Scale,MARS)、糖尿病自我管理行为量表(Summary of Diabetes Self Care Activities,SDSCA)等,但是并无一个跨人群、跨病种统一的金标准存在[12]。续配和服药依从性量表(Adherence to Refills and Medications Scale,ARMS)作为专门为不同文化层次的慢性病患者研发的依从性量表,已应用于高血压、糖尿病等慢病患者的依从性评估,被认为具有良好信效度,比常用的Morisky量表考察更多的依从性内容和患者反馈信息,但目前该工具仍未在中国人群中进行应用[13-16]。
除用药依从性外,对患者用药管理能力的评估和教育也正逐渐受到广泛重视。自我效能作为研究人类行为、人内在诸因素以及环境三者交互作用的认知心理学概念,在促进患者健康过程中扮演重要角色[17-18]。合理用药效能量表(Self-Efficacy for Appropriate Medication Adherence Scale,SEAMS)是基于“自我效能”理论框架开发的有关患者合理用药管理能力评估的工具,经不断改进完善后已在临床慢病药物管理中被广泛应用[19-21]。本研究目的即应用ARMS量表、MMAS-8量表及SEAMS量表同时对老年2型糖尿病患者的用药依从性及合理用药管理能力进行评估,通过建立用药依从性对合理用药效能的预测诊断,探讨ARMS量表在预测诊断老年2型糖尿病患者合理用药效能中的应用价值。
资料和方法研究对象 选择2018年7月—2019年1月于复旦大学附属华东医院内分泌病房住院的2型糖尿病老年患者(年龄≥ 65岁),均符合《中国2型糖尿病防治指南》(2017版)诊断标准,且连续服用降糖药物3个月以上。排除标准:急性感染性疾病、糖尿病酮症、糖尿病高渗昏迷急性心肌梗死、急性脑梗死、认知障碍或不能自主沟通患者,以及拒绝参与调查的患者。本研究经复旦大学附属华东医院道德伦理委员会批准(批件编号:20180076)。
调查工具 合理用药效能评价:本研究采用SEAMS量表进行评定,经作者Risser的许可后应用该量表的中文版。该量表共有13个条目,总分39分。统计学家Kelly和Cureton认为量表平均得分作为分组依据时可能存在较大系统误差(尤其是非正态分布时),故本研究中我们采用推荐的27分位法[22-23]进行分组判定。具体分组方式见“统计学方法”部分。
用药依从性评价:采用MMAS-8量表和ARMS量表进行评定[14, 24]。MMAS-8量表采用国内广泛应用的中文版MMAS-8;ARMS量表由作者Kripalani授权后使用其中文版。MMAS量表:< 6分表示依从性较差,6~7分表示依从性中等,8分以上表示依从性高;ARMS量表:≥ 16分表示依从性差。ARMS量表内容参见表 1。
No. | Item | Frequency happened | |||
None of time | Some of time | Most of time | All of time | ||
1 | How often do you forget to take your medicine? | 1 | 2 | 3 | 4 |
2 | How often do you decide not to take your medicine? | 1 | 2 | 3 | 4 |
3 | How often do you forget to get your medicine prescribed in the hospital? | 1 | 2 | 3 | 4 |
4 | How often do you run out of your medicine? | 1 | 2 | 3 | 4 |
5 | How often do you skip a dose before each visit to the doctor? | 1 | 2 | 3 | 4 |
6 | How often do you miss taking your medicine when you feel better? | 1 | 2 | 3 | 4 |
7 | How often do you miss taking your medicine when you feel sick? | 1 | 2 | 3 | 4 |
8 | How often do you miss taking your medicine when you are careless? | 1 | 2 | 3 | 4 |
9 | How often do you change the dose of your medicines to suit your needs (e.g. you may take more or less doses than you’re supposed to)? | 1 | 2 | 3 | 4 |
10 | How often do you forget to take your medicine when you should take it more than once a day? | 1 | 2 | 3 | 4 |
11 | How often do you put off going to the hospital to get your medicines prescribed because they cost too much? | 1 | 2 | 3 | 4 |
12 | How often do you plan ahead and get your medicines prescribed before they run out?a | 4 | 3 | 2 | 1 |
It is common phenomena for people to miss taking their medicine occasionally, or to take it differently than prescribed.The following is the question to ask your frequency of not taking medicine as prescribe.There is no right or wrong answer.For each question, please answer “none of the time”, “some of the time”, “most of the time”, or “all of the time”. aThis item is reverse coded. |
问卷数据质量控制与管理 患者的基本资料信息、问卷评估和得分记录由两名临床药师开展,一名临床药师完成数据收集和录入,另一名临床药师进行问卷及数据核对。所有满足入选条件患者的访视在入住内分泌科病房后的24 h之内完成,经患者知情同意后发放调查问卷并交代填写方法和规则,由患者自行填写当场交回,由临床药师检查问卷回答是否完整。如患者对问卷条目或回答有疑问,临床药师将会给予适当的解释,帮助其正确理解含义。患者实验室指标从医院HIS系统提取并录入,包括糖化血红蛋白等生化指标。
统计学方法 所有调查数据采用SPSS 23.0进行统计分析。服从正态分布的计量资料以x±s表示,非正态分布的以中位数(四分位数)即M(Q1,Q3)表示;计数资料以百分率表示;分组变量组间比较采用χ2检验。首先对患者SEAMS评分进行正态分布检验,若研究数据显示为正态分布,我们将73分位数作临界点区分合理效能是否充足;数据显示为非正态分布则采用71分位数[22]。合理用药效能与用药依从性的相关性采用Spearman相关。本研究考察的两种用药依从性评估量表(MMAS-8和ARMS)的评估目的一致且来自同一样本,所以在执行二元Logistic回归之前,首先采用方差膨胀因子(VIF)来考察该两种变量之间的共线性。若共线性检验结果提示VIF ≥ 10,则证明该两种因素间存在共线性,将按依从性量表不同分别采用二元Logistic回归分析。用药依从性预测合理用药效能的诊断模型采用受试者工作特征曲线(receiver operating characteristic curve,ROC)检验,并计算用药依从性诊断合理用药效能的特异性、敏感性及约登指数(Youden’s Index,YI),确定依从性诊断自我效能的最佳临界值。由ROC曲线产生的ARMS量表评分临界值对预测合理用药效能的验证采用Kappa一致性检验,验证人群的入选/排除标准同诊断模型建立人群,并按以下公式计算在验证人群中的特异性和敏感性:灵敏度=真阳性/(真阳性+假阴性);特异性=真阴性/(假阳性+真阴性);准确率=(真阳性+真阴性)/样本量。
结果患者基本情况 共纳入505例患者,其中女性患者275名(54.5%)。患者年龄73(68~81)岁,病程15(8~20)年,65岁之前患病374名(74.1%),平均住院10(9~12)天,降糖药物数量2(1~3)种。
合理用药效能的分组 Kolmogorov-Smirnov检验结果显示患者的SEAMS得分呈非正态分布(P < 0.001),即按Cureton建议的统计原则,采取非正态分布71分位数确定此次调查人群的合理效能分组临界点[22]。统计结果显示,患者SEAMS量表得分71分位数值38分,即SEAMS得分≥ 38分为合理用药效能充足组(效能充足组);SEAMS得分 < 38分为合理用药效能不足组(效能不足组)。
不同合理用药效能患者临床特征 效能充足组161人(31.9%)、效能不足组344人(68.1%)。两组患者在年龄差异上无统计学意义(P > 0.05),而在性别、病程、住院费用、入院前降糖药品使用类别和是否存在糖尿病周围血管病变上差异有统计学意义(P < 0.05)。
患者用药依从性量表评价结果显示,老年糖尿病患者的用药依从性不甚理想,MMAS-8量表和ARMS量表评价结果发现,分别有30.9%(156例)和64.4%(325例)的患者用药依从性差。不同合理用药效能患者组间MMAS-8量表和ARMS量表评分差异具有统计学意义(P < 0.05),表明有充足合理用药效能的患者具有更好的用药依从性(表 2)。
[n=505, n (%) or x±s] | |||||||||||||||||||||||||||||
Item | Adequate self-efficacy(n=161) | Inadequate self-efficacy(n=344) | χ2 or t value | P | |||||||||||||||||||||||||
Gender | 4.717 | 0.035 | |||||||||||||||||||||||||||
Female | 99 (36.0) | 176 (64.0) | |||||||||||||||||||||||||||
Male | 62 (27.0) | 168 (73.0) | |||||||||||||||||||||||||||
Age | 3.680 | 0.159 | |||||||||||||||||||||||||||
65-74 y | 74(28.1) | 189(71.9) | |||||||||||||||||||||||||||
75-84 y | 68(36.6) | 118(63.4) | |||||||||||||||||||||||||||
85 y or above | 19(33.9) | 37(66.1) | |||||||||||||||||||||||||||
Duration of diabetes(y) | 17.18±9.78 | 14.43±9.31 | 3.046 | 0.002 | |||||||||||||||||||||||||
MMAS-8 | 160.867 | 0.000 | |||||||||||||||||||||||||||
Low | 4(2.6) | 152(97.4) | |||||||||||||||||||||||||||
Medium | 55(27.1) | 148(72.9) | |||||||||||||||||||||||||||
High | 102(69.9) | 44(30.1) | |||||||||||||||||||||||||||
ARMS | 131.943 | 0.000 | |||||||||||||||||||||||||||
Low | 46(14.2) | 279(85.8) | |||||||||||||||||||||||||||
High | 115(63.9) | 65(36.1) | |||||||||||||||||||||||||||
Total treatment cost(Yuan) | 12 225.95±4 129.68 | 13 773.86±8 824.55 | -2.119 | 0.035 | |||||||||||||||||||||||||
HbA1c | |||||||||||||||||||||||||||||
Reach the standard | 75(31.5) | 163(68.5) | 0.028 | 0.924 | |||||||||||||||||||||||||
Not reach the standard | 86(32.2) | 181(67.8) | |||||||||||||||||||||||||||
Antidiabetic agents | 8.291 | 0.016 | |||||||||||||||||||||||||||
Oral agents | 62(25.7) | 179(74.3) | |||||||||||||||||||||||||||
Inulin preparations | 29(35.4) | 53(64.6) | |||||||||||||||||||||||||||
Oral agents+Insulin preparations | 70(38.5) | 112(61.5) | |||||||||||||||||||||||||||
Hypertension | 0.094 | 0.759 | |||||||||||||||||||||||||||
Yes | 57(32.8) | 117(67.2) | |||||||||||||||||||||||||||
No | 104(31.4) | 227(68.6) | |||||||||||||||||||||||||||
Diabetic peripheral vascular disease | 6.046 | 0.014 | |||||||||||||||||||||||||||
Yes | 153(33.6) | 303(66.4) | |||||||||||||||||||||||||||
No | 8(16.3) | 41(83.7) | |||||||||||||||||||||||||||
Diabetic peripheral neuropathy | 0.558 | 0.455 | |||||||||||||||||||||||||||
Yes | 127(32.7) | 261(67.3) | |||||||||||||||||||||||||||
No | 34(29.1) | 83(70.9) | |||||||||||||||||||||||||||
Diabetic nephropathy | 0.557 | 0.456 | |||||||||||||||||||||||||||
Yes | 48(29.6) | 114(70.4) | |||||||||||||||||||||||||||
No | 113(32.9) | 230(67.1) | |||||||||||||||||||||||||||
Diabetic retinopathy | 0.108 | 0.742 | |||||||||||||||||||||||||||
Yes | 15(34.1) | 29(65.9) | |||||||||||||||||||||||||||
No | 146(31.7) | 315(68.3) |
Spearman相关性检验表明:MMAS-8量表和ARMS量表评分与SEAMS评分均在0.01的显著性水平上(双尾)呈显著相关(MMAS-8:r=0.705,P < 0.001;ARMS:r=-0.717,P < 0.001),表明患者的用药依从性越好、合理用药效能值越高。
合理用药效能影响因素分析 影响因素共线性检验显示,MMAS-8评分与ARMS评分的方差膨胀因子VIF=56.784 > 10,表明该两种评价方法的结果存在中高等共线,因此按用药依从性量表种类分别进行二元Logistic回归影响因素分析。结果显示,MMAS-8评分与ARMS评分均是显著影响其合理用药效能的风险因素(P < 0.05),其他考察因素除性别项未有显著差异(表 3~4)。
Factors | β | SE | Wald | df | P | Exp (β) | 95% CI for EXP (β) | |
Lower bound | Upper bound | |||||||
Gender (1) | -0.595 | 0.246 | 5.849 | 1 | 0.016 | 0.551 | 0.340 | 0.893 |
Duration of diabetes | -0.018 | 0.014 | 1.600 | 1 | 0.206 | 0.982 | 0.955 | 1.010 |
Antidiabetic agents | - | - | 2.999 | 2 | 0.223 | - | - | - |
Antidiabetic agents (1) | 0.221 | 0.281 | 0.620 | 1 | 0.431 | 1.248 | 0.719 | 2.163 |
Antidiabetic agents (2) | -.419 | .369 | 1.286 | 1 | 0.257 | 0.658 | 0.319 | 1.357 |
Total treatment cost | 0 | 0 | 2.925 | 1 | 0.087 | 1.000 | 1.000 | 1.000 |
Diabetic peripheral vascular disease (1) | 0.201 | 0.514 | 0.153 | 1 | 0.696 | 1.222 | 0.447 | 3.344 |
ARMS | 0.249 | 0.026 | 94.311 | 1 | < 0.001 | 1.282 | 1.220 | 1.349 |
Constant | -3.924 | 0.687 | 32.641 | 1 | < 0.001 | 0.020 | - | - |
Reference group for categorical variances:Gender:Male; Antidiabetic agents:Oral hypoglycemic agents combined with insulin preparation; Diabetic peripheral vascular disease or not: With peripheral vascular disease. |
Factors | β | SE | Wald | df | P | Exp (β) | 95% CI for EXP (B) | |
Lower bound | Upper bound | |||||||
Gender (1) | -0.549 | 0.242 | 5.157 | 1 | 0.023 | 0.578 | 0.360 | 0.928 |
Duration of diabetes | -0.017 | 0.014 | 1.587 | 1 | 0.208 | 0.983 | 0.956 | 1.010 |
Antidiabetic agents | - | - | 3.399 | 2 | 0.183 | - | - | - |
Antidiabetic agents (1) | 0.244 | 0.277 | 0.773 | 1 | 0.379 | 1.276 | 0.741 | 2.197 |
Antidiabetic agents (2) | -0.423 | 0.362 | 1.362 | 1 | 0.243 | 0.655 | 0.322 | 1.333 |
Total treatment cost | 0 | 0 | 2.667 | 1 | 0.102 | 1.000 | 1.000 | 1.000 |
Diabetic peripheral vascular disease (1) | 0.262 | 0.501 | 0.274 | 1 | 0.601 | 1.300 | 0.487 | 3.469 |
MORISKY | -1.417 | 0.148 | 91.348 | 1 | < 0.001 | 0.242 | 0.181 | 0.324 |
Constant | 10.444 | 1.217 | 73.613 | 1 | < 0.001 | 34 348.734 | - | - |
Reference group for categorical variances:Gender: Male; Antidiabetic agents: Oral hypoglycemic agents combined with insulin preparation; Diabetic peripheral vascular diseaseor not: With peripheral vascular disease. |
ROC检验 ROC检验结果(图 1)显示,MMAS-8评分缺乏预判目标患者存在合理用药效能不足所具有的特异性和敏感性(AUC=0.155;P < 0.001;95%CI:0.121~0.189),但ARMS评分具有较高的特异性和敏感性(AUC=0.851;P < 0.001;95%CI:0.818~0.885)。YI计算结果表明,ARMS量表评分等于16时达到YI最大值0.582,同时敏感性和特异性分别为80.5%和77.6%,可以作为最佳预测诊断临界值。该值也与ARMS量表分组临界值一致(表 5)。表明ARMS量表比MMAS-8量表更适合于糖尿病患者的用药依从性评价。
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图 1 受试者工作曲线结果 Fig 1 Result of receiver operating characteristic curve |
(n=505) | |||||||||||||||||||||||||||||
Positive if greater than or equal to | Sensitivity | 1-Specificity | YI | ||||||||||||||||||||||||||
≥ 11.0 | 1.000 | 1.000 | 0.000 | ||||||||||||||||||||||||||
13.0 | 0.860 | 0.323 | 0.537 | ||||||||||||||||||||||||||
14.5 | 0.828 | 0.286 | 0.543 | ||||||||||||||||||||||||||
15.5 | 0.811 | 0.286 | 0.525 | ||||||||||||||||||||||||||
16.5(1) | 0.805 | 0.224 | 0.582 | ||||||||||||||||||||||||||
17.5 | 0.797 | 0.224 | 0.573 | ||||||||||||||||||||||||||
19.0 | 0.683 | 0.106 | 0.578 | ||||||||||||||||||||||||||
20.5 | 0.608 | 0.081 | 0.527 | ||||||||||||||||||||||||||
21.5 | 0.602 | 0.081 | 0.521 | ||||||||||||||||||||||||||
22.5 | 0.596 | 0.068 | 0.528 | ||||||||||||||||||||||||||
23.5 | 0.573 | 0.068 | 0.504 | ||||||||||||||||||||||||||
25.0 | 0.442 | 0.025 | 0.417 | ||||||||||||||||||||||||||
26.5 | 0.378 | 0.025 | 0.353 | ||||||||||||||||||||||||||
27.5 | 0.288 | 0.012 | 0.275 | ||||||||||||||||||||||||||
28.5 | 0.282 | 0.012 | 0.270 | ||||||||||||||||||||||||||
29.5 | 0.244 | 0.012 | 0.232 | ||||||||||||||||||||||||||
30.5 | 0.224 | 0 | 0.224 | ||||||||||||||||||||||||||
31.5 | 0.221 | 0 | 0.221 | ||||||||||||||||||||||||||
32.5 | 0.177 | 0 | 0.177 | ||||||||||||||||||||||||||
34.0 | 0.151 | 0 | 0.151 | ||||||||||||||||||||||||||
35.5 | 0.128 | 0 | 0.128 | ||||||||||||||||||||||||||
37.0 | 0.108 | 0 | 0.108 | ||||||||||||||||||||||||||
38.5 | 0.084 | 0 | 0.084 | ||||||||||||||||||||||||||
40.0 | 0.070 | 0 | 0.070 | ||||||||||||||||||||||||||
43.0 | 0.044 | 0 | 0.044 | ||||||||||||||||||||||||||
46.0 | 0.032 | 0 | 0.032 | ||||||||||||||||||||||||||
47.5 | 0.026 | 0 | 0.026 | ||||||||||||||||||||||||||
49.0 | 0 | 0 | 0 | ||||||||||||||||||||||||||
(1)Represent best cutoff value of ARMS. |
ARMS评分对合理用药效能的预测诊断验证 访视2019年1-3月上述内分泌病房入院患者50名作为该风险预测模型的验证样本,检验风险预测效能。该验证样本患者年龄为72(68~79)岁,其中实际效能充足组27名,效能不足组23名。风险预测模型验证结果显示判断真阳性患者26名,假阳性患者6名;真阴性患者17名,假阴性患者1名。因此ARMS评分对该验证人群合理用药效能的预测实际灵敏度为96.3%、特异性为73.9%、准确率为86.0%。Kappa一致性显著性检验结果为κ=0.714(P < 0.01),表明该风险预测模型与实际情况存在较高的一致性。
讨论本次调查研究显示,采用MMAS-8量表和ARMS量表进行用药依从性评估后,分别有30.9%和64.4%患者的用药依从性差,表明老年2型糖尿病患者的用药依从性不容乐观,同时评估结果的差异可能由于两种量表的编制策略不同造成。
MMAS-8量表是Morisky等开发出的用药依从性评估量表已在全球广泛使用并译成多个版本[25-28]。MMAS-8量表评估简易、快速,回答多是二分类的,可以迅速判断患者的态度和意见,将患者按依从性程度区分为低、中、高3组,但不能区分患者对各题项态度的差别,回答也没有进一步阐明理由的机会,这样就造成调查者对患者的用药情况了解不够深入,形成评估误差。ARMS量表作为专门为不同文化层次慢性病患者研发的依从性量表也已在多个慢病研究以及多个国家中得到应用[13, 15-16]。ARMS量表采用了社会科学研究中常用的李克特分级量表,为了减少中立效应和社会期许效应,该量表设置为4级量表并增加了反向题,这样更方便研究者对患者态度的判断和就调查问题的互动,有利于对患者的用药情况、态度、管理方式等进行深入了解,从而体现比MMAS-8量表更多的患者反馈信息[13, 16]。因此以上2种用药依从性量表在评估模式和实施中的不同是造成本次研究中依从性结果差异的主要原因。
合理用药效能与糖尿病患者的疾病控制与自我管理等有密切联系[29-30],也与患者的用药依从性显著相关[19-21]。本研究中单因素分析结果提示,具备充足合理用药效能的病程更长、用药方案更复杂、依从性更好、存在周围血管病变合并症并且住院费用更低。这表明2型糖尿病作为起病隐蔽、平日症状不明显的慢性疾病,多数患者在疾病初始期间并未重视治疗;但随着疾病的不断进展、治疗方案不断增强以及糖尿病并发症的出现,患者才开始对疾病的管理加以重视,这一结果也与国外文献报道的一致[31]。二元Logistic回归分析进一步证实,在控制了其他干扰因素的情况下,患者的用药依从性仍是与合理用药效能显著相关的风险因素。
为了更好地检验两种用药依从性量表在用药管理能力方面评估能力,本研究进一步采用ROC曲线检验,考察对合理用药效能的预测能力。结果显示,ARMS评分诊断目标患者存在合理用药效能不足具有更高的的特异性和敏感性(AUC=0.851,P < 0.001,95%CI:0.818~0.885);相反,MMAS-8评分却未达到诊断应具有的特异性和敏感性(AUC=0.155,P < 0.001,95%CI:0.121~0.189)。而且ARMS量表的诊断值与该量表开发时设定的用药依从性分组值完全一致,这证明该量表可以表现出优于MMAS-8量表的对目标患者的合理用药管理能力的评估价值。不仅如此,在本研究后续验证人群的评估中,采用ARMS量表诊断患者是否存在合理用药效能不足可以达到实际灵敏度96.3%、特异性73.9%、准确率86.0%,并可通过Kappa一致性检验验证诊断值和实际测定值的一致性。
本研究从患者合理用药管理效能的角度,证明了MMAS-8量表和ARMS量表评分与SEAMS评分呈显著相关,且老年2型糖尿病患者的用药依从性越佳,其合理用药效能值越高。用药依从性作为患者合理用药效能的影响因素,在二元Logistic回归中也进一步得到证实。ROC曲线检验结果证明,ARMS量表对诊断患者合理用药效能状态具有临床意义的敏感性和特异性,展现出比MMAS-8更有价值的用药管理能力评估素质,可以作为老年2型糖尿病患者用药依从性和合理用药效能评估的理论参考。更为重要的是,ARMS量表可以成为临床药师工作中进行用药教育与用药管理能力评估时的新工具,会让更多患者受益于不断丰富和完善的临床药学服务。
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