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儿童Ⅱ期人工晶状体植入术后青光眼相关不良事件影响因素与预测的研究进展

Research progress on associated factors and prediction of glaucoma-related adverse events following secondary intraocular lens implantation in pediatric eyes

来源期刊: 眼科学报 | 2024年8月 第39卷 第8期 416-423 发布时间:2024-08-28 收稿时间:2024/10/15 16:48:12 阅读量:336
作者:
关键词:
儿童白内障Ⅱ期IOL植入术术后并发症青光眼相关不良事件多因素回归模型
pediatric cataract secondary IOL implantation postoperative complications glaucoma-related adverse events multifactorial regression model
DOI:
10.12419/24070109
收稿时间:
2024-07-01 
修订日期:
2024-07-28 
接收日期:
2024-08-13 
儿童白内障是全球范围内可治疗儿童盲症的主要原因之一。对于这些患儿而言,手术是恢复或保护视力的主要方法。然而,手术后的并发症,特别是青光眼相关不良事件(glaucoma-related adverse events, GRAEs),常常成为导致儿童二次致盲的主要原因,这引起了眼科医疗领域的广泛关注。文章综述了儿童Ⅱ期人工晶状体植入术后GRAEs的影响因素,包括手术设计、眼部解剖特征、其他眼部发育异常和全身疾病等。手术设计中是否植入人工晶状体(intraocular lens,IOL)以及植入的时机和位置都对GRAEs的发生有显著影响。此外,眼部解剖特征如角膜直径、眼轴长度、前房深度、中央角膜厚度和术前晶状体厚度等,也是影响GRAEs发生的重要因素。同时,其他眼部发育异常和全身疾病,如先天性无虹膜、先天性风疹综合征等,也会增加儿童白内障术后青光眼的发生率。文章还总结了预测GRAEs的方法,并推荐使用Cox回归模型建立预测模型。这种模型可以有效地预测儿童Ⅱ期IOL植入术后在特定时间段内发展为GRAEs的概率,从而为早期识别GRAEs高危儿童提供了重要的借鉴。通过对GRAEs影响因素的深入分析和预测模型的建立,文章旨在帮助眼科医生更好地理解GRAEs的发生机制,并在手术前对患儿进行风险评估,从而选择最佳的手术方案和预防措施。这对于改善患儿的术后恢复、减少并发症、保护视功能具有重要的临床意义。
Pediatric cataract is one of the leading causes of treatable childhood blindness worldwide. For these children, surgery is the primary method to restore or preserve vision. However, postoperative complications, particularly glaucoma-related adverse events (GRAEs), often become the main reason for secondary blindness in children, attracting widespread concern in the field of ophthalmology. This study reviews the impact factors of glaucoma-related adverse events after secondary intraocular lens (IOL) implantation in children, including surgical design, ocular anatomical characteristics, other ocular developmental abnormalities, and systemic diseases. Whether to implant an IOL in the surgical design and the timing and positioning of the implantation have a significant impact on the occurrence of GRAEs. In addition, ocular anatomical characteristics, such as corneal diameter, axial length, anterior chamber depth, central corneal thickness, and preoperative lens thickness, are also important factors affecting the occurrence of GRAEs. At the same time, other ocular developmental abnormalities and systemic diseases, such as congenital aniridia and congenital rubella syndrome, also increase the incidence of glaucoma after pediatric cataract surgery. The article also summarizes methods for predicting GRAEs and recommends using the Cox regression model to establish a predictive model. This model can effectively predict the probability of children developing GRAEs after secondary IOL implantation within a specific time period, providing an important reference for the early identification of high-risk children for GRAEs. Through in-depth analysis of the impact factors of GRAEs and the establishment of predictive models, the article aims to help ophthalmologists better understand the mechanisms of GRAEs and assess the risks of children before surgery, thereby selecting the best surgical plan and preventive measures. This is of great clinical significance for improving postoperative recovery in children, reducing complications, and protecting visual function.

文章亮点

1. 关键发现

• 文章推荐使用 Cox 回归模型建立预测模型,以预测儿童Ⅱ期人工晶状体植入术后青光眼相关不良事件的风险,对于早期识别高危儿童,从而及时进行临床干预以改善视功能预后具有重要意义。

2. 已知与发现

• 青光眼相关不良事件(glaucoma-related adverse events, GRAEs) 作为儿童白内障术后并发症之一,GRAEs 是术后二次致盲的首要原因。已知的相关风险因素包括手术设计、眼部解剖特征、其他眼部发育异常和全身疾病等因素有关。文章同时总结了预测 GRAEs 的方法,并推荐使用 Cox 回归模型建立预测模型,这在以往的研究中可能未被充分探讨或推荐。

3. 意义与改变

• 文章通过综述现有的研究,提高了医疗专业人员对儿童白内障手术后 GRAEs 发生风险因素的认识;通过推荐使用 Cox回归模型建立预测模型,可以帮助医生做出更好的临床决策,比如选择最佳的手术时机和方法,以及确定需要密切监测的高风险患者;最后,文章的发现可能会激发未来在儿童白内障手术和青光眼预防领域的进一步研究,特别是在开发和验证预测模型方面。

       儿童白内障是全球儿童盲的主要原因之一。2岁以下的儿童白内障患者的手术通常分期进行:Ⅰ期摘除白内障,解除形觉剥夺;眼球发育相对接近成熟状态后,Ⅱ期植入人工晶状体(intraocular lens,IOL)以矫正屈光不正。青光眼相关不良事件(glaucoma-related adverse events, GRAEs)是儿童白内障术后严重并发症之一。据报道,6%~50% 的儿童在手术后发生青光眼[1-3],从白内障摘除手术到GRAEs的发病时间平均为(16.96±12.02)个月[4],且随着术后时间的增加,累积发生率逐渐升高[5]。GRAEs起病隐匿,如未被及时发现与干预,可对视功能造成不可逆的损伤,及时识别发生GRAEs的高危人群以及预判其发生的高危时间具有重要临床意义。
       随着手术技术的进步,儿童Ⅰ期白内障摘除术后,无晶状体眼继发性青光眼的发生率大大降低,Ⅱ期IOL植入术后的GRAEs成为眼科医生关注的主要类型[6-8]。既往文献报道了Ⅱ期IOL植入术后的GRAEs的可能相关因素[6-7, 9],但目前尚缺乏风险预测模型。进一步明确儿童Ⅱ期IOL植入术后GRAEs的影响因素,建立该并发症的个性化预测模型,及时甄别高危人群,对患儿的及时治疗和预后的改善至关重要。

1 儿童白内障术后青光眼类型与相关定义的演变

       既往研究对儿童白内障手术后青光眼的定义不尽相同[10-14]。一些研究仅根据眼压升高这个单一的指标诊断青光眼,并不考虑眼部结构是否发生改变[12,15-16],而且不同研究对于高眼压的界定值也存在各自的标准[11-12,16]
       1960年Scheie将针头抽吸术用于治疗儿童白内障,但是患儿术后经常出现瞳孔阻滞合并房角关闭的情况,使得青光眼成为儿童白内障摘除手术后的常见问题[17]。学者们也发现,部分术后出现青光眼的患儿表现为前房深、虹膜平坦、房角宽等“安静的特例”[10]
       20 世纪70 年代末,晶状体 Scheie 抽吸法联合后囊膜切开术和前段玻璃体切割术逐渐成为治疗儿童白内障最常用的术式[18-19]。手术方法的改变,使医生能在术中能够更为有效地去除晶状体、囊膜的残留和前部玻璃体;同时,术后抗炎药物的合理使用进一步降低了术后炎性反应和瞳孔阻滞的发生率,减少了术后继发性青光眼的发生[5-6,19]。Egbert团队[11]对接受白内障摘除联合玻璃体切割术的患儿进行了至少 5年的前瞻性观察,得出以下结论:1)先天性白内障术后青光眼:眼压 > 21 mmHg(眼睑未受压迫情况下,使用 Goldmann,Tonopen 或气压计所测得的眼压,1 mmHg=0.133 kPa),视盘的杯盘比 > 0.5,或视盘之间的不对称 ≥ 0.2;2)先天性白内障术后高眼压:眼压 >21 mmHg,但无上述青光眼视神经异常表现。然而,在不同研究中,诊断儿童白内障术后青光眼的眼压阈值不一致[11-12,16]。Sanjay等[12]基于无晶状体眼患儿的数据将术后青光眼定义为眼压 > 25 mmHg超过1次。Peter研究团队将白内障摘除术后至少2次眼压≥ 26 mmHg(在临床或麻醉诱导下用压平眼压计、Puff眼压计或Tonopen测得,视神经、房角镜和视野评估等均未纳入)定义为青光眼[16]
       美国的婴儿无晶状体眼治疗研究小组(the Infant Aphakia Treatment Study, IATS)通过大型前瞻性队列研究对白内障患儿术后青光眼和可疑青光眼的发病率进行研究,并将视神经结构的变化纳入术后青光眼的诊断标准中,在世界青光眼协会儿童青光眼第9次共识中提出了GRAEs的概念,这一定义目前被广为采纳。具体诊断标准如下:1)青光眼:1只眼眼压 >21 mmHg,且有以下1个或以上的解剖学改变:a.角膜直径增加;b. 双眼不对称变性近视伴角膜直径和或眼轴的增加;c. 视杯直径进行性增大,杯盘比增加≥0.2;d. 必须通过手术才能控制眼压。2)可疑青光眼:停用局部糖皮质激素(激素)后连续2次眼压 > 21 mmHg,或使用抗青光眼药物控制眼压,但无上述青光眼的任何解剖改变[13]
       儿童青光眼研究网络(the Childhood Glaucoma Research Network, CGRN)在GRAEs基础上对诊断方法进行补充并形成对儿童青光眼和可疑青光眼分类的国际共识[14]。儿童白内障术后继发青光眼:满足以下 2 项或以上:1)眼压变化,眼压 >21 mmHg;2)视野改变:出现与青光眼视神经病变一致的视野缺损改变;3)眼轴长度改变,进展性近视或近视漂移,伴随眼球发育的异常增长;4)角膜改变,Haab纹出现,以及角膜直径增加(新生儿 > 11 mm,1岁内 > 12 mm,大于1岁 >13 mm);5)视神经变化,视杯与杯盘直径比(cup-disc ratio, C/D)进行性增大,双眼 C/D 差距 ≥ 0.2 及伴随视盘边缘变薄。疑似青光眼,至少需要满足以下条件之一:1)眼压,2次以上测得 > 21 mmHg;2)视野,青光眼的可疑视野缺损;3)眼轴长度,眼压正常时眼轴长度增加;4)角膜,眼压正常时角膜直径增大;5)视神经,青光眼的可疑视盘外观。

2 儿童白内障术后青光眼相关不良事件的影响因素研究现状

       既往研究表明,儿童白内障术后GRAEs的发生可能与手术设计、眼部解剖特征、其他眼部发育异常和全身疾病等因素有关。

2.1 手术设计

       2.1.1 是否植入IOL及植入IOL的时机
       多数研究推荐2岁以上儿童采用联合手术,即白内障摘除联合Ⅰ期IOL植入术。不建议出生6个月以内的患儿植入IOL[20-23],对于6个月~2岁的患儿,是否植入IOL仍需谨慎[6, 24-25]。一项meta分析纳入了892眼,结果发现2岁以下的双眼白内障患儿,联合I期IOL植入术可降低继发青光眼的风险;而单眼白内障患儿在Ⅰ期IOL植入术后继发的青光眼,与无晶状体眼和Ⅱ期IOL植入术后的发生率没有显著差异[6]。目前大部分GRAEs研究对象为I期白内障摘除联合植入IOL和I期单纯行白内障摘除人群[2,16,24-25],而Ⅱ期IOL植入人群[7-8]的GRAEs相关研究极少,亟需针对这个群体开展研究。
       2.1.2 IOL植入位置
       Liu等[13]对儿童Ⅱ期IOL植入的前瞻性队列研究发现,与IOL睫状沟植入相比,囊袋内植入IOL对GRAEs具有较强的保护作用(HR=0.08,95%CI 0.01~0.53,P=0.009)。这一研究提供了较高等级的证据,为儿童白内障手术方案制定提供了可靠的指导。
       2.1.3 手术年龄
       对于儿童白内障摘除手术年龄是否会影响GRAEs的发生,目前研究仍存在争议。有研究表明,不论是否I期植入IOL,手术年龄小都是白内障术后GRAEs的风险因素[26-27]。但另有研究发现,对于行分期手术的I期白内障摘除的患儿,白内障摘除的手术年龄并非GRAEs的影响因素,原因可能是相关研究纳入患儿的年龄范围窄(小于24个月)或目前的儿童白内障术式(后囊膜切开术、玻璃体前切割术)降低了术后炎性反应[4]。Zhao等[28]研究发现,白内障摘除年龄对于I期白内障摘除和Ⅱ期IOL植入术后GRAEs无显著影响,但该研究样本量较小,研究结论仍需扩大样本量进行验证。Liu等[7]发现Ⅱ期IOL植入时年龄较大(HR=1.03,95%CI 1.00~1.07,P=0.034)的患者术后可能更易发生GRAEs。

2.2 眼部解剖特征

       2.2.1 小角膜或短眼轴
       Sharon团队[21]发现与小角膜相关的单眼白内障患者的GRAEs风险增加,提示与其他青光眼风险预测指标(例如眼轴)相比,角膜直径(作为反映眼前段发育状态的指标之一)或许对GRAEs的发生有着更为重要的影响。Kim等[29]发现,眼轴长度与青光眼发展有关(OR=0.364, P=0.025),而Wang等[4]发现,排除小眼球患者后,眼轴长度与青光眼发生无相关性。目前研究仍难以明确对于儿童白内障术后GRAEs、小角膜或短眼轴是否增加其发生的风险;也尚未明确角膜直径和眼轴长度两者之间是否存在相互影响作用。
       2.2.2 前房容积、前房深度、中央角膜厚度和术前晶状体厚度
       前房容积小、前房深度浅、中央角膜厚、晶状体较薄可能更易发生GRAEs[4, 28]。对于疑似青光眼患者,其平均角膜厚度更大(660 mm vs. 612 mm, P ¼ =0.003 6)[25],这提示我们,中央角膜厚度不仅可影响眼压测量,也可能是儿童白内障术后发生GRAEs的影响因素。

2.3 其他眼部发育异常和全身疾病等因素

       除小角膜和短眼轴外,其他眼部发育异常(如先天性无虹膜、虹膜脉络膜缺损和永存胚胎血管)和全身疾病(如先天性风疹综合征、Lowe综合征等)可能会增加儿童白内障术后青光眼发生率[27, 30-31]。儿童白内障家族史也被认为是GRAEs的危险因素[4,28]。所以术前需要全面检查患儿眼部和全身状况,并收集其家族史。
       综上所述,许多学者对儿童白内障术后GRAEs发生的影响因素进行了探索,但是由于各研究在研究对象、治疗方式、随访时长等因素中的差异,不同研究间得到的结论也不一致,且未能综合评估各项影响因素以预测特定患儿发生GRAEs的风险,对临床的指导意义有限。为甄别儿童白内障术后发生GRAEs的高危人群,及时进行治疗以改善视功能预后,亟须建立具有良好敏感性与准确性的GRAEs预测模型以进行个体的发病风险预测,指导临床决策。

3临床预测模型的类型选择及其在眼科应用

       临床预测模型(Clinical Prediction Models),是指利用模型预测个体患者当前或未来特定时间的患病概率,目的是基于患者诊断或预后的信息,帮助医生和患者做出更好的检测和治疗决策,或为治疗制定风险分层[32-33]
       研究的目的是建立模型用于预测儿童Ⅱ期IOL植入术后在特定时间段内发展为GRAEs的概率,即建立预后预测模型。建立预后预测模型的常用方法为Logistic和Cox回归分析,新兴的人工智能(artificial intelligence, AI)模型也正逐渐应用于临床。需根据以上3种方法的特点选择合适模型进行GRAEs风险估计,现总结如下。

3.1 Logistic回归模型

       作为分类模型,该模型能根据给定的自变量数据集来估计事件的发生概率[34-35]。主要用途及优势[32, 36]:1)用于探索某疾病发生的危险因素并分析其作用大小;2)预测短期(如30 d)内疾病或事件发生的概率。局限性:1)仅能给出随访终点(短期)时的发生概率,无法利用发病时间的信息;2)因变量数据不允许存在删失值。目前Logistic回归模型多应用于眼底病方向,包括预测糖尿病视网膜病变及黄斑水肿的发生风险、视力损害因素探究等[37-40]。其他研究方向还包括白内障的影响因素[41-42]及术后并发症的危险因素探究[42]、青光眼手术预后[42]、近视进展危险因素探究及近视防控[40,43-44]等。

3.2 Cox回归模型

       该模型以生存结局和生存时间为因变量,可同时分析众多因素对生存期的影响[34-35]。主要用途及优势[32]:1)能够充分利用发病时间反映的信息;2)长期预测分析,预测结局在一定时间(如10年)内的风险概率;3)Cox回归因变量允许存在删失值。局限性:Cox模型必须满足比例风险的假设[34-35]。Cox回归模型多应用在儿童白内障手术决策[8]、术后并发症及其相关因素[45-46]的探究中,许多国内外的儿童白内障队列研究便是采取该模型进行危险因素探索。此外,Cox模型还应用于研究青光眼预后及危险因素[47]、近视的预测[44] 、眼病与全身性疾病关联[48]等方面。

3.3 人工智能模型

       AI算法以机器学习与深度学习为主,可系统性处理并学习外部数据以实现特定任务。主要用途及优势[49]:1)进行自然语言图像识别、大数据统计分析、专家决策系统等;2)利用图像及其他生物学参数实现较高准确度的疾病诊断。局限性[50]:1)对样本量要求极高;2)不透明性、不确定性,预测效果可能不稳定。在儿童白内障方面,AI模型可应用于婴幼儿视功能智能评估[51],辅助婴幼儿白内障诊疗决策[52]、婴幼儿白内障术后并发症(包括高眼压)预测等方面[52]。此外,AI模型还广泛应用于评估晶状体年龄以预测重大疾病发生风险[53]、诊断青光眼[54]和高度近视合并青光眼[55]、预测青光眼疾病进展[56]、基于眼底彩照生成眼底自发荧光图像[57]、辅助缺血性视网膜疾病全程诊疗[58] 、预测糖尿病视网膜病变、年龄相关性黄斑变性[59]等方面。
       综上所述,基于儿童白内障罕见病队列的数据特点,因其无法满足AI模型的极大样本量要求,且队列数据存在删失,为充分利用结局信息进行GRAEs发生时间及风险估计,最终建议选择Cox模型作为儿童白内障队列建立GRAEs预测模型的方法。

利益冲突

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1、广东省自然科学基金(2023A1515011102);广州市院校联合项目 (2023A03J0174;2023A03J0188)。
This work was supported by the Natural Science Foundation of Guangdong Province, China(2023A1515011102) and the grant from the Municipal Government and School (Hospital) Joint Funding Program of Guangzhou (2023A03J0174, 2023A03J0188).()
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