Pediatrics Department, Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950, Spain.
Department of Genetic Medicine, Pediatric Institute of Rare Diseases (IPER), Hospital Sant Joan de Déu, Esplugues de Llobregat, 08950, Spain.
Eur J Med Genet. 2023 Nov;66(11):104858. doi: 10.1016/j.ejmg.2023.104858. Epub 2023 Sep 26.
The objective of this study was to develop a simple tool for general physicians to promptly identify and refer pediatric patients with a higher probability of having a genetic condition.
This retrospective, descriptive study was conducted at a tertiary pediatric hospital's Clinical Genetics Unit from June 2019 to January 2020. We included patients under 18 years of age who visited the unit, excluding those without genetic testing. Epidemiological, clinical, and genetic variables were collected from electronic medical records. The primary outcome was the diagnosis of a genetic condition based on genetic testing.
Among 445 patients, 304 were included; 163 (53.6%) were male, and mean age was 7.4 years (SD 5.1 years). A genetic condition was diagnosed in 139 patients (45.7%). Using a multiple logistic regression model, five variables significantly contributed to reaching a diagnosis: suspected diagnosis at referral (OR 3.45, P < 0.001), short stature (OR 3.11, P < 0.001), global developmental delay/intellectual disability (OR 2.65, P < 0.001), dysmorphic craniofacial features (OR 1.99, P = 0.035), and multiple congenital anomalies (OR 2.54, P = 0.033). The association strength (OR) increased when these variables were paired with each other. The study's findings are presented in the form of a triangle, known as the Clinical Genetics Assessment Triangle (CGAT), which summarizes the results. A decision tree model is applied to guide clinical department referrals based on the affected sides of the triangle.
The CGAT has the potential to enable general physicians to promptly identify pediatric patients with an increased probability of having a genetic condition.
本研究旨在开发一种简单的工具，以便普通医生能够迅速识别和转介具有更高遗传疾病可能性的儿科患者。
本回顾性描述性研究于 2019 年 6 月至 2020 年 1 月在一家三级儿科医院的临床遗传学科进行。我们纳入了在该科就诊的 18 岁以下患者，但不包括未进行基因检测的患者。从电子病历中收集了流行病学、临床和遗传变量。主要结局是根据基因检测诊断出遗传疾病。
在 445 名患者中，有 304 名患者符合纳入标准；其中 163 名（53.6%）为男性，平均年龄为 7.4 岁（标准差 5.1 岁）。在 139 名患者（45.7%）中诊断出遗传疾病。使用多因素逻辑回归模型，有五个变量对诊断结果有显著影响：转诊时的疑似诊断（比值比 3.45，P<0.001）、身材矮小（比值比 3.11，P<0.001）、全面发育迟缓/智力残疾（比值比 2.65，P<0.001）、颜面畸形（比值比 1.99，P=0.035）和多发先天性畸形（比值比 2.54，P=0.033）。当这些变量相互配对时，关联强度（比值比）会增加。研究结果以三角形的形式呈现，称为临床遗传学评估三角形（CGAT），总结了结果。应用决策树模型根据三角形的受影响侧指导临床科室转诊。
CGAT 有可能使普通医生能够迅速识别出患有遗传疾病可能性增加的儿科患者。
