虫增长的多变量预测模型:系统审查和批判性评估
Kristian Havsed1,2,3, Gunnel Hänsel Petersson4, Per-Erik Isberg5
1Department of Pediatric Dentistry, Institute for Postgraduate Dental Education, Jönköping, Sweden. kristian.havsed@rjl.se.
Systematic reviews
|October 31, 2023
概括
这次审查发现,大多数多变量预测模型对虫增加有方法上的缺陷和有限的临床有用性. 替代预测因素,如耐酸细菌,可能会改善未来的口腔健康风险评估.
科学领域:
- 口腔健康 口腔健康
- 流行病学 流行病学
- 生物统计学 生物统计学
背景情况:
- 多变量预测模型在口腔卫生保健中至关重要,用于识别患脏高风险的个体.
- 这些模型指导个性化干预,并确定牙科服务周期.
研究的目的:
- 系统地审查和批判性地评估现有的关于多变量预测模型的研究.
主要方法:
- 包括纵向研究,开发或验证至少有三种预测因素的虫病预测模型.
- 搜索了PubMed,科克伦图书馆,科学网和参考清单.
- 使用PROBAST评估偏差风险和适用性;使用概率比率 (LR+/LR-) 重新计算模型性能.
主要成果:
- 使用66种模型的21项研究符合标准;确定了31种常见预测因子 (例如,脏经历,突变性链球菌,化物,斑块).
- 预测性能有所不同 (LR+范围:0.78-10.3;LR-范围:0.0-1.1).
- 大多数研究都有高偏差风险;只有少数模型显示出强大的预测值 (LR+ ≥ 5).
结论:
- 方法上的缺陷和异质性限制了当前空预测模型的临床实用性.
- 错误的估计造成不确定性,影响临床决策.
- 建议考虑替代预测因素,如耐酸细菌,以改善口腔健康风险评估.
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