模型的验证,该模型预测了新冠牙中裂的参与 - - 一个5年后期追踪追踪
Khushboo Kalani1, Giuseppe Troiano2, Asfandyar Sheikh1
1Department of Periodontics and Oral Medicine, University of Michigan School of Dentistry, Ann Arbor, Michigan, USA.
Journal of periodontology
|February 7, 2026
概括
一个新的预测模型准确地识别了固定假肢 (FP) 的牙中裂参与 (FI) 风险. 这种工具有助于临床医生在修复之前评估风险,特别是对于牙周炎患者.
科学领域:
- 牙科 牙科是指牙科的专业.
- 牙周病学 牙周病学
- 牙修复 牙修复 牙修复 牙修复 牙修复
背景情况:
- 裂干涉 (FI) 是固定假肢 (FP) 的牙的一个重要问题.
- 预测FI风险对于长期假肢成功和患者的结果至关重要.
研究的目的:
- 为了验证一个预测模型,对接收固定假肢 (FP) 的牙中裂参与 (FI) 风险进行预测.
- 评估模型的准确性,并随着时间的推移确定关键预测因素.
主要方法:
- 一项纵向队列研究从2018年至2023年跟踪了181名患者 (203个).
- 开发了一个后勤回归模型来预测FI,使用AUC,灵敏度和特异性来评估性能.
- 牙在假牙安置后的1,3年和5年被评估.
主要成果:
- 裂参与 (FI) 的发生率从1年后的4.43%增加到5年后的28.57%.
- 重要的预测因素包括牙周炎史和晚期牙周病阶段 (III和IV).
- 短根干与所有时间点的FI风险增加密切相关 (RR 3.96-6.08).
- 预测模型显示出高性能,AUC为0.81在3年和0.76在5年.
结论:
- 经过验证的预测模型在识别随时间推移的裂参与 (FI) 风险方面表现出高准确性.
- 临床医生应该在皇冠或桥梁修复之前使用此评估工具.
- 在考虑固定假肢时,应特别注意有牙周炎病史的患者.
相关概念视频
Crown Ethers
6.1K
Crown ethers are cyclic polyethers that contain multiple oxygen atoms, usually arranged in a regular pattern. The first crown ether was synthesized by Charles Pederson while working at DuPont in 1967. For this work, Pedersen was co-awarded the 1987 Nobel Prize in Chemistry. Crown ethers are named using the formula x-crown-y, where x is the total number of atoms in the ring and y is the number of ether oxygen atoms. The term 'crown' refers to the crown-like shape that these ether molecules...
6.1K
Teeth
1.8K
The formation of teeth, also known as odontogenesis, is a complex process that begins in utero, around the sixth week of embryonic development. There are three stages to this process: the bud stage, the cap stage, and the bell stage.
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin...
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin...
1.8K
Reliability and Validity
14.1K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
14.1K
Predicting Molecular Geometry
46.0K
VSEPR Theory for Determination of Electron Pair Geometries
46.0K
5-Number Summary
5.7K
In a dataset, the 5-number summary includes the minimum data value, the data value of the first quartile, the median data value or data value of the second quartile, the data value of the third quartile, and the maximum data value. These 5 data values can be visualized as a box and whisker plot.
In a box plot, the minimum and maximum data values represent the lower and upper whiskers in the graph, and the median is designated as the center of the box in the chart. The first quartile and third...
In a box plot, the minimum and maximum data values represent the lower and upper whiskers in the graph, and the median is designated as the center of the box in the chart. The first quartile and third...
5.7K
Prediction Intervals
3.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
3.4K


