PDF(Pubmed)
Abstract：
UNASSIGNED: There is a scarcity of evidence concerning the use of a prognostic instrument for predicting normal healing, delayed healing, and medication-related osteonecrosis of the jaw (MRONJ) occurrence following tooth extraction in medically compromised patients. The present study aimed to predict healing outcomes following tooth extraction in medically compromised patients using an Adapted-University of Connecticut osteonecrosis numerical scale (A-UCONNS).
UNASSIGNED: The digital medical records of medically compromised patients were reviewed, who underwent tooth extraction. The A-UCONNS parameters included the initial pathological condition, dental procedures, comorbidities (smoking habits, type and duration of medication, and type of intervention), and administered antiresorptive (AR) medications. Each parameter was assigned a different weight, and the scores were then accumulated and classified into three categories: minimal risk (less than 10), moderate risk (10-15), and significant risk (16 or more). The patient\'s healing status was categorized as normal healing, delayed healing, or MRONJ.
UNASSIGNED: A total of 353 male patients (mean age: 67.4 years) were recruited from a pool of 3977 patients, where 12.46% of patients had delayed wound healing, and 18.69% developed MRONJ. The median A-UCONNS scores for MRONJ were higher based on initial pathology, comorbidity, and AR drugs compared to normal or delayed healing. In addition, a significant relationship existed between A-UCONNS and healing outcomes (p < 0.05), with a unit increase in A-UCONNS associated with 1.347 times higher odds of experiencing MRONJ compared to normal healing. In contrast, a low score was linked to an increased likelihood of normal wound healing.
UNASSIGNED: The A-UCONNS could act as a promising tool for predicting wound healing outcomes. It can provide clinicians the ability to pinpoint patients at high risk and allow tailoring of patient-specific strategies for improving healing outcomes following tooth extraction.
UNASSIGNED: The digital medical records of medically compromised patients were reviewed, who underwent tooth extraction. The A-UCONNS parameters included the initial pathological condition, dental procedures, comorbidities (smoking habits, type and duration of medication, and type of intervention), and administered antiresorptive (AR) medications. Each parameter was assigned a different weight, and the scores were then accumulated and classified into three categories: minimal risk (less than 10), moderate risk (10-15), and significant risk (16 or more). The patient\'s healing status was categorized as normal healing, delayed healing, or MRONJ.
UNASSIGNED: A total of 353 male patients (mean age: 67.4 years) were recruited from a pool of 3977 patients, where 12.46% of patients had delayed wound healing, and 18.69% developed MRONJ. The median A-UCONNS scores for MRONJ were higher based on initial pathology, comorbidity, and AR drugs compared to normal or delayed healing. In addition, a significant relationship existed between A-UCONNS and healing outcomes (p < 0.05), with a unit increase in A-UCONNS associated with 1.347 times higher odds of experiencing MRONJ compared to normal healing. In contrast, a low score was linked to an increased likelihood of normal wound healing.
UNASSIGNED: The A-UCONNS could act as a promising tool for predicting wound healing outcomes. It can provide clinicians the ability to pinpoint patients at high risk and allow tailoring of patient-specific strategies for improving healing outcomes following tooth extraction.
摘要：
■关于使用预后工具来预测正常愈合的证据很少，延迟愈合,和药物相关的颌骨坏死（MRONJ）发生拔牙后，医学受损的患者。本研究旨在使用康涅狄格州适应大学骨坏死数字量表（A-UCONNS）预测医学受损患者拔牙后的愈合结果。
■对医学受损患者的数字病历进行了审查，接受了拔牙的人。A-UCONNS参数包括初始病理状况，牙科手术,合并症(吸烟习惯，药物的类型和持续时间，和干预类型)，并给予抗再吸收（AR）药物。每个参数被分配了不同的权重，然后将分数累加并分为三类：最小风险(小于10)，中等风险（10-15），和重大风险(16或以上)。患者的愈合状态被归类为正常愈合，延迟愈合,或者MRONJ.
■从3977名患者中招募了353名男性患者（平均年龄：67.4岁），12.46%的患者伤口愈合延迟，18.69%开发了MRONJ。MRONJ的A-UCONNS评分中位数较高，合并症，与AR药物相比，正常或延迟愈合。此外,A-UCONNS和愈合结果之间存在显著关系(p<0.05)，与正常愈合相比，A-UCONNS的单位增加与经历MRONJ的1.347倍相关。相比之下,得分低与伤口正常愈合的可能性增加有关.
■A-UCONNS可以作为预测伤口愈合结果的有希望的工具。它可以为临床医生提供查明高风险患者的能力，并允许定制患者特定的策略，以改善拔牙后的愈合结果。
■对医学受损患者的数字病历进行了审查，接受了拔牙的人。A-UCONNS参数包括初始病理状况，牙科手术,合并症(吸烟习惯，药物的类型和持续时间，和干预类型)，并给予抗再吸收（AR）药物。每个参数被分配了不同的权重，然后将分数累加并分为三类：最小风险(小于10)，中等风险（10-15），和重大风险(16或以上)。患者的愈合状态被归类为正常愈合，延迟愈合,或者MRONJ.
■从3977名患者中招募了353名男性患者（平均年龄：67.4岁），12.46%的患者伤口愈合延迟，18.69%开发了MRONJ。MRONJ的A-UCONNS评分中位数较高，合并症，与AR药物相比，正常或延迟愈合。此外,A-UCONNS和愈合结果之间存在显著关系(p<0.05)，与正常愈合相比，A-UCONNS的单位增加与经历MRONJ的1.347倍相关。相比之下,得分低与伤口正常愈合的可能性增加有关.
■A-UCONNS可以作为预测伤口愈合结果的有希望的工具。它可以为临床医生提供查明高风险患者的能力，并允许定制患者特定的策略，以改善拔牙后的愈合结果。
