Abstract
This retrospective study evaluated the influence of known risk factors on nonsurgical periodontal treatment (NSPT) response using a pocket depth fine-tuning multilevel linear model (MLM). Overall, 37 patients (24 males and 13 females) with moderate-to-severe chronic periodontitis underwent NSPT. Follow-up visits at 3, 6, and 12 months included measurements of several clinical periodontal parameters. Data were sourced from a previously reported database. In a total of 1416 initially affected sites (baseline PD ≥ 4 mm) on 536 teeth, probing depth (PD) and clinical attachment loss (CAL) reductions after NSPT were evaluated against known risk factors at 3 hierarchical levels (patient, tooth, and site). For each post-treatment follow-up, the variance component models fitted to evaluate the 3-level variance of PD and CAL decrease revealed that all levels contributed significantly to the overall variance (p < 0.001). Patients who underwent NSPT and were continually monitored had curative results. All 3 hierarchical levels included risk factors influencing the degree of PD and CAL reduction. Specifically, the type of tooth, surfaces involved, and tooth mobility site-level risk factors had the strongest impact on these reductions and were highly relevant for the success of NSPT.
Highlights
We identified 13 patients with a monthly income up to 580€, 11 earning 581€–900€, and 13 earning more than 900€
A limitation of the present study is its limited sample size, which may lead to unpowered analysis and test results, even though we have identified the same limitation in similar multilevel modeling (MLM) studie.[21,23,29] from p < 0.05 to p < 0.10 and by fitting the model strictly with data from treated sites
Pocket depth fine-tuning MLM showed that nonsurgical periodontal treatment (NSPT) had a significant healing effect for moderate-to-severe chronic periodontitis (CP) with considerable reductions in probing depth (PD) and clinical attachment loss (CAL)
Summary
Periodontitis is an inflammatory disease that progressively destroys tooth-supporting structures and, according to the Global Burden of Disease Study (GBD, 1990–2010), its severe form is the sixth most prevalent disease worldwide, affecting 11% of the overall population.[1,2,3,4,5,6] The complexity of bacterial biofilms, the “silent pattern” of progression, and poor awareness of periodontal health in individuals hinders its treatment and requires a motivated patient and long-term compliance for a successful treatment outcome.[5,6,7,8,9,10]Currently, periodontitis treatment approaches consist of nonsurgical (NSPT) and surgical treatments (SPT) that are centered on the patient.[11,12,13] Conventional NSPT is the mainstay of periodontitis treatment and is shown to have meaningful results;[7,12] the presence of residual pockets may jeopardize tooth survival , 14,15 requiring NSPT or SPT.[13]The application of multilevel modeling (MLM) to periodontal research was proposed by Albandar and Goldstein[16] in an attempt to integrateBraz.
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