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Background: There is little evidence regarding risk prediction for surgical site infection (SSI) after lower third molar (L3M) surgery. Methods: We conducted a nested case–control study to develop a multivariable logistic model for predicting the risk of SSI after L3M surgery. Data were obtained from Hokkaido University Hospital from April 2013 to March 2020. Multiple imputation was applied for the missing values. We conducted decision tree (DT) analysis to evaluate the combinations of factors affecting SSI risk. Results: We identified 648 patients. The final model retained the available distal space (Pell & Gregory II [p = 0.05], Pell & Gregory III [p < 0.01]), depth (Pell & Gregory B [p < 0.01], Pell & Gregory C [p < 0.01]), surgeon's experience (3–10 years [p = 0.25], <3 years [p < 0.01]), and simultaneous extraction of both L3M [p < 0.01]; the concordance‐statistic was 0.72. The DT analysis demonstrated that patients with Pell and Gregory B or C and simultaneous extraction of both L3M had the highest risk of SSI. Conclusions: We developed a model for predicting SSI after L3M surgery with adequate predictive metrics in a single center. This model will make the SSI risk prediction more accessible. [ABSTRACT FROM AUTHOR]

The document is a reply to a commentary on the development of a risk prediction model for surgical site infection after lower third molar surgery. The authors address the comments made on the adequacy of the sample size and the comparison between outcome and non-outcome groups. They provide results from multivariable logistic regression and acknowledge the importance of having an adequate sample size for developing a prediction model. The authors also list their contributions and declare any conflicts of interest. [Extracted from the article]

1. The need to understand the mechanisms enhancing species coexistence and diversity is one of the central issues of community ecology. Theoretical work suggests that resource partitioning based on body size contributes to the coexistence of competing species, resulting in increased species diversity. Nevertheless, few empirical studies have investigated this. The species composition of wood-dwelling arthropods was surveyed to examine resource partitioning based on body size in the dead wood of the ubame oak (Quercus phillyraeoides A. Grey) trees. 2. Greater resource sizes (larger dead wood diameter) retained a lower overall density of wood-dwelling beetles per resource volume, greater total beetle biomass per resource volume and larger bodied individuals of the dominant species (Cerambycidae; Anaglyptus nipponensis Bates). A gradient in the species composition of arboreal ant assemblages along resource size and a positive correlation between resource size and ant body size was observed. These results suggest that the incidence of wood-boring beetles was limited by the size of the available resource, resulting in resource partitioning by the ants according to the sizes of galleries made by the beetles. 3. Our findings indicate that resource size leads both directly and indirectly to body size-dependent resource partitioning in beetle and ant assemblages, and contributes to the maintenance of species coexistence in the assemblages present in dead wood. [ABSTRACT FROM AUTHOR]