Analysis of Risk Factors for Post-Extraction Bleeding and Study on Emergency Intervention Strategies

The objective of this investigation is to delineate the distributional attributes of factors correlated with post-tooth extraction bleeding and to scrutinize corresponding strategies for emergency prevention and intervention.

The chi-squared test and rank sum test were deployed to evaluate fluctuations in blood loss. Univariate and multivariate binary logistic regression methodologies were employed to compute the odds ratio (OR) and its associated 95% confidence interval (95% CI). Furthermore, we delved into the relationship between each contributing factor and blood loss. Concurrently, univariate and multivariate logistic regression techniques were utilized to probe the nexus between blood loss and treatment modalities.

Following adjustments for pertinent factors, the outcomes of multivariate analyses unveiled an escalated susceptibility to bleeding among male patients and individuals aged 60 years or older. The adjusted OR values and their corresponding 95% CI were determined as follows: OR = 1.54 (95% CI: 1.34-1.77, P < 0.001), OR = 0.74 (95% CI: 0.59-0.91, P = 0.005), OR = 0.58 (95% CI: 0.42-0.80, P = 0.001). Additionally, the results of multivariate logistic regression analysis indicated that, in contrast to individuals experiencing minimal blood loss, the OR values associated with treatment modalities for patients encountering substantial blood loss, namely iodoform gauze strips, sutures, collagen, and compression, were noted as follows: OR = 220.80 (95% CI: 151.43-321.95, P < 0.001), OR = 69.40 (95% CI: 46.11-104.44, P < 0.001), OR = 52.78 (95% CI: 34.66-80.38, P < 0.001), OR = 12.85 (95% CI: 9.46-17.45, P < 0.001).

It is imperative to prioritize the scrutiny of risk factors associated with post-tooth extraction hemorrhage, with the aim of preemptively averting incidences of bleeding subsequent to tooth extraction. Moreover, it is paramount to offer expert and tailored emergency interventions designed to address diverse case scenarios.