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Prognostic Factors of Long-Term Outcomes in Endodontic Microsurgery: A Retrospective Cohort Study over Five Years.

ABSTRACT: The aim of this study was to analyze the long-term outcomes of endodontic microsurgeries in a cohort and identify their association with prognostic factors. A cohort of endodontic microsurgeries followed up periodically with complete clinical and radiographic records for at least 5 years were reviewed retrospectively. Their survival and healing status and profile characteristics were analyzed by Pearson chi-square test and logistic regression (? = 0.05) to identify prognostic factors that influenced outcomes. Of 652 cases in the cohort, 225 (34.5%) were included. The mean follow-up period was 90.4 months (range, 60-168 months). The long-term success rate was 80.5%, and the 5-year survival rate was 83.5%. Logistic regression showed higher success in anteriors compared to molars (OR = 5.405, (95% CI, 1.663-17.571; p = 0.005)) and in teeth with crown restorations (OR = 10.232, (95% CI, 3.374-31.024; p < 0.001)). Conversely, lower success was found in teeth with periodontal disease (OR = 0.170, (95% CI, 0.032-0.900; p = 0.037)) and maxillary sinus involvement (OR = 0.187, (95% CI, 0.035-0.994; p = 0.049)). Endodontic microsurgery has a highly favorable long-term outcome. Tooth position, crown restoration, periodontal disease, and maxillary sinus involvement were identified as main prognostic factors.

SUBMITTER: Yoo YJ

PROVIDER: S-EPMC7409012 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Prognostic Factors of Long-Term Outcomes in Endodontic Microsurgery: A Retrospective Cohort Study over Five Years.

Yoo Yeon-Jee YJ Kim Dong-Won DW Perinpanayagam Hiran H Baek Seung-Ho SH Zhu Qiang Q Safavi Kamran K Kum Kee-Yeon KY

Journal of clinical medicine 20200713 7

The aim of this study was to analyze the long-term outcomes of endodontic microsurgeries in a cohort and identify their association with prognostic factors. A cohort of endodontic microsurgeries followed up periodically with complete clinical and radiographic records for at least 5 years were reviewed retrospectively. Their survival and healing status and profile characteristics were analyzed by Pearson chi-square test and logistic regression (α = 0.05) to identify prognostic factors that influe ...[more]

PMID: 32668578

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Project description:ObjectivesTo develop a transparent and reproducible measure for hospitals that can indicate when deaths in hospital or within 30 days of discharge are high relative to other hospitals, given the characteristics of the patients in that hospital, and to investigate those factors that have the greatest effect in changing the rank of a hospital, whether interactions exist between those factors, and the stability of the measure over time.DesignRetrospective cross sectional study of admissions to English hospitals.SettingHospital episode statistics for England from 1 April 2005 to 30 September 2010, with linked mortality data from the Office for National Statistics.Participants36.5 million completed hospital admissions in 146 general and 72 specialist trusts.Main outcome measuresDeaths within hospital or within 30 days of discharge from hospital.ResultsThe predictors that were used in the final model comprised admission diagnosis, age, sex, type of admission, and comorbidity. The percentage of people admitted who died in hospital or within 30 days of discharge was 4.2% for males and 4.5% for females. Emergency admissions comprised 75% of all admissions and 5.5% died, in contrast to 0.8% who died after an elective admission. The percentage who died with a Charlson comorbidity score of 0 was 2% in contrast with 15% who died with a score greater than 5. Given these variables, the relative standardised mortality rates of the hospitals were not noticeably changed by adjusting for the area level deprivation and number of previous emergency visits to hospital. There was little evidence that including interaction terms changed the relative values by any great amount. Using these predictors the summary hospital mortality index (SHMI) was derived. For 2007/8 the model had a C statistic of 0.911 and accounted for 81% of the variability of between hospital mortality. A random effects funnel plot was used to identify outlying hospitals. The outliers from the SHMI over the period 2005-10 have previously been identified using other mortality indicators.ConclusionThe SHMI is a relatively simple tool that can be used in conjunction with other information to identify hospitals that may need further investigation.

Project description:BackgroundChronic kidney disease (CKD) is commonly managed in primary care, but most guidelines have a secondary care perspective emphasizing the risk of end-stage kidney disease (ESKD) and need for renal replacement therapy. In this prospective cohort study, we sought to study in detail the natural history of CKD in primary care to better inform the appropriate emphasis for future guidance.Methods and findingsIn this study, 1,741 people with CKD stage 3 were individually recruited from 32 primary care practices in Derbyshire, United Kingdom. Study visits were undertaken at baseline, year 1, and year 5. Binomial logistic regression and Cox proportional hazards models were used to model progression, CKD remission, and all-cause mortality. We used Kidney Disease: Improving Global Outcomes (KDIGO) criteria to define CKD progression and defined CKD remission as the absence of diagnostic criteria (estimated glomerular filtration rate [eGFR] >60 ml/min/1.73 m2 and urine albumin-to-creatinine ratio [uACR] <3 mg/mmol) at any study visit. Participants were predominantly elderly (mean ± standard deviation (SD) age 72.9 ± 9.0 y), with relatively mild reduction in GFR (mean ± SD eGFR 53.5 ± 11.8 mL/min/1,73 m2) and a low prevalence of albuminuria (16.9%). After 5 y, 247 participants (14.2%) had died, most of cardiovascular causes. Only 4 (0.2%) developed ESKD, but 308 (17.7%) evidenced CKD progression by KDIGO criteria. Stable CKD was observed in 593 participants (34.1%), and 336 (19.3%) met the criteria for remission. Remission at baseline and year 1 was associated with a high likelihood of remission at year 5 (odds ratio [OR] = 23.6, 95% CI 16.5-33.9 relative to participants with no remission at baseline and year 1 study visits). Multivariable analyses confirmed eGFR and albuminuria as key risk factors for predicting adverse as well as positive outcomes. Limitations of this study include reliance on GFR estimated using the Modification of Diet in Renal Disease study (MDRD) equation for recruitment (but not subsequent analysis) and a study population that was predominantly elderly and white, implying that the results may not be directly applicable to younger populations of more diverse ethnicity.ConclusionsManagement of CKD in primary care should focus principally on identifying the minority of people at high risk of adverse outcomes, to allow intervention to slow CKD progression and reduce cardiovascular events. Efforts should also be made to identify and reassure the majority who are at low risk of progression to ESKD. Consideration should be given to adopting an age-calibrated definition of CKD to avoid labelling a large group of people with age-related decline in GFR and low associated risk as having CKD.

Dataset Information

Prognostic Factors of Long-Term Outcomes in Endodontic Microsurgery: A Retrospective Cohort Study over Five Years.

Publications

Prognostic Factors of Long-Term Outcomes in Endodontic Microsurgery: A Retrospective Cohort Study over Five Years.

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