Browsing by Subject "dental informatics"

Now showing 1 - 3 of 3
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    Developing Automated Computer Algorithms to Track Periodontal Disease Change from Longitudinal Electronic Dental Records
    (MDPI, 2023-03-08) Patel, Jay S.; Kumar, Krishna; Zai, Ahad; Shin, Daniel; Willis, Lisa; Thyvalikakath, Thankam P.
    Objective: To develop two automated computer algorithms to extract information from clinical notes, and to generate three cohorts of patients (disease improvement, disease progression, and no disease change) to track periodontal disease (PD) change over time using longitudinal electronic dental records (EDR). Methods: We conducted a retrospective study of 28,908 patients who received a comprehensive oral evaluation between 1 January 2009, and 31 December 2014, at Indiana University School of Dentistry (IUSD) clinics. We utilized various Python libraries, such as Pandas, TensorFlow, and PyTorch, and a natural language tool kit to develop and test computer algorithms. We tested the performance through a manual review process by generating a confusion matrix. We calculated precision, recall, sensitivity, specificity, and accuracy to evaluate the performances of the algorithms. Finally, we evaluated the density of longitudinal EDR data for the following follow-up times: (1) None; (2) Up to 5 years; (3) > 5 and ≤ 10 years; and (4) >10 and ≤ 15 years. Results: Thirty-four percent (n = 9954) of the study cohort had up to five years of follow-up visits, with an average of 2.78 visits with periodontal charting information. For clinician-documented diagnoses from clinical notes, 42% of patients (n = 5562) had at least two PD diagnoses to determine their disease change. In this cohort, with clinician-documented diagnoses, 72% percent of patients (n = 3919) did not have a disease status change between their first and last visits, 669 (13%) patients’ disease status progressed, and 589 (11%) patients’ disease improved. Conclusions: This study demonstrated the feasibility of utilizing longitudinal EDR data to track disease changes over 15 years during the observation study period. We provided detailed steps and computer algorithms to clean and preprocess the EDR data and generated three cohorts of patients. This information can now be utilized for studying clinical courses using artificial intelligence and machine learning methods.
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    Nutritional Assessment of Denture Wearers Using Matched Electronic Dental-Health Record Data
    (Wiley, 2022-08) Felix Gomez, Grace Gomez; Cho, Sopanis D.; Varghese, Roshan; Rajendran, Divya; Eckert, George J.; Bhamidipalli, Sruthi Surya; Gonzalez, Theresa; Khan, Babar Ali; Thyvalikakath, Thankam Paul; Cariology, Operative Dentistry and Dental Public Health, School of Dentistry
    Purpose To assess the nutritional profile of denture wearers through a retrospective cohort study using nutritional biomarkers from matched electronic dental and health record (EDR-EHR) data. Materials and methods The case group (denture wearers) included matched EDR-EHR data of patients who received removable partial, complete, and implant-supported prosthodontic treatments between January 1, 2010 and December 31, 2018, study time. The control (nondenture wearers) group did not have recorded denture treatments and included patient records within 1 year of the denture index date (first date of case patients’ receiving complete or partial denture) of the matching cases. The qualified patients’ EDR were matched with their EHR based on the availability of laboratory reports within 2 years of receiving the dentures (index date). Nutritional biomarkers were selected from laboratory reports for complete blood count, comprehensive and basic metabolic profile, lipid, and thyroid panels. Summary statistics were performed, and general linear mixed effect models were used to evaluate the rate of change over time (slope) of nutritional biomarkers before and after the index date. Likelihood ratio tests were performed to determine the differences between dentures and controls. Results The final cohort included 10,481 matched EDR-EHR data with 3,519 denture wearers and 6,962 controls that contained laboratory results within the study time. The denture wearers’ mean age was 57 ±10 years and the control group was 56 ±10 years with 55% females in both groups. Pre-post analysis among denture wearers revealed decreased serum albumin (p = 0.002), calcium (p = 0.039), creatinine (p < 0.001) during the post-index time. Hemoglobin (Hb) was higher pre-index, and was decreasing during the time period but did not change post-index (p < 0.001). Among denture wearers, completely edentulous patients had a significant decrease in serum albumin, creatinine, blood urea nitrogen (BUN), but increased estimated glomerular filtration rate (eGFR). In partially edentulous patients, total cholesterol decreased (p = 0.018) and TSH (p = 0.004), BUN (p < 0.001) increased post-index. Patients edentulous in either upper or lower arch had decreased BUN and eGFR during post-index. Compared to controls, denture wearers showed decreased serum albumin and protein (p = 0.008), serum calcium (p = 0.001), and controls showed increased Hb (p = 0.035) during post-index. Conclusions The study results indicate nutritional biomarker variations among denture wearers suggesting a risk for undernutrition and the potential of using selected nutritional biomarkers to monitor nutritional profile.
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    Root Canal Treatment Survival Analysis in National Dental PBRN Practices
    (Sage, 2022-10) Thyvalikakath, T.; LaPradd, M.; Siddiqui, Z.; Duncan, W. D.; Eckert, G.; Medam, J. K.; Rindal, D. B.; Jurkovich, M.; Gilbert, G. H.; National Dental PBRN Collaborative Group; Dental Public Health and Dental Informatics, School of Dentistry
    Few studies have examined the longevity of endodontically treated teeth in nonacademic clinical settings where most of the population receives its care. This study aimed to quantify the longevity of teeth treated endodontically in general dentistry practices and test the hypothesis that longevity significantly differed by the patient’s age, gender, dental insurance, geographic region, and placement of a crown and/or other restoration soon after root canal treatment (RCT). This retrospective study used deidentified data of patients who underwent RCT of permanent teeth through October 2015 in 99 general dentistry practices in the National Dental Practice-Based Research Network (Network). The data set included 46,702 patients and 71,283 RCT permanent teeth. The Kaplan–Meier (product limit) estimator was performed to estimate survival rate after the first RCT performed on a specific tooth. The Cox proportional hazards model was done to account for patient- and tooth-specific covariates. The overall median survival time was 11.1 y; 26% of RCT teeth survived beyond 20 y. Tooth type, presence of dental insurance any time during dental care, placement of crown and/or receiving a filling soon after RCT, and Network region were significant predictors of survival time (P < 0.0001). Gender and age were not statistically significant predictors in univariable analysis, but in multivariable analyses, gender was significant after accounting for other variables. This study of Network practices geographically distributed across the United States observed shorter longevity of endodontically treated permanent teeth than in previous community-based studies. Also, having a crown placed following an RCT was associated with 5.3 y longer median survival time. Teeth that received a filling soon after the RCT before the crown was placed had a median survival time of 20.1 y compared to RCT teeth with only a crown (11.4 y), only a filling (11.2 y), or no filling and no crown (6.5 y).