Browsing by Author "Thyvalikakath, Thankam Paul"
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Item Can Salivary Innate Immune Molecules Provide Clue on Taste Dysfunction in COVID-19?(Frontiers, 2021-10) Ermel, Aaron; Thyvalikakath, Thankam Paul; Foroud, Tatiana; Khan, Babar; Srinivasan, Mythily; Medicine, School of MedicineEmerging concerns following the severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) pandemic are the long-term effects of coronavirus disease (COVID)-19. Dysgeusia in COVID-19 is supported by the abundant expression of the entry receptor, angiotensin-converting enzyme-2 (ACE2), in the oral mucosa. The invading virus perturbs the commensal biofilm and regulates the host responses that permit or suppress viral infection. We correlated the microbial recognition receptors and soluble ACE2 (sACE2) with the SARS-CoV2 measures in the saliva of COVID-19 patients. Data indicate that the toll-like receptor-4, peptidoglycan recognition protein, and sACE2 are elevated in COVID-19 saliva and correlate moderately with the viral load.Item Leveraging Electronic Dental Record Data for Clinical Research in the National Dental PBRN Practices(Thieme, 2020-03) Thyvalikakath, Thankam Paul; Duncan, William D.; Siddiqui, Zasim; LaPradd, Michelle; Eckert, George; Schleyer, Titus; Rindal, Donald Brad; Jurkovich, Mark; Shea, Tracy; Gilbert, Gregg H.; Pediatrics, School of MedicineObjectives: The aim of this study is to determine the feasibility of conducting clinical research using electronic dental record (EDR) data from U.S. solo and small-group general dental practices in the National Dental Practice-Based Research Network (network) and evaluate the data completeness and correctness before performing survival analyses of root canal treatment (RCT) and posterior composite restorations (PCR). Methods: Ninety-nine network general dentistry practices that used Dentrix or EagleSoft EDR shared de-identified data of patients who received PCR and/or RCT on permanent teeth through October 31, 2015. We evaluated the data completeness and correctness, summarized practice, and patient characteristics and summarized the two treatments by tooth type and arch location. Results: Eighty-two percent of practitioners were male, with a mean age of 49 and 22.4 years of clinical experience. The final dataset comprised 217,887 patients and 11,289,594 observations, with the observation period ranging from 0 to 37 years. Most patients (73%) were 18 to 64 years old; 56% were female. The data were nearly 100% complete. Eight percent of observations had incorrect data, such as incorrect tooth number or surface, primary teeth, supernumerary teeth, and tooth ranges, indicating multitooth procedures instead of PCR or RCT. Seventy-three percent of patients had dental insurance information; 27% lacked any insurance information. While gender was documented for all patients, race/ethnicity was missing in the dataset. Conclusion: This study established the feasibility of using EDR data integrated from multiple distinct solo and small-group network practices for longitudinal studies to assess treatment outcomes. The results laid the groundwork for a learning health system that enables practitioners to learn about their patients' outcomes by using data from their own practice.Item Leveraging Electronic Dental Record Data to Classify Patients Based on Their Smoking Intensity(Thieme, 2018) Patel, Jay; Siddiqui, Zasim; Krishnan, A.; Thyvalikakath, Thankam Paul; Cariology, Operative Dentistry and Dental Public Health, School of DentistryBackground Smoking is an established risk factor for oral diseases and, therefore, dental clinicians routinely assess and record their patients' detailed smoking status. Researchers have successfully extracted smoking history from electronic health records (EHRs) using text mining methods. However, they could not retrieve patients' smoking intensity due to its limited availability in the EHR. The presence of detailed smoking information in the electronic dental record (EDR) often under a separate section allows retrieving this information with less preprocessing. Objective To determine patients' detailed smoking status based on smoking intensity from the EDR. Methods First, the authors created a reference standard of 3,296 unique patients’ smoking histories from the EDR that classified patients based on their smoking intensity. Next, they trained three machine learning classifiers (support vector machine, random forest, and naïve Bayes) using the training set (2,176) and evaluated performances on test set (1,120) using precision (P), recall (R), and F-measure (F). Finally, they applied the best classifier to classify smoking status from an additional 3,114 patients’ smoking histories. Results Support vector machine performed best to classify patients into smokers, nonsmokers, and unknowns (P, R, F: 98%); intermittent smoker (P: 95%, R: 98%, F: 96%); past smoker (P, R, F: 89%); light smoker (P, R, F: 87%); smokers with unknown intensity (P: 76%, R: 86%, F: 81%), and intermediate smoker (P: 90%, R: 88%, F: 89%). It performed moderately to differentiate heavy smokers (P: 90%, R: 44%, F: 60%). EDR could be a valuable source for obtaining patients’ detailed smoking information. Conclusion EDR data could serve as a valuable source for obtaining patients' detailed smoking information based on their smoking intensity that may not be readily available in the EHR.Item Longevity of dental restorations in Sjogren's disease patients using electronic dental and health record data(Springer Nature, 2024-02-07) Gomez, Grace Gomez Felix; Wang, Mei; Siddiqui, Zasim A.; Gonzalez, Theresa; Capin, Oriana R.; Willis, Lisa; Boyd, LaKeisha; Eckert, George J.; Zero, Domenick T.; Thyvalikakath, Thankam Paul; Dental Public Health and Dental Informatics, School of DentistryBackground: Decreased salivary secretion is not only a risk factor for carious lesions in Sjögren's disease (SD) but also an indicator of deterioration of teeth with every restorative replacement. This study determined the longevity of direct dental restorations placed in patients with SD using matched electronic dental record (EDR) and electronic health record (EHR) data. Methods: We conducted a retrospective cohort study using EDR and EHR data of Indiana University School of Dentistry patients who have a SD diagnosis in their EHR. Treatment history of patients during 15 years with SD (cases) and their matched controls with at least one direct dental restoration were retrieved from the EDR. Descriptive statistics summarized the study population characteristics. Cox regression models with random effects analyzed differences between cases and controls for time to direct restoration failure. Further the model explored the effect of covariates such as age, sex, race, dental insurance, medical insurance, medical diagnosis, medication use, preventive dental visits per year, and the number of tooth surfaces on time to restoration failure. Results: At least one completed direct restoration was present for 102 cases and 42 controls resulting in a cohort of 144 patients' EDR and EHR data. The cases were distributed as 21 positives, 57 negatives, and 24 uncertain cases based on clinical findings. The average age was 56, about 93% were females, 54% were White, 74% had no dental insurance, 61% had public medical insurance, < 1 preventive dental visit per year, 94% used medications and 93% had a medical diagnosis that potentially causes dry mouth within the overall study cohort. About 529 direct dental restorations were present in cases with SD and 140 restorations in corresponding controls. Hazard ratios of 2.99 (1.48-6.03; p = 0.002) and 3.30 (1.49-7.31, p-value: 0.003) showed significantly decreased time to restoration failure among cases and positive for SD cases compared to controls, respectively. Except for the number of tooth surfaces, no other covariates had a significant influence on the survival time. Conclusion: Considering the rapid failure of dental restorations, appropriate post-treatment assessment, management, and evaluation should be implemented while planning restorative dental procedures among cases with SD. Since survival time is decreased with an increase in the number of surfaces, guidelines for restorative procedures should be formulated specifically for patients with SD.Item 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 DentistryPurpose 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.Item Survival Analysis of Endodontically Treated Teeth in Patients with Diabetes and Hypertension within National Dental PBRN Practices(2022-06) Crosby, William Justin; Spolnik, Kenneth; Thyvalikakath, Thankam Paul; Ehrlich, Ygal; Warner, NedIntroduction: The prevalence of diabetes mellitus (DM) is rapidly increasing among the aging United States population. This poses a challenge to dental providers since DM and multiple oral conditions have been identified as comorbidities. Hypertension (HTN) is associated with more poorly controlled DM and has been identified as contributing to RCT tooth loss in prior studies. Links have also been established between DM and the survival rate of root canal treated teeth, however, previous research has focused on institutional settings despite the majority of RCT being performed in private dental practices. This study will use data from private dental practices to evaluate the survival rate of RCT teeth in patients with DM and HTN. Materials and Methods: This retrospective study evaluated the survival rate of endodontic treated teeth among patients with DM and HTN using National Dental PBRN Practice data. Electronic dental records from 42 private dental practices in the United States over a period of 15 years with a minimum 2-year follow-up comprising 11,532 root canal treated teeth were analyzed. Kaplan-Meier survival curves were used to demonstrate the effects of HTN and DM on RCT tooth survival and Cox proportional hazards survival analysis was used to evaluate the DM and HTN effects after accounting for age, gender, insurance, year of treatment, tooth type, and crown and filling placement as covariates. Results: Patients with HTN only had significantly lower risk of failure than patients with both HTN and DM (p=0.003). Patients with neither HTN nor DM had significantly lower risk of failure than patients with both HTN and DM (p=0.020). Patients with DM only did not have significantly different risk of failure than patients with both HTN and DM (p=0.223). Patients with DM only did not have significantly different risk of failure than patients with HTN only (p=0.361). Patients with neither HTN nor DM did not have significantly different risk of failure than patients with HTN only (p=0.121) or patients with DM only (p=0.800). Conclusions: Patients with both DM and HTN have an increased chance of root canal treated tooth failure while patients with only DM or only HTN do not. Evaluation of severity of DM may be more important in determining RCT failure and studies utilizing laboratory values should be considered for future research.Item Utilizing Electronic Dental Record Data to Track Periodontal Disease Change(2020-07) Patel, Jay Sureshbhai; Jones, Josette; Thyvalikakath, Thankam Paul; Palkal, Mathew; Kowolik, Michael; Nagarajan, RadhaPeriodontal disease (PD) affects 42% of US population resulting in compromised quality of life, the potential for tooth loss and influence on overall health. Despite significant understanding of PD etiology, limited longitudinal studies have investigated PD change in response to various treatments. A major barrier is the difficulty of conducting randomized controlled trials with adequate numbers of patients over a longer time. Electronic dental record (EDR) data offer the opportunity to study outcomes following various periodontal treatments. However, using EDR data for research has challenges including quality and missing data. In this dissertation, I studied a cohort of patients with PD from EDR to monitor their disease status over time. I studied retrospectively 28,908 patients who received comprehensive oral evaluation at the Indiana University School of Dentistry between January 1st-2009 and December 31st-2014. Using natural language processing and automated approaches, we 1) determined PD diagnoses from periodontal charting based on case definitions for surveillance studies, 2) extracted clinician-recorded diagnoses from clinical notes, 3) determined the number of patients with disease improvement or progression over time from EDR data. We found 100% completeness for age, sex; 72% for race; 80% for periodontal charting findings; and 47% for clinician-recorded diagnoses. The number of visits ranged from 1-14 with an average of two visits. From diagnoses obtained from findings, 37% of patients had gingivitis, 55% had moderate periodontitis, and 28% had severe periodontitis. In clinician-recorded diagnoses, 50% patients had gingivitis, 18% had mild, 14% had moderate, and 4% had severe periodontitis. The concordance between periodontal charting-generated and clinician-recorded diagnoses was 47%. The results indicate that case definitions for PD are underestimating gingivitis and overestimating the prevalence of periodontitis. Expert review of findings identified clinicians relying on visual assessment and radiographic findings in addition to the case definition criteria to document PD diagnosis.