Evaluation of the effects of postprocessing settings in digital bitewing radiographs on proximal caries detection.

OBJECTIVE: Radiographs are an integral part of detecting proximal caries. The aim of this study was to evaluate the effect of contrast, brightness, noise, sharpness, and γ adjustment of digital intraoral radiographs on the diagnosis of proximal caries. MATERIALS AND METHODS: In this in vitro study, 40 extracted teeth including 20 premolars and 20 molars with enamel lesions (white spot or dentin discoloration seen through the enamel) were mounted together in groups of eight inside the skull. Bitewing radiographic images of each dental group were obtained by a photostimulable phosphor plate sensor with exposure conditions of 8 mA, 70 kV, and 0.2 s. The images were reconstructed by the built-in software and examined by two oral and maxillofacial radiologists in various settings of contrast, brightness, sharpness, noise, and γ. The teeth were then cut mesiodistally and the presence or absence of caries was confirmed by an oral and maxillofacial pathologist using a stereomicroscope. The data were then analyzed using the κ agreement coefficient, sensitivity, specificity, and accuracy (α = .05). RESULTS: Adjustment of brightness and contrast led to higher diagnostic performance with an accuracy of 82.5% and 83.8 (for observers 1 and 2, respectively) and 82.5% (for both observers), respectively. Noise adjustment was the least helpful approach for diagnosis of proximal dental caries among other adjustments, with an accuracy of 78.8% and 77.5% for observers 1 and 2, respectively. CONCLUSION: Brightness and contrast setting was more efficient in improving the diagnostic potential of bitewing radiographs compared to other adjustments.

Predicting dental caries outcomes in young adults using machine learning approach.

OBJECTIVES: To predict the dental caries outcomes in young adults from a set of longitudinally-obtained predictor variables and identify the most important predictors using machine learning techniques. METHODS: This study was conducted using the Iowa Fluoride Study dataset. The predictor variables - sex, mother's education, family income, composite socio-economic status (SES), caries experience at ages 9, 13, and 17, and the cumulative estimates of risk and protective factors, including fluoride, dietary, and behavioral variables from ages 5-9, 9-13, 13-17, and 17-23 were used to predict the age 23 D2+MFS count. The following machine learning models (LASSO regression, generalized boosting machines (GBM), negative binomial (NegGLM), and extreme gradient boosting models (XGBOOST)) were compared under 5-fold cross validation with nested resampling techniques. RESULTS: The prevalence of cavitated level caries experience at age 23 (mean D2+MFS count) was 4.75. The predictive analysis found LASSO to be the best performing model (compared to GBM, NegGLM, and XGBOOST), with a root mean square error (RMSE) of 0.70, and coefficient of determination (R2) of 0.44. After dichotomization of the predicted and observed values of the LASSO regression, the classification results showed accuracy, precision, recall, and ROC AUC of 83.7%, 85.9%, 93.1%, 68.2%, respectively. Previous caries experience at age 13 and age 17 and sugar-sweetened beverages intakes at age 13 and age 17 were found to be the four most important predictors of cavitated caries count at age 23. CONCLUSION: Our machine learning model showed high accuracy and precision in the prediction of caries in young adults from a longitudinally-obtained predictor variables. Our model could, in the future, after further development and validation with other diverse population data, be used by public health specialists and policy-makers as a screening tool to identify the risk of caries in young adults and apply more targeted interventions. However, data from a more diverse population are needed to improve the quality and generalizability of caries prediction.

Salivary Proteinase 3 as a Biomarker for Caries Severity in Children: A Cross-sectional Study.

AIM: This study aims to evaluate the relation between salivary proteinase 3 (PR3) concentration and caries severity in children. MATERIALS AND METHODS: Six-to-eight-year age group children, from the Outpatient Department of Pediatric and Preventive dentistry at PMS Dental College were selected for the study. From these children, three groups each consisting of 28 children were selected according to the dental caries severity. Three groups were: (1) No Dental Caries group, (2) Low Dental Caries group with DMFT/DEFT score of 1-4, and (3) High Dental Caries group with DMFT/DEFT score of 5-15. Thus, a total of 84 children who satisfied the inclusion criteria were selected. The concentration of PR3 in saliva of the donors were analyzed using an ELISA kit. One way ANOVA was used for finding the relation of salivary PR3 concentration with caries severity. Pairwise comparison of PR3 concentration and caries severity were analyzed using post hoc Tukey test. RESULTS: Severity of caries and concentration of salivary PR3 showed an inverse relation. As the caries severity increases there was a decrease in PR3 concentration and vice versa. CONCLUSION: The children with high caries severity showed lower concentration of PR3 in their saliva compared with those with lower caries severity which indicates that PR3 can be used as a biomarker for assessing caries severity and also paves way to use PR3 as a caries vaccine in future. Nowadays, interest toward noninvasive and personalized dentistry has been increased. Molecular assays using salivary biomarkers can be an effective tool in detecting the caries in earlier stages and assessing a patient's caries risk. CLINICAL SIGNIFICANCE: Salivary PR3 can be used as prognostic biomarker for assessing caries severity and after treatment the value of PR3 can be used as a assessment tool to confirm its relation with caries. How to cite this article: Karthika S, George S, Soman A, et al. Salivary Proteinase 3 as a Biomarker for Caries Severity in Children: A Cross-sectional Study. J Contemp Dent Pract 2024;25(3):236-240.

Simultaneous detection of dental caries and fissure sealant in intraoral photos by deep learning: a pilot study.

BACKGROUND: Deep learning, as an artificial intelligence method has been proved to be powerful in analyzing images. The purpose of this study is to construct a deep learning-based model (ToothNet) for the simultaneous detection of dental caries and fissure sealants in intraoral photos. METHODS: A total of 1020 intraoral photos were collected from 762 volunteers. Teeth, caries and sealants were annotated by two endodontists using the LabelMe tool. ToothNet was developed by modifying the YOLOX framework for simultaneous detection of caries and fissure sealants. The area under curve (AUC) in the receiver operating characteristic curve (ROC) and free-response ROC (FROC) curves were used to evaluate model performance in the following aspects: (i) classification accuracy of detecting dental caries and fissure sealants from a photograph (image-level); and (ii) localization accuracy of the locations of predicted dental caries and fissure sealants (tooth-level). The performance of ToothNet and dentist with 1year of experience (1-year dentist) were compared at tooth-level and image-level using Wilcoxon test and DeLong test. RESULTS: At the image level, ToothNet achieved an AUC of 0.925 (95% CI, 0.880-0.958) for caries detection and 0.902 (95% CI, 0.853-0.940) for sealant detection. At the tooth level, with a confidence threshold of 0.5, the sensitivity, precision, and F1-score for caries detection were 0.807, 0.814, and 0.810, respectively. For fissure sealant detection, the values were 0.714, 0.750, and 0.731. Compared with ToothNet, the 1-year dentist had a lower F1 value (0.599, p < 0.0001) and AUC (0.749, p < 0.0001) in caries detection, and a lower F1 value (0.727, p = 0.023) and similar AUC (0.829, p = 0.154) in sealant detection. CONCLUSIONS: The proposed deep learning model achieved multi-task simultaneous detection in intraoral photos and showed good performance in the detection of dental caries and fissure sealants. Compared with 1-year dentist, the model has advantages in caries detection and is equivalent in fissure sealants detection.

Comparison of two different caries risk assessment tools for infants and toddlers - A cross-sectional study.

CONTEXT: One of the essential components for successful caries management is caries risk assessment (CRA). Among CRA tools (CRATs) published in the literature: Caries management by risk assessment (CAMBRA) 123 and American Academy of Pediatric Dentistry (AAPD) CRATs are specifically designed for infants and toddlers. AIMS: The aim of this study is to compare readily available internationally accepted CRAT for infants and toddlers and check the usability of these tools in assigning caries risk among the Indian population. SETTINGS AND DESIGN: The study was conducted at Baby Oral Health Promotion Clinic, Department of Pediatrics, Tertiary Care Hospital using a cross-sectional study design. SUBJECTS AND METHODS: Data were collected using CAMBRA 123 and AAPD CRATs from 379 children aged 0-6 years. The caries risk of the children was recorded with each CRAT and a comparison was made between the two tools used. STATISTICAL ANALYSIS USED: The percentage of agreement and Cohen's kappa coefficient were used to know the agreement between the CAMBRA 123 and AAPD CRATs using the SPSS statistical tool. The significance level was set at 5% (α = 0.05). RESULTS: For children aged <2 years, the study showed slight agreement between the CAMBRA 123 and AAPD, whereas, for children more than 2 years, there was a fair agreement between the two methods which was statistically significant. This indicates that the agreement between the two methods is still not perfectly established, and AAPD CRA assigns a higher risk category than CAMBRA 123. CONCLUSIONS: CAMBRA 123 is a promising user-friendly quantitative method for CRA in clinical practice. Since there is ambiguity in assessing the caries risk in children <2 years, there is a need to establish a CRAT that can be used exclusively for children below 2 years.

Machine learning to predict untreated dental caries in adolescents.

OBJECTIVE: This study aimed to predict adolescents with untreated dental caries through a machine-learning approach using three different algorithms METHODS: Data came from an epidemiological survey in the five largest cities in Mato Grosso do Sul, Brazil. Data on sociodemographic characteristics, consumption of unhealthy foods and behaviours (use of dental floss and toothbrushing) were collected using Sisson's theoretical model, in 615 adolescents. For the machine learning, three different algorithms were used: (1) XGboost; (2) decision tree and (3) logistic regression. The epidemiological baseline was used to train and test predictions to detect individuals with untreated dental caries, through eight main predictor variables. Analyzes were performed using the R software (R Foundation for Statistical Computing, Vienna, Austria). The Ethics Committee approved the study.. RESULTS: For the 615 adolescents, xgboost performed better with an area under the curve (AUC) of 84% versus 81% for the decision tree algorithm. The most important variables were the use of dental floss, unhealthy food consumption, self-declared race and exposure to fluoridated water. CONCLUSIONS: Family health teams can improve the work process and use artificial intelligence mechanisms to predict adolescents with untreated dental caries, and, in this way, schedule dental appointments for the treatment of adolescents earlier.

Effect of bottled fluoridated water to prevent dental caries in primary teeth: study protocol for a phase 2 parallel-group 3.5-year randomized controlled clinical trial (waterBEST).

BACKGROUND: Fluoridation of public water systems is known as a safe and effective strategy for preventing dental caries based on evidence from non-randomized studies. Yet 110 million Americans do not have access to a fluoridated public water system and many others do not drink tap water. This article describes the study protocol for the first randomized controlled trial (RCT) of fluoridated water that assesses its potential dental caries preventive efficacy when delivered in bottles. METHODS: waterBEST is a phase 2b proof-of-concept, randomized, quadruple-masked, placebo-controlled, parallel-group trial designed to estimate the potential efficacy of fluoridated versus non-fluoridated bottled water to prevent dental caries incidence in the first 4 years of life. Two hundred children living in eastern North Carolina, USA, and aged 2-6 months at screening are being allocated at random in a 1:1 ratio to receive fluoridated (0.7 mg/L F) or non-fluoridated bottled water sourced from two local public water systems. Throughout the 3.5-year intervention, study water is delivered monthly in 5-gallon bottles to each child's home with instructions to use it whenever the child consumes water as a beverage or in food preparation. Parents are interviewed quarterly to monitor children's water consumption and health. At annual visits, the presence of dental caries is evaluated with a dental screening examination. Clippings from fingernails and toenails are collected to quantify fluoride content as a biomarker of total fluoride intake. The primary endpoint is the number of primary tooth surfaces decayed, missing, or filled due to dental caries measured by the study dentist near the time of the child's fourth birthday. Tooth decay is assessed at the threshold of macroscopic enamel loss. For the primary aim, a least-squares, generalized linear model will estimate efficacy and its one-tailed, upper 80% confidence limit. DISCUSSION: waterBEST is the first evaluation of a randomized intervention of fluoridated drinking water in bottles to prevent dental caries in the primary dentition. This innovative method of delivering fluoridated water has the potential to prevent early childhood caries in a large segment of the US population that currently does not benefit from fluoridated public water. TRIAL REGISTRATION: ClinicalTrials.gov NCT04893681. Registered on March 2022. Last update posted on 10 October 2023. https://clinicaltrials.gov/study/NCT04893681?cond=Dental%20Caries%20in%20Children&term=fluoride&locStr=North%20Carolina,%20USA&country=United%20States&state=North%20Carolina&distance=50&rank=1.

Development of short forms for screening children's dental caries and urgent treatment needs using item response theory and machine learning methods.

OBJECTIVES: Surveys can assist in screening oral diseases in populations to enhance the early detection of disease and intervention strategies for children in need. This paper aims to develop short forms of child-report and proxy-report survey screening instruments for active dental caries and urgent treatment needs in school-age children. METHODS: This cross-sectional study recruited 497 distinct dyads of children aged 8-17 and their parents between 2015 to 2019 from 14 dental clinics and private practices in Los Angeles County. We evaluated responses to 88 child-reported and 64 proxy-reported oral health questions to select and calibrate short forms using Item Response Theory. Seven classical Machine Learning algorithms were employed to predict children's active caries and urgent treatment needs using the short forms together with family demographic variables. The candidate algorithms include CatBoost, Logistic Regression, K-Nearest Neighbors (KNN), Naïve Bayes, Neural Network, Random Forest, and Support Vector Machine. Predictive performance was assessed using repeated 5-fold nested cross-validations. RESULTS: We developed and calibrated four ten-item short forms. Naïve Bayes outperformed other algorithms with the highest median of cross-validated area under the ROC curve. The means of best testing sensitivities and specificities using both child-reported and proxy-reported responses were 0.84 and 0.30 for active caries, and 0.81 and 0.31 for urgent treatment needs respectively. Models incorporating both response types showed a slightly higher predictive accuracy than those relying on either child-reported or proxy-reported responses. CONCLUSIONS: The combination of Item Response Theory and Machine Learning algorithms yielded potentially useful screening instruments for both active caries and urgent treatment needs of children. The survey screening approach is relatively cost-effective and convenient when dealing with oral health assessment in large populations. Future studies are needed to further leverage the customize and refine the instruments based on the estimated item characteristics for specific subgroups of the populations to enhance predictive accuracy.

Caries risk assessment by Caries Management by Risk Assessment (CAMBRA) Protocol among the general population of Pakistan-a multicenter analytical study.

Background: Caries risk (CR) assessment tools are used to properly identify individuals with caries risk and to improve preventive procedures and programs. A tool such as CAMBRA determines the precise protective factors of caries and identifies an individual's specific therapeutic intervention. The purpose of this study was to assess the caries risk using the CAMBRA protocol among the general population of Pakistan. Methods: This multicentre analytical study was conducted in ten dental hospitals in different provinces of Pakistan and the caries risk assessment was carried out using a questionnaire that was designed using the Caries Management by Risk Assessment (CAMBRA) protocol. All 521 participants were intra-orally examined to assess oral hygiene status and the presence of disease. Multiple logistic regression test was performed for analysis. Results: A higher number of participants (61.2%) were found to be in the moderate risk category of caries risk assessment. The males are 51% less likely to have caries compared to the females (AOR = 0.49, P = 0.081). The majority of participants (71.3%) had one or more disease indicators, with white spots and visible cavities. Those with visible, heavy plaque were 13.9 times more likely to have caries compared to those without (AOR = 13.92, P < 0.001). Those using calcium and phosphate during the last 6 months were 90% less likely to have caries compared to those not using them (AOR = 0.10, P < 0.001). There was no significant interaction between all eight risk factors retained in the final model (P > 0.05), the Hosmer and Lemeshow Test P < 0.001, classification accuracy = 87.1%, and AUC = 91.2%. Conclusion: The caries risk among the general population of Pakistan is moderate, with significant variation among age groups, education levels, and socioeconomic status.

Diagnosing and recording root caries: A survey among Swiss dentists.

OBJECTIVES: Despite the increase in the root caries prevalence, little is still known about how dentists manage this condition. The present study aimed to evaluate the knowledge of dentists on diagnosing and recording root caries lesions (RCL). METHODS: The survey consisted of three domains: (1) dentists' knowledge on diagnosing, recording and managing RCL; (2) information about their current general clinical routines; and (3) their demographics. The four Swiss Universities distributed the survey via e-mail lists for alumni or professionals participating in continuing education. The data was quality checked. Construct validity, internal reliability and intraclass correlation (ICC) were assessed. RESULTS: The survey was answered by 383 dentists from 25(out of 26) cantons [mean(SD) working experience: 22.5(12) years]. The majority replied that they see less than 5 patients with RCL per week, whereas 41 have at least 5 per week, and 40 % (157 dentists) do not distinguish RCL from coronal caries in their patients' medical records. When diagnosing active RCL, tactile sensation was the most predominant criterion (n = 380), whereas color (n = 224) and visual appearance (n = 129) of the lesion were less often selected. The most often chosen risk factors for RCL were poor oral hygiene and presence of biofilm.The responses were significantly influenced by the participants' place of education, their age and working area. CONCLUSION: The present survey highlights the huge diversity in diagnosing, recording and assessing risk factors of RCL. The benefits of an appropriate diagnosis, recording and management of risk factors of RCL should be highlighted in under- and postgraduate dental education. CLINICAL SIGNIFICANCE: A great diversity in diagnosing, recording and assessing risk factors of RCL was observed, which migh strongly impact how dentists manage RCL. The study emphasizes the necessity for intensive efforts to bridge the gap between guideline recommendations and their implementation in private dental practices.

Artificial neural network and convolutional neural network for prediction of dental caries.

Dental caries has high prevalence among kids and adults thus it has become one of the global health concerns. The current modern dentistry focused on the preventives measures to reduce the number of dental caries cases. The employment of machine learning coupled with UV spectroscopy plays a crucial role to detect the early stage of caries. Artificial neural network with hyperparameter tuning was employed to train spectral data for the classification based on the International Caries Detection and Assesment System (ICDAS). Spectra preprocessing namely mean center (MC), autoscale (AS) and Savitzky Golay smoothing (SG) were applied on the data for spectra correction. The best performance of ANN model obtained has accuracy of 0.85 with precision of 1.00. Convolutional neural network (CNN) combined with Savitzky Golay smoothing performed on the spectral data has accuracy, precision, sensitivity and specificity for validation data of 1.00 respectively. The result obtained shows that the application of ANN and CNN capable to produce robust model to be used as an early screening of dental caries.

Artificial Intelligence: A Mighty Adjunct for Caries Detection.

Articifial intelligence (AI) is impacting many aspects of people's lives today. In fields such as finance, manufacturing, agriculture, insurance, education, and healthcare, AI has been commissioned to cut costs, increase efficiency, and improve accuracy. Like many innovations, the use of AI can have both positive and potentially negative consequences. As an example, if used in dentistry to detect interproximal carious lesions, AI technology does not have the ability (at least not yet) to recognize the individual uniqueness of each patient. For instance, some patients are highly caries prone and may be best served by prophylactic intervention of even small borderline lesions, while other patients are very caries resistant and may simply require the monitoring of suspected carious lesions.

[Pathogenesis, diagnostic and therapeutic strategies for radiation-related caries].

Radiation-related caries is a common complication following head and neck tumor radiotherapy. It is a rapidly progressing and widespread destructive disease of tooth tissue after radiotherapy, which greatly affects the life quality of patients after radiotherapy. This article elucidates research progress in the pathogenic mechanisms, diagnosis and caries assessment, treatment, as well as prevention strategies for radiation-related caries, aiming to provide references for clinical prevention and treatment of radiation-related caries.

[Application and exploration of artificial intelligence for caries management].

With the advent of big data era and improvement of computer performance, the artificial intelligence (AI) technology has rapidly boosted in the field of stomatology. Dental caries is one of the cutting-edge research domains in stomatology. The application of AI in dental caries is expected to promote intelligent, precise and high-efficient diagnosis and treatment of caries. This article focuses on the application of AI in medical-aided diagnosis, treatment and risk prediction of caries and discusses their challenges.

Are salivary NO2- / NO2- and NO3- levels biomarkers for dental caries in children? Systematic review and meta-analysis.

The literature is conflicting regarding salivary nitrite (NO2-)/nitrite and nitrate (NO2- and NO3-) levels in children affected by dental caries. For this reason, a systematic review to provide a consensus on the subject was propose, whose objective is to verify whether these molecules could be used as biomarkers in children with caries. A comprehensive search was performed on online database and eleven articles were included in the meta-analysis. The methodological quality of studies was assessed by Newcastle-Ottawa Scale recommended for case-control studies and by AXIS tool for cross-sectional studies. Grading of Recommendations Assessment, Development and Evaluation was used for the assessment of the certainty of the evidence for each outcome. The results showed lower NO2- levels in the group of children affected by dental caries (SMD = -2.18 [-3.24, -1.13], p < 0.01). Age, saliva collection and methods of evaluation can impact the results. When evaluating the severity of the condition, an important variation was detected in relation to the different evaluation methods NO2-/NO2- and NO3-. In conclusion, based on the evidence presented, the results suggest that NO2- levels in saliva are a possible biomarker of dental caries. Results should be evaluated with caution due to the very low evidence from primary studies. Longitudinal studies are necessary to strengthen this hypothesis.

Sleep disorders, anxiety and obesity associated with untreated dental caries in children eight to ten years of age.

OBJECTIVE: To evaluate the presence of sleep disorders, obesity and anxiety associated with cavitated carious lesions in children aged 8 to 10 years. MATERIALS AND METHODS: A cross-sectional study was carried out in the Northeast of Brazil. The sample was comprised of 793 schoolchildren randomly selected from public and private schools. Calibrated examiners (Kappa >0.80) performed the clinical examination of dental caries using the International Caries Detection and Assessment System and applied the Revised Children's Manifest Anxiety Scale and the Sleep Disturbance Scale for Children questionnaires. The anthropometric variables evaluated were weight and height. Negative binomial regressions (α ≤ 0.05) were performed. A Directed Acyclic Graph was prepared using DAGitty software (version 3.0), to select the co-variables for the statistical fits. RESULTS: The prevalence of tooth decay was 52.8%. The mean number of tooth surfaces with cavitated caries was 2.2(2.8), 58.9% of the schoolchildren had some type of sleep disorder, while 20.2% were anxious and 29.1% were obese. Sleep disturbance (RR = 1.38; 95% CI: 1.05-1.83), general anxiety (RR = 1.71; 95% CI: 1.32-2.21), obesity (RR = 1.48; 95% CI: 1.17-1.86) were associated with dental caries in the final model. CONCLUSION: The presence of carious lesions was higher in children with sleep disorders, anxiety, obesity, and those who experienced dry mouth.

Dental Caries a Risk Factor for Intracerebral Hemorrhage.

INTRODUCTION: Streptococcus mutans is a known cause of dental caries that contains a collagen-binding protein, Cnm, and exhibits inhibition of platelet aggregation and matrix metalloproteinase-9 activation. This strain has been linked to aggravation of experimental intracerebral hemorrhage (ICH) and may be a risk factor for ICH. The purpose of this study was to test the association between dental caries and incident ICH. METHODS: The presence of dental caries and periodontal disease was assessed in subjects from the Dental Atherosclerosis Risk in Communities (DARIC) study without prior stroke or ICH. This cohort was followed for incident ICH over a period of 10 years. Cox regression was used to compute crude and adjusted hazards ratio from the dental assessment. RESULTS: Among 6,315 subjects, dental surface caries and/or root caries were recorded in 1,338 (27%) subjects. Of those, 7 (0.5%) had incident ICH over a period of 10 years following the visit 4 assessment. Of the remaining 4,977 subjects, 10 (0.2%) had incident ICH. Those with dental caries versus those without dental caries were slightly younger (mean age 62.0 ± 5.7 vs. 62.4 ± 5.6, p = 0.012), had a greater proportion of males (51 vs. 44%, p < 0.001), African Americans (44 vs. 10%, p < 0.001), and were hypertensive (42 vs. 31%, p < 0.001). The association between caries and ICH was significant (crude HR 2.69, 95% CI 1.02-7.06) and strengthened after adjustment for age, gender, race, education level, hypertension, and periodontal disease (adjusted HR 3.88, 95% CI 1.34-11.24). CONCLUSION: Dental caries is a potential risk for incident ICH after caries detection. Future studies are needed to determine if treatment of dental caries can reduce the risk of ICH.

Salivary elemental signature of dental caries: a systematic review and meta-analysis of ionomics studies.

Trace- and macro-chemical elements are crucial for cellular physiological functioning, and their alterations in biological fluids might be associated with an underlying pathological state. Hence, this study aimed to examine and summarize the published literature concerning the application of salivary ionomics for caries diagnosis. An extensive search of studies was conducted using PubMed, EMBASE, Web of Science, and Scopus, without any language and year restriction for answering the following PECO question: "In subjects (i.e., children, adolescents, or adults) with good systematic health, are there any variations in the salivary concentrations of trace- or macro-elements between caries-free (CF) individuals and caries-active (CA) subjects?" A modified version of the QUADOMICS tool was used to assess the quality of the included studies. The Review Manager Version 5.4.1. was used for data analyses. The analysis of salivary chemical elements that significantly differed between CF and CA subjects was also performed. Thirty-four studies were included, involving 2299 CA and 1669 CF subjects, having an age range from 3 to 64 years in over 16 countries. The meta-analysis revealed a statistically significant difference (p < 0.05) in the salivary levels of calcium, phosphorus, chloride, magnesium, potassium, sodium, and zinc between CA and CF subjects, suggesting higher levels of calcium, phosphorus, potassium, and sodium in CF subjects while higher levels of chloride, magnesium, and zinc in CA patients. Half of the included studies (17/34) were considered high quality, while the remaining half were considered medium quality. Only zinc and chloride ions were found to be higher significantly and consistent in CF and CA subjects, respectively. Conflicting outcomes were observed for all other salivary chemical elements including aluminum, bromine, calcium, copper, fluoride, iron, potassium, magnesium, manganese, sodium, ammonia, nitrite, nitrate, phosphorus, lead, selenium, and sulfate ions.