Measure Of Irregularity Research Articles

Nordhaus–Gaddum type results for graph irregularities

A graph whose vertices have the same degree is called regular. Otherwise, the graph is irregular. In fact, various measures of irregularity have been proposed and examined. For a given graph G=(V,E) with V={v1,v2,…,vn} and edge set E(G), di is the vertex degree where 1 ≤ i ≤ n. The irregularity of G is defined by irr(G)=∑vivj∈E(G)|di−dj|. A similar measure can be defined by irr2(G)=∑vivj∈E(G)(di−dj)2. The total irregularity of G is defined by irrt(G)=12∑vi,vj∈V(G)|di−dj|. The variance of the vertex degrees is defined var(G)=1n∑i=1ndi2−(2mn)2. In this paper, we present some Nordhaus–Gaddum type results for these measures and draw conclusions.

Cholesterol is Inefficiently Converted to Cholesteryl Esters in the Blood of Cardiovascular Disease Patients

Shotgun lipidomic analysis of 203 lipids in 13 lipid classes performed on blood plasma of donors who had just suffered an acute coronary syndrome (ACS, n = 74), or an ischemic stroke (IS, n = 21), or who suffer from stable angina pectoris (SAP, n = 78), and an age-matched control cohort (n = 52), showed some of the highest inter-lipid class correlations between cholesteryl esters (CE) and phosphatidylcholines (PC) sharing a common fatty acid. The concentration of lysophospatidylcholine (LPC) and ratios of concentrations of CE to free cholesterol (Chol) were also lower in the CVD cohorts than in the control cohort, indicating a deficient conversion of Chol to CE in the blood plasma in the CVD subjects. A non-equilibrium reaction quotient, Q′, describing the global homeostasis of cholesterol as manifested in the blood plasma was shown to have a value in the CVD cohorts (Q′ACS = 0.217 ± 0.084; Q′IS = 0.201 ± 0.084; Q′SAP = 0.220 ± 0.071) that was about one third less than in the control cohort (Q′Control = 0.320 ± 0.095, p < 1 × 10−4), suggesting its potential use as a rapid predictive/diagnostic measure of CVD-related irregularities in cholesterol homeostasis.

Motor activity patterns in acute schizophrenia and other psychotic disorders can be differentiated from bipolar mania and unipolar depression

The purpose of this study was to compare 24-h motor activity patterns between and within three groups of acutely admitted inpatients with schizophrenia and psychotic disorders (n = 28), bipolar mania (n = 18) and motor-retarded unipolar depression (n = 25) and one group of non-hospitalized healthy individuals (n = 28). Motor activity was measured by wrist actigraphy, and analytical approaches using linear and non-linear variability and irregularity measures were undertaken. In between-group comparisons, the schizophrenia group showed more irregular activity patterns than depression cases and healthy individuals. The schizophrenia and mania cases were clinically similar with respect to high prevalence of psychotic symptoms. Although they could not be separated by a formal statistical test, the schizophrenia cases showed more normal amplitudes in morning to evening mean activity and activity variability. Schizophrenia constituted an independent entity in terms of motor activation that could be distinguished from the other diagnostic groups of psychotic and non-psychotic affective disorders. Despite limitations such as small subgroups, short recordings and confounding effects of medication/hospitalization, these results suggest that detailed temporal analysis of motor activity patterns can identify similarities and differences between prevalent functional psychiatric disorders. For this purpose, irregularity measures seem particularly useful to characterize psychotic symptoms and should be explored in larger samples with longer-term recordings, while searching for underlying mechanisms of motor activity disturbances.

APPROXIMATE INTEGRATION FOR DETERMINING THE SURFACE ROUGHNESS

Measurement of surface irregularities, forming in aggregate its relief, belongs to linear-angular measurements. Their main feature is the smallness of the measured values. Measurements at production are subject to values: the heights of inequalities of 0.025 μm and steps – starting from 2 μm. A quantitative approach in analysis allows us to identify the optimal surface structure, which most closely meets the conditions of service material. It is worth noting that it is roughness, which has the strongest impact on the performance of engines of machines, as well as parts and components of various equipment. In case of roughness, as a rule, the parameter of the arithmetic mean deviation of the profile is used. Consideration of the mathematical aspects of data processing profilograms aimed at increasing the adequacy of the results. In the work the well-known formulas for determining the roughness of the surface of metals and alloys are analyzed, additional criteria for estimating microgeometry of surfaces are determined based on the methods of approximate integration, and the proposed correction of the formula for determining the mean arithmetic deviation of the investigated profile is determined. It is proposed to use the corrected formula, using the form factor k for practical calculations , where – amplitude values of deviations from the middle line of the profilogram, = 0,5 ... 0,67 – is chosen depending on the predominant form of the protrusions and depressions on the profilogram (triangles or curvilinear trapezes). The facts confirming the correctness of the correction of the calculation formula using are the relation between and . The process of determining the roughness of parts surfaces in the analysis of work profilograms based on the use of approximate integration, the application of the coefficient of form for projections and concaves on the profilogram in the formula for increasing the adequacy of determining the surface roughness by values and in a range of nominal values is investigated.

High frequency resonant response of a monopile in irregular deep water waves

Experiments with a weakly damped monopile, either fixed or free to oscillate, exposed to irregular waves in deep water, obtain the wave-exciting moment and motion response. The nonlinearity and peak wavenumber cover the ranges: $\unicode[STIX]{x1D716}_{P}\sim 0.10{-}0.14$ and $k_{P}r\sim 0.09{-}0.14$ where $\unicode[STIX]{x1D716}_{P}=0.5H_{S}k_{P}$ is an estimate of the spectral wave slope, $H_{S}$ the significant wave height, $k_{P}$ the peak wavenumber and $r$ the cylinder radius. The response and its statistics, expressed in terms of the exceedance probability, are discussed as a function of the resonance frequency, $\unicode[STIX]{x1D714}_{0}$ in the range $\unicode[STIX]{x1D714}_{0}\sim 3{-}5$ times the spectral peak frequency, $\unicode[STIX]{x1D714}_{P}$. For small wave slope, long waves and $\unicode[STIX]{x1D714}_{0}/\unicode[STIX]{x1D714}_{P}=3$, the nonlinear response deviates only very little from its linear counterpart. However, the nonlinearity becomes important for increasing wave slope, wavenumber and resonance frequency ratio. The extreme response events are found in a region where the Keulegan–Carpenter number exceeds $KC&gt;5$, indicating the importance of possible flow separation effects. A similar region is also covered by a Froude number exceeding $Fr&gt;0.4$, pointing to surface gravity wave effects at the scale of the cylinder diameter. Regarding contributions to the higher harmonic forces, different wave load mechanisms are identified, including: (i) wave-exciting inertia forces, a function of the fluid acceleration; (ii) wave slamming due to both non-breaking and breaking wave events; (iii) a secondary load cycle; and (iv) possible drag forces, a function of the fluid velocity. Also, history effects due to the inertia of the moving pile, contribute to the large response events. The ensemble means of the third, fourth and fifth harmonic wave-exciting force components extracted from the irregular wave results are compared to the third harmonic FNV (Faltinsen, Newman and Vinje) theory as well as other available experiments and calculations. The present irregular wave measurements generalize results obtained in deep water regular waves.

Digitized spiral analysis may be a potential biomarker for brachial dystonia

IntroductionObjective measures for detection and quantification of dystonic movements may guide both diagnosis and clinical monitoring. Digitized spiral analysis is a non-invasive method used to assess upper limb motor control in movement disorders and may have utility in dystonia. We aimed to determine if digitized spiral analysis can distinguish dystonia subjects from controls, and evaluated correlation with a validated clinical rating scale. MethodsKinematic, dynamic, and spatial attributes of Archimedean spirals drawn with an inking pen on a digitizing tablet were compared for participants with brachial dystonia and either Tor1A (DYT1) (n = 15) or THAP1 (DYT6) mutations (n = 12) and age and gender matched controls (n = 27) using Receiver Operator Characteristics (ROC) analysis. Spiral indices including an overall degree of severity (DoS) were also calculated and correlated with clinical severity ratings as measured by the Burke-Fahn-Marsden scale. ResultsDystonia spirals had significantly higher severity scores as well as higher measures of spiral irregularity compared to controls. ROC analysis demonstrated that the DoS score had good discriminative ability to distinguish dystonia spirals from controls, with an Area Under the Curve (AUC) of 0.87. Measures of spiral irregularity correlated with validated clinical rates of dystonia severity in the analyzed arm, with one particular index, Residue of Theta vs R, showing the highest correlation (r = 0.55, p = 0.005). ConclusionDigitized spiral analysis may be a promising non-invasive method to objectively quantify brachial dystonia. It may also be a useful way to monitor subtle changes in dystonia severity over time not captured with current clinical rating scales.

Analytic Synthesis of a Kalman Adaptive Filter on the Basis of Irregular Precise Measurements

The problem of construction of an adaptive discrete Kalman filter is analytically solved with the use of irregular precise measurements. It is shown that the possibility of irregular precise measurements makes it possible to precisely determine the parameters of the filter (gain and adaptation factor) within the stage of their appearance and guarantees the error of estimation equal to zero. The indicated reconstruction of the parameters of the estimation algorithm significantly improves its convergence.

Effects of vegetation structure and landscape complexity on insect parasitism across an agricultural frontier in Argentina

Insect parasitism patterns are influenced by vegetation structure and landscape complexity. Our objective was to examine the effects of vegetation structure and landscape complexity on parasitism based on direct measurements of structure and diversity indices as well as on metrics based on remote sensing using Quickbird images. We collected 2266 lepidopteran larvae and pupae, including different families and habits, to estimate parasitism, and recorded vegetation characteristics in five 100-m2 transects and 18 1ha-plots in the dry Chaco, Northwest Argentina. We calculated landscape metrics and semivariograms in the plots from the image. The plots represented four “complexity groups”: agricultural, riparian/hedgerow, bare ground, and forest plots. Mean parasitism in the study sites was 10.7% (min: 0%, max: 23%). Parasitism was highest in agricultural plots, lowest in forest plots, and intermediate in riparian/hedgerow and bare ground plots. The landscape model explained parasitism more than the vegetation model. The landscape final model included Normalized Difference Vegetation Index (NDVI) Range, a measure of landscape heterogeneity, and Mean Shape Index, a measure of patch shape irregularity, and their interaction. The vegetation model included basal area and the Coefficient of Variation of tree density among transects, a measure of tree spatial distribution within a plot. Our results agree with previous studies that found higher parasitism in agricultural vs. non-agricultural environments in the subtropics, while riparian/hedgerow plots were important for conserving parasitism, as reported for temperate environments. We showed that under-explored tools such as the semivariogram and satellite band combinations were useful for the assessment of parasitism and that studying vegetation and landscape complexity simultaneously can help us examine mechanisms in detail. The identified variables related to high parasitism should be used for image classifications with a functional approach.

Discriminative Spectral Pattern Analysis for Positive Margin Detection of Prostate Cancer Specimens using Light Reflectance Spectroscopy

ABSTRACTFor localized prostate cancer, one treatment is prostatectomy which surgically removes the prostate gland. However, some undetectable cancer cells may be left as positive surgical margins, leading to a high risk of cancer recurrence. It is highly desirable to develop a portable and accurate classification methodology that detects positive margins on human prostate specimens immediately after their removal during surgery. This study applied data mining techniques on the light reflectance spectroscopy (LRS) data taken from ex-vivo human specimens and developed a novel classification algorithm that could enable real-time, positive-margin identification during surgery.Specifically, the LRS measurements taken from human prostate specimens ex vivo were classified to normal or cancerous tissue with support vector machines and were also classified to normal, cancerous and transition-to-cancer class with an ensemble of trees. The data in this study were highly overlapped and imbalanced among classes. We solved the overlapping issue by defining a middle class (transition-to-cancer), and by optimizing a moving spectral window through the range of LRS. To solve the imbalanced problem, we removed irregular tissue measurements, followed by application of random undersampling from the majority class. We achieved sensitivity and specificity of 100% and 82% for binary classification.

Actigraphy as an objective intra-individual marker of activity patterns in acute-phase bipolar disorder: a case series

BackgroundActigraphy could be an objective alternative to clinical ratings of motor activity in bipolar disorder (BD), which is of importance now that increased activity and energy are added as cardinal symptoms of (hypo)mania in the DSM-5 and commonly used rating scales give inadequate information about motor symptoms. To date, most actigraphy studies have been conducted in groups and/or used mean activity levels as the variable of interest. The novelty of this case series is therefore to indicate the potential of actigraphy and non-parametric analysis as an objective and personalized marker of intra-individual activity patterns in different phases of BD. To our knowledge, this is the first case series that provides an objective assessment of non-linear dynamics in within-person activity patterns during acute BD episodes.ResultsWe report on three cases of bipolar I disorder with 24-h actigraphy recordings undertaken during the first few days of two or more separate admissions for an acute illness episode, including admissions for individuals in different phases of BD, or with different levels of severity in the same phase of illness. For each recording, we calculated mean activity levels over 24 h, but especially focused on key measures of variability and complexity in activity. Intra-individual activity patterns were found to be different according to phase of illness, but showed consistency within the same phase. With increasing psychotic symptoms, there was evidence of a lower overall level and greater irregularity in activity. As such, sample entropy (a measure of irregularity) may have particular utility in characterizing mania and psychotic symptoms, while assessment of the distribution of rest versus activity over 24 h may distinguish between phases of BD within an individual.ConclusionsThis case series indicates that objective, intra-individual, real-time recordings of patterns of activity may have clinical impact as a valuable adjunct to clinical observation and symptom ratings. We suggest that actigraphy combined with detailed mathematical analysis provides a biological variable that could become an important tool for developing a personalized approach to diagnostics and treatment monitoring in BD.

An Approximate Representation of the Fourier Spectra of Irregularly Sampled Multidimensional Functions: A Cost-Effective, Memory-Saving Algorithm

This article discusses how to estimate the Fourier spectra of irregularly sampled multidimensional functions in an approximate way, using current fast Fourier transform (FFT) algorithms. This estimate may be an alternative for more rigorous approaches when the inversion of huge matrices is prohibitively expensive. The approximation results from a Taylor expansion of the Fourier transform kernel, which is a series on the product of wavenumbers and displacements from centers of a grid where a regular, discrete Fourier transform (DFT) is defined. Convergence and efficiency, as well as some shortcuts for implementation, is indicated. The problem of finding a Fourier spectrum of a function given a finite set of irregular measurements is usually associated with the idea of regularization/interpolation. This, in turn, raises the question of representativeness of continuous functions via its discrete measurements. Although this question is central for the very Fourier spectrum estimation, the scope of this article will be restricted to the trigonometric interpolation, postponing representativeness issues. For the sake of simplicity, the proposed approximation is first derived for the one-dimensional (problem where most related aspects are more clearly stated. Then, extensions to higher dimensions are straightforwardly presented.

Effect of supplemental vibration on orthodontic treatment with aligners: A randomized trial.

Supplemental vibration has been reported to accelerate orthodontic tooth movement and reduce discomfort. Our purpose was to investigate the effects of AcceleDent on Invisalign treatment. This randomized clinical trial was carried out in 2 orthodontic private practices with a 1:1 allocation ratio. Adult patients who were beginning their orthodontic treatment were randomly allocated to either an active (A) or a sham (B) AcceleDent Auradevice (OrthoAccel Technologies, Inc. Houston, TX). All patients were placed on a 1-week aligner change regimen, and fit was evaluated every 3weeks. The outcomes were the ability to complete the initial set of aligners and the incisor irregularity measurements for those who completed their regimen of aligners. In addition, aligner compliance, pain levels, and oral health-related quality of life data were gathered from questionnaires. The subjects, investigators, and assessors were all blinded to the treatment arms. Twenty-seven subjects were randomized into 2 groups (A and B), 1 subject discontinued treatment, and 13 subjects were analyzed in each group. The Fisher exact test showed no significant difference in completion rates between the 2 groups (group A, 77%; group B, 85%; P=1). Independent-sample t tests showed no significant difference between the final irregularity index or change in irregularity index between the 2 groups. Compliance was similar in both groups. The Wilcoxon rank sum test showed minimal differences in pain levels. Quality of life responses were similar in both groups. No serious harm was observed. We found no evidence that the AcceleDent Aura device impacts the ability to complete a series of aligners with a 1-week change regimen or the final alignment achieved in adult patients. It also had no significant effect on the reduction of orthodontic pain or oral health-related quality of life parameters when used with Invisalign.

Fractal analysis of plaque border, a novel method for the quantification of atherosclerotic plaque contour irregularity, is associated with pro-atherogenic plasma lipid profile in subjects with non-obstructive carotid stenoses.

Background and aimsPlaque border irregularity is a known imaging characteristic of vulnerable plaques, but its evaluation heavily relies on subjective evaluation and operator expertise. Aim of the present work is to propose a novel fractal-analysis based method for the quantification of atherosclerotic plaque border irregularity and assess its relation with cardiovascular risk factors.Methods and resultsForty-two asymptomatic subjects with carotid stenosis underwent ultrasound evaluation and assessment of cardiovascular risk factors. Total, low-density lipoprotein (LDL), high-density lipoprotein (HDL) plasma cholesterol and triglycerides concentrations were measured for each subject. Fractal analysis was performed in all the carotid segments affected by atherosclerosis, i.e. 147 segments. The resulting fractal dimension (FD) is a measure of irregularity of plaque profile on long axis view of the plaque. FD in the severest stenosis (main plaque FD,mFD) was 1.136±0.039. Average FD per patient (global FD,gFD) was 1.145±0.039. FD was independent of other plaque characteristics. mFD significantly correlated with plasma HDL (r = -0.367,p = 0.02) and triglycerides-to-HDL ratio (r = 0.480,p = 0.002).ConclusionsFractal analysis is a novel, readily available, reproducible and inexpensive technique for the quantitative measurement of plaque irregularity. The correlation between low HDL levels and plaque FD suggests a role for HDL in the acquisition of morphologic features of plaque instability. Further studies are needed to validate the prognostic value of fractal analysis in carotid plaques evaluation.

Two-dimensional multiscale entropy analysis: Applications to image texture evaluation

Complexity measures, defined as measures of irregularity over time scales, are the subject of a growing number of studies as the information they reveal can find utility in a large field of applications. One of the most popular complexity measures is the multiscale entropy. Nevertheless, more and more algorithms dedicated to complexity analyses are proposed to improve the existing ones. However, such measures are available only for one-dimensional time series. For bidimensional data (images), no equivalent algorithm has been proposed to analyze irregularity over spatial scales. We herein introduce a new framework that extends the one-dimensional multiscale entropy (MSE1D) to the bidimensional case (MSE2D). Moreover, a variant of MSE2D is also ModMSE2D). The two new algorithms are tested as new texture analysis frameworks. They are applied to simulated and real data. Our results show that, compared with other existing texture analysis algorithms, MSE2D and ModMSE2D are suitable and powerful tools for image analysis and classification according to their texture patterns. While MSE2D is computationally faster than ModMSE2D, ModMSE2D is more robust to small image sizes. The two methods present interesting performances, and can be as useful as their unidimensional versions in two-dimensional applications.

The probability distributions and fractal dimension of sunspot cycles associated with ENSO phenomena

Various methods have been used to secure the certainty of significant relations among the sunspot cycles and some of the terrestrial climate parameters such as temperature, rainfall, and ENSO. This study investigates the behavior of ENSO cycles and mean monthly sunspot cycles. Sunspot cycles range from 1755 to 2016 whereas, ENSO cycles range from 1866 to 2012. In this regard, the appropriateness of distributions is investigated with the help of Kolmogorov-Smirnov D, Anderson-Darling, and chi-square tests. It is found that most of the sunspot cycle follows generalized Pareto distribution whereas, generalized extreme value distribution was found appropriate for ENSO cycles. Probability distribution is used to analyze the behavior of each sunspot cycle and ENSO cycle separately. Probability distribution indicates the tail behavior of each cycle; tail explored correlation cycles. Furthermore, self-similar and self-affine fractal dimension methods are used to compute Hurst exponents to determine the persistency of the available data. Fractal dimension has an ability to study the complexity involved in sunspot and ENSO cycles. The fractal dimension and Hurst exponent describe persistency (smoothness) and complexity of data. Hurst exponent measures long-term behavior of time series, making it more helpful for forecasting. This is the measure of regularity or irregularity (chaos) of the time function in the form of their persistency or anti-persistency, respectively. Hurst exponents are computed using rescaled range analysis method and box counting methods. Both these methods are suitable for long-term forecasting. The results of this study confirm that during the period 1980–2000, ENSO cycles were very active. Simultaneously, ENSO was active for the periods 1982–1983, 1986–1987, 1991–1993, 1994–1995, and 1997–1998; these periods include two strongest periods of the century viz., 1982–1983 and 1997–1998. Sunspot cycles and ENSO cycles both were found to be persistent. Self-similar fractal dimensions exhibited a better persistency and a better correlation as compared to self-affine fractal dimension. This research is a part of a larger research project investigating the correlation of sunspot cycles and ENSO cycles, and the influence of ENSO cycles on variations of the local climatic parameters which in turn depends on solar activity changes.

Carotid Artery Wall Imaging: Perspective and Guidelines from the ASNR Vessel Wall Imaging Study Group and Expert Consensus Recommendations of the American Society of Neuroradiology.

Identification of carotid artery atherosclerosis is conventionally based on measurements of luminal stenosis and surface irregularities using in vivo imaging techniques including sonography, CT and MR angiography, and digital subtraction angiography. However, histopathologic studies demonstrate considerable differences between plaques with identical degrees of stenosis and indicate that certain plaque features are associated with increased risk for ischemic events. The ability to look beyond the lumen using highly developed vessel wall imaging methods to identify plaque vulnerable to disruption has prompted an active debate as to whether a paradigm shift is needed to move away from relying on measurements of luminal stenosis for gauging the risk of ischemic injury. Further evaluation in randomized clinical trials will help to better define the exact role of plaque imaging in clinical decision-making. However, current carotid vessel wall imaging techniques can be informative. The goal of this article is to present the perspective of the ASNR Vessel Wall Imaging Study Group as it relates to the current status of arterial wall imaging in carotid artery disease.

Fourier transforms of irregular mixed homogeneous hypersurface measures

AbstractWith the help of Van der Corput lemmas, decay estimates are proven for Fourier transforms of mixed homogeneous hypersurface measures with densities that can be quite irregular. The primary results are local in nature, but can be extended to global theorems in an appropriate sense. The estimates are sharp for a certain range of indices in the theorems.

Online Classification of Road Roughness Conditions with Vehicle Unsprung Mass Acceleration by Sliding Time Window

Suspension control systems are in need for more information of road roughness conditions to improve their performance under different roads. Existing methods of gauging road roughness are limited, and they usually involve visual inspections or special vehicles equipped with instruments that can gauge physical measurements of road irregularities. This paper proposes data collection for a period of a time from accelerometers fixed on unsprung mass and uses the mean square values of this datasets divided by vehicle speed to classify the roughness conditions of a section of a road. This approach is possible due to the existence of relationships between the power spectral densities of the road surface, unsprung mass accelerations via a transfer function, and vehicle speed. This paper gave the relationship between the resolution of road roughness classification and the length of time‐window and suggestions about choosing the appropriate time‐window length on the balance of road roughness resolution and classification delay. Moreover, to enhance the stability of classification, the influence of damping parameters of vehicle suspension on the classification output is studied, and a classification method of road roughness is proposed based on neural network and damping coefficient correction.

Ionospheric Irregularities at Mars Probed by MARSIS Topside Sounding

AbstractThe upper ionosphere of Mars contains a variety of perturbations driven by solar wind forcing from above and upward propagating atmospheric waves from below. Here we explore the global distribution and variability of ionospheric irregularities around the exobase at Mars by analyzing topside sounding data from the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) instrument on board Mars Express. As irregular structure gives rise to off‐vertical echoes with excess propagation time, the diffuseness of ionospheric echo traces can be used as a diagnostic tool for perturbed reflection surfaces. The observed properties of diffuse echoes above unmagnetized regions suggest that ionospheric irregularities with horizontal wavelengths of tens to hundreds of kilometers are particularly enhanced in the winter hemisphere and at high solar zenith angles. Given the known inverse dependence of neutral gravity wave amplitudes on the background atmospheric temperature, the ionospheric irregularities probed by MARSIS are most likely associated with plasma perturbations driven by atmospheric gravity waves. Though extreme events with unusually diffuse echoes are more frequently observed for high solar wind dynamic pressures during some time intervals, the vast majority of the diffuse echo events are unaffected by varying solar wind conditions, implying limited influence of solar wind forcing on the generation of ionospheric irregularities. Combination of remote and in situ measurements of ionospheric irregularities would offer the opportunity for a better understanding of the ionospheric dynamics at Mars.

Assessment of periodontal status among the outpatients attending private university dental clinics in Riyadh city, Saudi Arabia

Aim of the Study: The study aims to evaluate the prevalence of gingivitis and periodontitis among dental outpatients attending Munisiya Clinics of Riyadh Elm University using CPI criteria and also to compare the results with age, gender, systemic condition, smoking, and the use of oral hygiene measures. Materials and Methods: The periodontal status of 214 (90 male and 124 female) patients selected from outpatient's clinics in Munisiya Campus of Riyadh Elm University was evaluated according to the Community Periodontal Index (CPI) criteria. A close-ended, self-administered questionnaire recorded the patient's personal characteristics (age, gender, systemic condition, smoking, and the use of oral hygiene measures). The study population comprised three age groups – Group I: consisted of 148 patients aged 20–34 years old, Group II: consisted of 39 patients aged 35–49 years old, and Group III: consisted of 27 patients aged 50–64 years old. Data were collected tabulated and statistically analyzed to compare between all groups. Results: Our results showed that age and smoking status were considered significant factors associated with periodontitis. Furthermore, the highest prevalence of gingivitis was among younger age groups, while the highest prevalence of periodontitis was among older age groups. Furthermore, the highest prevalence of gingivitis and periodontitis was seen among males compared to female population. Conclusions: Smoking and diabetes mellitus were strongly associated with periodontitis. Moreover, irregular oral hygiene measures were considered among the risk factors of gingivitis and periodontitis.