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In the study of age estimation in living individuals, a lot of data needs to be analyzed by mathematical statistics, and reasonable medical statistical methods play an important role in data design and analysis. The selection of accurate and appropriate statistical methods is one of the key factors affecting the quality of research results. This paper reviews the principles and applicable principles of the commonly used medical statistical methods such as descriptive statistics, difference analysis, consistency test and multivariate statistical analysis, as well as machine learning methods such as shallow learning and deep learning in the age estimation research of living individuals, and summarizes the relevance and application prospects between medical statistical methods and machine learning methods. This paper aims to provide technical guidance for the age estimation research of living individuals to obtain more scientific and accurate results.
Subject(s)
Machine Learning , Humans , Age Determination by Skeleton/methods , Multivariate Analysis , Age Determination by Teeth/methodsABSTRACT
PURPOSE: To compute reference centiles for 5- and 30-m sprint times relative to chronological and skeletal age in youth soccer players. Subsequently, to compare individual's sprint performance scores derived from the chronological and skeletal age reference centiles. METHODS: Sprint times were collected for a sample of male U11 to U19 soccer players (n = 1745 data points). Skeletal age data were available for a subsample (n = 776 data points). Reference centiles were fitted using generalized additive models for location, scale, and shape. Individual z scores relative to chronological and skeletal age reference centiles were computed and compared for each maturity group (late, on-time, early, and very early) using standardized mean differences (SMD). RESULTS: Reference centiles for chronological age increased more rapidly between 10.5 and 15.5 years, while reference centiles for skeletal age increased more rapidly between 13.0 and 16.5 years. Differences in chronological and skeletal z scores for very early (SMD: -0.73 to -0.43) and late (SMD: 0.58 to 1.29) maturing players were small to large, while differences for early (SMD: -0.30 to -0.19) and on-time (SMD: 0.16 to 0.28) were trivial to small. CONCLUSION: Reference centiles provide a valuable tool to assist the evaluation of sprint performance in relation to chronological and skeletal age for talent identification purposes in youth soccer players.
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The contributions of height, weight and skeletal age (SA) to strength and motor performances of male soccer players 9-12 (n = 60) and 13-16 (n = 52) years were estimated. SA was assessed with the Fels method, and was expressed as the standardized residual of the regression of SA on chronological age CA (SAsr). Static strength (right + left grip), speed (5 m, 20 m sprints), acceleration (10 to 20 m), agility (figure-of-eight run), explosive strength (vertical jump) and endurance (yo-yo intermittent shuttle run, 13-16 years only) were measured. Hierarchical multiple regression was used. The interaction of SAsr with body size (height and height x weight interaction) explained most of the variance in strength in both age groups, 9-12 years (51.6%) and 13-16 years (56.7%), and in speed (31.4%, 38.7%), acceleration (39.6%), and explosive strength (32.6%) among players 13-16 years. In contrast, SAsr alone explained limited amounts of variance in strength, speed, acceleration and vertical jump among players 9-12 years (1.4-4.5%) and 13-16 years (0-0.5%). Results for agility varied with CA group, while SAsr per se was the primary contributor to endurance among players 13-16 years (18.5% of the variance). Although the influence of body size and skeletal maturity status on performances was significant, the explained variance differed among tasks and between CA groups, and suggested a role for other factors affecting performances of the soccer players.
Subject(s)
Athletic Performance , Soccer , Male , Humans , Middle Aged , Child , Body Size , Nutritional Status , Multivariate AnalysisABSTRACT
Age estimation in living individuals around the age of 18 years is medico-legally important in undocumented migrant cases and in countries like South Africa where many individuals are devoid of identification documents. Establishing whether an individual is younger than 18 years largely influences the legal procedure that should be followed in dealing with an undocumented individual. The aim of this study was to combine dental third molar and anterior inferior apophysis ossification data for purposes of age estimation, by applying a decision tree analysis. A sample comprising of 871 black South African individuals (n = 446 males, 425 = females) with ages ranging between 15 and 24 years was analyzed using panoramic and cephalometric radiographs. Variables related to the left upper and lower third molars and cervical vertebral ring apophysis ossification of C2, C3, and C4 vertebrae analyzed in previous studies were combined in a multifactorial approach. The data were analyzed using a pruned decision tree function for classification. Male and female groups were handled separately as a statistically significant difference was found between the sexes in the original studies. A test sample of 30 individuals was used to determine if this approach could be used with confidence in estimating age of living individuals. The outcomes obtained from the test sample indicated a close correlation between the actual ages (in years and months) and the predicted ages (in years only), demonstrating an average age difference of 0.47 years between the corresponding values. This method showed that the application of decision tree analysis using the combination of third molar and cervical vertebral development is usable and potentially valuable in this application.
Subject(s)
Age Determination by Teeth , Black People , Female , Humans , Male , Age Determination by Teeth/methods , Cervical Vertebrae/diagnostic imaging , Decision Trees , Molar, Third/diagnostic imaging , Radiography, Panoramic , South Africa , Adolescent , Young AdultABSTRACT
The advent of artificial intelligence (AI) in medicine has transformed various medical specialties, including orthodontics. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. Its usage in orthodontic practices worldwide has increased with the availability of various AI applications and tools. This review explores the principles of AI, its applications in orthodontics, and its implementation in clinical practice. A comprehensive literature review was conducted, focusing on AI applications in dental diagnostics, cephalometric evaluation, skeletal age determination, temporomandibular joint (TMJ) evaluation, decision making, and patient telemonitoring. Due to study heterogeneity, no meta-analysis was possible. AI has demonstrated high efficacy in all these areas, but variations in performance and the need for manual supervision suggest caution in clinical settings. The complexity and unpredictability of AI algorithms call for cautious implementation and regular manual validation. Continuous AI learning, proper governance, and addressing privacy and ethical concerns are crucial for successful integration into orthodontic practice.
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Forensic age assessments are crucial in the evaluation of criminal responsibility and preventing false age claims. Of all the methods available, the Greulich and Pyle (GP) atlas is most commonly used for age estimation purposes. Therefore, the current study sought to analyze the reliability and applicability of the GP standard and, additionally, to determine any possible association between the socioeconomic status (SES), food habits, and estimated skeletal maturity in the North Indian population. The study included 627 (334 males and 293 females) healthy children up to 19 years of age with varying SES and food habits. The skeletal age (SA) was estimated by three different evaluators using the GP atlas. The chronological mean age (CA) and SA were compared in different age cohorts. A paired t-test and a Pearson chi-square test were applied to show the difference between CA and estimated SA and the association of skeletal maturity with SES and food habits. The estimated skeletal age in males was retarded by 0.142 years or 1.72 months (p ≤ 0.05), whereas in females, it was retarded by 0.259 years or 3.12 months (p ≤ 0.05). In males, the GP method has significantly underestimated SA in age cohorts 3-4, 4-5, 6-7, 7-8, 8-9, and 12-13, whereas it overestimated in 10-11 and 18-19 years. However, in females, the SA was significantly underestimated in age groups 10-11, 12-13, and 14-15, respectively. Estimated skeletal maturity had no significant association with SES and food habits. The current study concludes that the GP atlas may not be applicable to North India's population. The observed difference in assessed skeletal maturity may be due to geographical region, genetics, hormonal effects, etc., which require further investigation. Hence, population-specific standards are necessary to determine the bone age of Indian children accurately.
Subject(s)
Age Determination by Skeleton , Asian People , Child , Male , Female , Humans , Infant , Reproducibility of Results , Age Determination by Skeleton/methodsABSTRACT
OBJECTIVE: In children with obstructive sleep apnea (OSA) who underwent adenotonsillectomy (AT), we measured body height and weight using standard deviation (SD) scores, insulin-like growth factor 1 (IGF-1), and skeletal age using carpal radiography. We then compared these values before and after surgery with the aim of investigating postoperative improvements in growth hormone (GH) deficiency. METHODS: Subjects comprised 35 children between 2 and 9 years of age (21 boys, 14 girls; mean age, 5.85 ± 1.75 years). Respiratory event index (REI), 3 % oxygen desaturation index (3 % ODI), height SD score, body mass index (BMI) percentile, blood IGF-1 level, and skeletal age from carpal radiographs were measured before surgery and both 3 and 12 months after surgery, and compared. RESULTS: Height SD score improved significantly from preoperatively (-0.44 ± 1.13) to both 3 months postoperatively (-0.22 ± 1.14) and 12 months postoperatively (-0.13 ± 0.94). However, no significant improvement in height SD score was seen from 3 months to 12 months after AT. BMI percentile improved significantly from preoperatively (35.6 ± 26.7) to both 3 months postoperatively (44.7 ± 26.5) and 12 months postoperatively (49.1 ± 22.15), with significant improvement also seen from 3 months to 12 months after AT. SD score for IGF-1 showed significant improvement from before (-0.57 ± 1.00) to 12 months after surgery (-0.12 ± 0.89). No significant improvement in the difference between skeletal and chronological ages was seen from before to after surgery, but the number of patients for whom skeletal age normalized from before to after surgery increased significantly (74.3 % vs. 94.3 %), and the number with advanced or delayed skeletal age decreased significantly (25.7 % vs. 5.7 %) CONCLUSION: Early improvements can be obtained with surgical treatment in children with OSA who have short height and poor weight gain due to GH deficiency.
Subject(s)
Sleep Apnea, Obstructive , Tonsillectomy , Child , Male , Female , Humans , Child, Preschool , Infant , Insulin-Like Growth Factor I , Age Determination by Skeleton , Adenoidectomy , Sleep Apnea, Obstructive/surgeryABSTRACT
OBJECTIVE: The objective of the study was to determine if support vector regression (SVR) models could enhance the accuracy of skeletal age estimation compared to original metrics. METHOD: The study used a dataset of 5,018 individuals from Wuhan, spanning ages 1 to 17. Optimal model parameters were found using cross-validation and grid search techniques. The study compared SVR-based bone age assessment metrics with original metrics and evaluated the performance of the SVR model across different sample sizes. RESULTS: The findings unequivocally demonstrated SVR's superior reliability over original metrics in assessing bone age among children in central China. Regardless of the training set size, constructing SVR models based on TW3, CHN05, or a combination of TW3, CHN05, and GP consistently results in top-tier predictive accuracy. CONCLUSION: This research highlights SVR's potential for accuracy improvement and robustness with limited datasets.
Subject(s)
Age Determination by Skeleton , Child , Humans , Age Determination by Skeleton/methods , Reproducibility of Results , ChinaABSTRACT
OBJECTIVES: The purpose of this study was to examine longitudinal growth changes in physical characteristics, muscle-tendon structure properties, and skeletal age in preadolescent boys and to compare the relationship between the changes in physical characteristics and muscle-tendon properties and the changes in chronological and skeletal ages. METHODS: Fourteen prepubescent boys (10.9 ± 1.1 years old at the onset of the study) participated in this study over two years (yearly). Maximal muscle strength and maximal strain of tendon structure during ramp isometric contraction and muscle and tendon thickness for knee extensors and plantar flexors were measured. In addition, skeletal age was assessed using Tanner-Whitehouse three method. RESULTS: Changes in height, thigh length, and lower leg length were highly correlated with changes in skeletal age but not chronological age. However, changes in the morphological and mechanical properties of muscle and tendon structure were not significantly associated with changes in chronological and skeletal ages. CONCLUSION: The present preliminary results suggest that longitudinal growth changes in the long-axis of the body are highly correlated with skeletal age change, whereas those in the muscle-tendon structure properties were not.
Subject(s)
Age Determination by Skeleton , Muscle, Skeletal , Male , Humans , Child , Muscle, Skeletal/physiology , Longitudinal Studies , Tendons/diagnostic imaging , Tendons/physiology , Knee , Isometric Contraction/physiologyABSTRACT
A common clinical method for identifying anomalies in bone growth in infants and newborns is skeletal age estimation with X-ray images. Children's bone abnormalities can result from several conditions including wounds, infections, or tumors. One of the most frequent reasons for bone issues is that most youngsters are affected by the slow displacement of bones caused by pressure applied to the growth plates as youngsters develop. The growth plate can be harmed by a lack of blood supply, separation from other parts of the bone, or slight misalignment. Problems with the growth plate prevent bones from developing, cause joint distortion, and may cause permanent joint injury. A significant discrepancy between the chronological and assessed ages may indicate a growth problem because determining bone age represents the real level of growth. Therefore, skeletal age estimation is performed to look for endocrine disorders, genetic problems, and growth anomalies. To address the bone age assessment challenge, this study uses the Radiological Society of North America's Pediatric Bone Age Challenge dataset which contains 12,600 radiological images of the left hand of a patient that includes the gender and bone age information. A bone age evaluation system based on the hand skeleton guidelines is proposed in this study for the detection of hand bone maturation. The proposed approach is based on a customized convolutional neural network. For the calculation of the skeletal age, different data augmentation techniques are used; these techniques not only increase the dataset size but also impact the training of the model. The performance of the model is assessed against the Visual Geometry Group (VGG) model. Results demonstrate that the customized convolutional neural network (CNN) model outperforms the VGG model with 97% accuracy.
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OBJECTIVES: Greulich-Pyle (GP) is one of the most used method for bone age determination (BAD) in various orthopedic, pediatric, radiological, and forensic situations. We aimed to investigate the inter- and intra-observer reliability of the GP method between the most relevant disciplines and its applicability to the Turkish population. METHODS: One-hundred and eighty (90 boys, 90 girls) patients with a chronological age younger than 18 (mean 9.33) were included. X-rays mixed by the blinded investigator were evaluated by two orthopedists, two radiologists, and two pediatric endocrinologists to determine skeletal age according to the GP atlas. A month later the process was repeated. As a statistical method, Paired t-test was used for comparison, an Intraclass Correlation Coefficients test was used for reliability and a 95â¯% confidence interval was determined. Results were classified according to Landis-Koch. RESULTS: All results were consistent with chronological age (p<0.001), according to the investigators' evaluations compared with chronological age. At the initial evaluation, the interobserver reliability of the method was 0.999 (excellent); at the second evaluation, the interobserver reliability was 0.997 (excellent). The intra-observer reliability of the method was 'excellent' in all observers. When results were separately evaluated by gender, excellent intraobserver correlation and excellent correlation with chronological age were found among all researchers (>0.9). When X-rays were divided into three groups based on age ranges and evaluated, 'moderate' and 'good' correlations with chronological age were obtained during the peripubertal period. CONCLUSIONS: The GP method used in skeletal age determination has excellent inter- and intra-observer reliability. During the peripubertal period, potential discrepancies in bone age assessments should be kept in mind. This method can be used safely and reproducibly by the relevant specialists.
Subject(s)
Age Determination by Skeleton , Bone and Bones , Male , Female , Humans , Child , Reproducibility of Results , Age Determination by Skeleton/methods , RadiographyABSTRACT
Introduction: The planning of effective orthodontic therapy greatly benefits from an understanding of the skeletal maturation and stage of growth of the patients seeking orthodontic treatment. However, the patient's various craniofacial structures have varying levels of growth potential. The patient is exposed to additional radiation when hand-wrist radiographs are regularly used to forecast growth. As an alternative, cervical vertebrae in the lateral cephalograph have been suggested. When arranging orthodontic treatment for growing children, it is important to take into account the pubertal growth spurt, which is a crucial time in therapy. Conclusion: Finding out how much growth a patient with skeletal discrepancy would experience during adolescence is one of the key goals of conducting a hand and wrist radiograph.
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The aim of the present study was to develop a specific formula by measuring the developing teeth, carpal bones, and epiphyses of the ulna and radius to determine the chronological age in Turkish children. The left developing permanent mandibular teeth were evaluated, and the number of teeth with closed apex was recorded. The distance between the inner sides of open apex/apices was measured by using the ImageJ program and divided by the tooth length. The sum of the normalized open apices was also calculated. The carpal area (Ca), covering the epiphyses of ulna and radius and the carpal bones, was measured on the X-rays of left hand. The areas of each carpal bone and epiphyses of the ulna and radius were measured, and these measurements were added together to obtain the bone area (Bo). The Bo/Ca ratio between the total area of carpal bones and the carpal area was calculated to normalize the measurements. The accuracy of the equations formulated by Cameriere was evaluated, and a new regression equation was developed accordingly. The new formula showed no statistically significant difference between the chronological and the estimated age for females, males, and total sample. The new formula, which hit the age with 72.80% accuracy, was more successful in predicting chronological age than other adjusted regression equations. The new regression model, created for the Turkish children by using both developing teeth and hand-wrist bones, was considerably successful in estimating the chronological age.
Subject(s)
Age Determination by Teeth , Carpal Bones , Male , Female , Child , Humans , Radius/diagnostic imaging , Radius/anatomy & histology , Age Determination by Skeleton/methods , Forensic Anthropology/methods , Ulna/diagnostic imaging , Ulna/anatomy & histology , Carpal Bones/diagnostic imaging , Carpal Bones/anatomy & histology , Epiphyses/diagnostic imaging , Age Determination by Teeth/methods , Radiography, PanoramicABSTRACT
BACKGROUND: Recently, it was proposed to estimate age from the biometric information of hand bones. We observed that these estimations became less precise as children get older, especially from the age of 13-15 years. OBJECTIVE: This study aimed to evaluate the influence of considering sex for age estimation based on hand bones biometrics. MATERIALS AND METHODS: The study sample consisted of metacarpals and proximal phalanges measurements collected on 1003 medical images performed at Nancy and Marseille Hospitals of individuals aged under 21 years. This sample was divided into two subgroups delineated by the age of 13, as it is a relevant legal threshold for most European countries. First, the influence of sex on the hand bones biometrics and on the estimated age was evaluated. Then, based on these results, new sex-specific age estimation formulas were constructed from linear models and their precision was assessed using residual analysis, in comparison with previous global formulas. RESULTS: An influence of sex was only highlighted from the age of 13 and for the total study sample. Thus, new sex-specific age estimation formulas were built for the [1-21] global sample and the [13-21] subsample. Even though the differences with the previous formulas were minor, age was more accurately estimated when sex was considered. CONCLUSION: Considering sex in age estimation is relevant when relying on hand bone biometrics. A new tool was proposed to select the most appropriate age estimation formula, based on the discriminant analysis result and the a priori knowledge of the sex.
Subject(s)
Hand Bones , Male , Child , Female , Humans , Aged , Adolescent , Hand Bones/diagnostic imaging , Discriminant Analysis , Biometry , EuropeABSTRACT
This paper presents a retrospective analysis of postmortem computed tomography (PMCT) scans of secondary ossification centers in the medial clavicular epiphysis, iliac crest apophysis, proximal humeral epiphysis, distal femoral epiphysis, proximal tibial epiphysis, and distal tibial epiphysis. At the same time, we analyzed PMCT scans of the maxillary and mandibular incisors, canines, premolars, and molars. We assessed 203 corpses, whose age ranged from 2 to 30 years, including 156 males and 47 females. The purpose of our study was to compare the processes of secondary ossification center fusion and permanent tooth maturation. Our research hypothesis was that certain stages of skeletal and dental maturation occur along consistent timelines that can be related to the chronological age. Secondary ossification center fusion was evaluated based on Kreitner and also McKern and Steward's classifications. The process of permanent tooth maturation was evaluated with Demirjian's method. Spearman's correlation coefficients (Rho) were positive in all analyses, which indicates that epiphyseal fusion progresses with age. The strongest relationship between the age and the stages of ossification was observed in the proximal tibial epiphysis (p < 0.001; Rho = 0.93) in females and in the medial clavicular epiphysis (p < 0.001; Rho = 0.77) in males. Studies show the importance of concomitant analysis of skeletal and dental maturation with a subsequent comparison of the results to achieve a greater precision in age estimation. A comparison of the results obtained in the study population of Polish children, adolescents, and young adults with the results of other studies in populations of similar ages showed a number of similarities in the time windows of dental and skeletal maturation. These similarities may help in age estimation.
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BACKGROUND: In Mongolian-origin ethnic groups digit ratio (2D:4D; a proxy for prenatal sex-steroids) is sexually dimorphic (males < females), as reported for other ethnicities. Most studies measured 2D:4D from soft tissue (directly from the digits, or indirectly from hand scans), or from radiographs. Evidence on the correspondence of 2D:4D measurements from soft tissue with measurements from radiographic images is scarce and has not been reported for a Mongolian-origin sample. In addition, previous research has not considered relationships between 2D:4D and measures of skeletal maturity. AIM: To examine (i) associations between 2D:4D measured directly from the palms with those obtained from radiographic images of the same individuals in a sample of children and adolescents from the Tuvan population in Siberia (Russian Federation), and ii) associations between 2D:4D measurements with chronological and skeletal age. SUBJECTS AND METHODS: Participants were Tuvan boys and girls aged 7 to 18 years. 2D:4D of the right and left hand was measured from soft tissue (directly from the palm) and compared with radiographic images (left hand only). In addition to finger length 2D:4D, we examined 2D:4D of the phalanges from measurements of radiographs. Skeletal age was assessed using the Tanner-Whitehouse method. RESULTS: Sex differences (boys < girls) in measurements of 2D:4D from soft tissue and radiographs were found for total finger length and phalanges. In addition, 2D:4D measurements from radiographs correlated positively and significantly with those obtained from soft tissue. Sex predicted 2D:4D measurements from soft tissue and radiographs, but no effects of chronological/skeletal age and body height were detected. In girls (but not in boys), earlier skeletal maturity (relative to chronological age) was associated with higher 2D:4D in soft tissue measurements of both hands, radiographic 2D:4D, and 2D:4D of the proximal phalanges. CONCLUSION: Consistent with reports from other ethnic groups, 2D:4D in young Tuvans was sexually dimorphic, with boys having lower 2D:4D than girls. For girls, higher 2D:4D was found for participants whose skeletal age was more advanced than chronological age. This finding was obtained from direct soft tissue and indirect radiographic measurements. Age and body height were not associated with 2D:4D, which suggests differences in hormone developmental trajectories for 2D:4D and height.
Subject(s)
Digit Ratios , Sex Characteristics , Pregnancy , Humans , Male , Child , Female , Adolescent , Siberia , Fingers/diagnostic imaging , Fingers/anatomy & histology , Gonadal Steroid HormonesABSTRACT
Background: Fragility fracture is associated with an increased risk of mortality, but mortality is not part of doctor-patient communication. Here, we introduce a new concept called 'Skeletal Age' as the age of an individual's skeleton resulting from a fragility fracture to convey the combined risk of fracture and fracture-associated mortality for an individual. Methods: We used the Danish National Hospital Discharge Register which includes the whole-country data of 1,667,339 adults in Denmark born on or before January 1, 1950, who were followed up to December 31, 2016 for incident low-trauma fracture and mortality. Skeletal age is defined as the sum of chronological age and the number of years of life lost (YLL) associated with a fracture. Cox's proportional hazards model was employed to determine the hazard of mortality associated with a specific fracture for a given risk profile, and the hazard was then transformed into YLL using the Gompertz law of mortality. Results: During the median follow-up period of 16 years, there had been 307,870 fractures and 122,744 post-fracture deaths. A fracture was associated with between 1 and 7 years of life lost, with the loss being greater in men than women. Hip fractures incurred the greatest loss of life years. For instance, a 60-year-old individual with a hip fracture is estimated to have a skeletal age of 66 for men and 65 for women. Skeletal Age was estimated for each age and fracture site stratified by gender. Conclusions: We propose 'Skeletal Age' as a new metric to assess the impact of a fragility fracture on an individual's life expectancy. This approach will enhance doctor-patient risk communication about the risks associated with osteoporosis. Funding: National Health and Medical Research Council in Australia and Amgen Competitive Grant Program 2019.
Osteoporosis is a 'silent disease' which often has no immediate symptoms but gradually weakens bones and makes them more likely to break. A bone fracture caused by osteoporosis in people over the age of 50 is linked to long-term health decline and in some cases, even early death. However, poor communication of the mortality risk to patients has led to a low uptake of treatment, resulting in a crisis of osteoporosis management. The impact of a fracture on life expectancy is typically conveyed to patients and the public in terms of probability (how likely something is to occur) or the relative risk of death compared to other groups. However, statements such as "Your risk of death over the next 10 years is 5% if you have suffered from a bone fracture" can be difficult to comprehend and can lead to patients underestimating the gravity of the risk. With the aim of devising a new way of conveying risks to patients, Tran et al. analyzed the relationship between fracture and lifespan in over 1.6 million individuals who were 50 years of age or older. The findings showed that one fracture was associated with losing up to 7 years of life, depending on gender, age and fracture site. Based on this finding, Tran et al. proposed the idea of 'skeletal age' as a new metric for quantifying the impact of a fracture on life expectancy. Skeletal age is the sum of the chronological age of a patient and the estimated number of years of life lost following a fracture. For example, a 60-year-old man with a hip fracture is predicted to lose an estimated 6 years of life, resulting in a skeletal age of around 66. Therefore, this individual has the same life expectancy as a 66-year-old person that has not experienced a fracture. Skeletal age can also be used to quantify the benefit of osteoporosis treatments. Some approved treatments substantially reduce the likelihood of post-fracture death and translating this into skeletal age could help communicate this to patients. For instance, telling patients that "This treatment will reduce your skeletal age by 2 years" is easier to understand than "This treatment will reduce your risk of death by 25%". Given the current crisis of osteoporosis management, adopting skeletal age as a new measure of how the skeleton declines after a fracture could enhance doctor-patient communication regarding treatment options and fracture risk assessment. Tran et al. are now developing an online tool called 'BONEcheck.org' to enable health care professionals and the public to calculate skeletal age. Future work should investigate the effectiveness of this new metric in conveying risk to patients, compared with current methods.
Subject(s)
Age Determination by Skeleton , Fractures, Bone , Life Expectancy , Adult , Female , Humans , Male , Middle Aged , Osteoporosis , Osteoporotic Fractures/complications , Osteoporotic Fractures/mortality , Proportional Hazards Models , Age Determination by Skeleton/methods , Fractures, Bone/complications , Fractures, Bone/epidemiology , Fractures, Bone/mortality , Denmark/epidemiology , AgedABSTRACT
This article is a retrospective analysis of postmortem computed tomography scans of ossification stages of the anterior and posterior intra-occipital sutures, the anterior arch of the atlas, and the neurocentral junction of the axis. We also analyzed the development of secondary ossification centers in the proximal humeral, femoral, and tibial epiphyses, and the distal femoral and tibial epiphyses. Additionally, the development of primary ossification centers in the wrist and metacarpals, and maxillary and mandibular deciduous tooth maturation. A total of 58 cadavers (35 males, 23 females), whose age ranged from 3rd month of pregnancy to 14 years, were analyzed. The results of this study show that analysis of synchondrosis closure, primary, and secondary ossification center development and deciduous tooth changes are a good tool for age estimation in subadults group (fetuses, newborns, infants, and children). The results of the study in a Polish population are consistent with those reported by other authors.
Subject(s)
Osteogenesis , Tomography, X-Ray Computed , Child , Infant , Male , Pregnancy , Female , Humans , Infant, Newborn , Retrospective Studies , Poland , FemurABSTRACT
OBJECTIVE: To determine the duration and age at the beginning of each stage corresponding to the circumpubertal period in the Middle Phalanx Maturation method (MPM) and to assess the differences between males and females. MATERIALS AND METHODS: Sets of X-rays of the middle phalanx of the third finger taken at 6-month intervals were analysed for 246 skeletal Class I subjects (102 females and 144 males) between 9 and 15 years of age. After staging, the duration of each stage was derived from chronological ages, and the difference between males and females for both duration and age at the beginning of each stage was investigated. RESULTS: The median duration for MPS2 and MPS3 was 1 year for both sexes, while MPS4 showed a median duration of 1 year in females and 9 months in males, with no significant differences between the sexes. Mean age at the beginning of MPS2 was 10y11m for females and 11y11m for males; for MPS3, it was 11y8m for females and 13y1m for males; for MPS4, it was 12y9m for females and 13y11m for males; for MPS5, it was 13y4m for females and 14y3m for males. The differences between the sexes were statistically significant for all the stages (P < .001). CONCLUSIONS: This study confirms, with relevant sample size, the median duration of 1 year for each MPM stage from MPS2 to MPS4. Despite the distinctive interindividual variability, the interquartile range is 6 months or less for all but one interval, confirming the soundness of the results.
Subject(s)
Age Determination by Skeleton , Bone Development , Male , Female , Humans , Age Determination by Skeleton/methods , RadiographyABSTRACT
PURPOSE: To assess conventional assumptions that underpin the percentage of mature height index as the simple ratio of screening height (numerator) divided by actual or predicted adult height (denominator). METHODS: We examined cross-sectional data from 99 academy youth soccer players (chronological age range, 11.5 to 17.7 y) skeletally immature at the screening time and with adult height measurements available at follow-up. RESULTS: The y-intercept value of -60 cm (95% confidence interval, -115 to -6 cm) from linear regression between screening height and adult height indicated the failure to meet the zero y-intercept assumption. The correlation coefficient between present height and adult height of .64 (95% confidence interval, .50 to .74) was not equal to the ratio of coefficient of variations between these variables (CVx/CVy = 0.46) suggesting Tanner's special circumstance was violated. The non-zero correlation between the ratio and the denominator of .21 (95% confidence interval, .01 to .39) indicated that the percentage of mature height was biased low for players with generally shorter adult height, and vice versa. CONCLUSION: For the first time, we have demonstrated that the percentage of mature height is an inconsistent statistic for determining the extent of completed growth, leading to potentially biased inferences for research and applied purposes.