Prediction of total corneal power in keratoconus using anterior surface data.

CLINICAL RELEVANCE: Keratoconus results in an increase in anterior and posterior curvatures and a reduction in corneal thickness. Anterior corneal ectasia is partially compensated by remodelling the corneal epithelium. Therefore, there is an alteration in the relationship between corneal surfaces and variation in corneal power. The variation in corneal power is one of the sources that induces errors in IOL power calculation. BACKGROUND: This study aimed to assess a method for predicting total corneal power in keratoconus using several anterior surface parameters at 3 mm and 4 mm. METHODS: Tomographic data obtained using Pentacam (Oculus, Germany) were analysed from 280 eyes of 140 patients with keratoconus using anterior and posterior keratometry, anterior Q-value at 8 mm, central corneal thickness, Kmax location and value, and true net power at 4 mm (TNP). Calculated total corneal power (TCPc) at 3 mm was obtained using the Gauss formula. Predicted total corneal power at 3 mm (TCPp3) and 4 mm (TCPp4) was obtained from univariate (TCPp3u and TCPp4u) and multivariate linear regression formulae (TCPp3m and TCPp4m). SimK, anterior Q-value, vertical location, and Kmax value were used in the multivariate formulae. Mean absolute error (MAE) and median absolute error (MedAE) were also calculated. Absolute frequencies within dioptric ranges of all formulas divided for keratoconus grading were evaluated. RESULTS: TCPc and TNP exhibited a good correlation (R2 = 0.58, p < 0.05) with a higher dispersion above 50 D of corneal power. Highly significant correlations were observed between TCPp3u and TCPc (R2 = 0.978, p < 0.05) and TCPp3m and TCPc (R2 = 0.989, p < 0.05). Lower but significant correlations were observed between TCPp4u and TNP (R2 = 0.692, p < 0.05) and between TCPp4m and TNP (R2 = 0.887, p < 0.05). The best results for TCP prediction at 3 and 4 mm were obtained with TCPp3m and TCPp4m as follows: MAE of TCPp3m was 0.24 ± 0.20 (SD) D with MedAE of 0.20 D, while MAE of TCPp4m was 0.96 ± 0.77 D with MedAE of 0.80 D. The 3 mm multivariate regression formula results in higher absolute frequencies of prediction errors in the total eyes within 0.5 D (93%) than the univariate formula (81%). At 4mm, the multivariate regression formula has a lower percentage within 0.5 D (32%) than the univariate formula (41%), but the percentage of the multivariate formula is higher within 1 D (63%) than the univariate formula (56%). CONCLUSION: All formulas show a decrease in accuracy with increasing grades of keratoconus. Multivariate linear regression formulae using only anterior surface data can predict TCP with good approximation in eyes with keratoconus in cases where posterior surface parameters are unavailable. The vertical location of Kmax and the anterior asphericity could play a relevant role in the prediction of total corneal power in keratoconus.

Development and validation of a risk prediction model for lost to follow-up among adults on active antiretroviral therapy in Ethiopia: a retrospective follow-up study.

BACKGROUND: Over 420,000 people have initiated life-saving antiretroviral therapy (ART) in Ethiopia; however, lost-to-follow-up (LTFU) rates continues to be high. A clinical decision tool is needed to identify patients at higher risk for LTFU to provide individualized risk prediction to intervention. Therefore, this study aimed to develop and validate a statistical risk prediction tool that predicts the probability of LTFU among adult clients on ART. METHODS: A retrospective follow-up study was conducted among 432 clients on ART in Gondar Town, northwest, Ethiopia. Prognostic determinates included in the analysis were determined by multivariable logistic regression. The area under the receiver operating characteristic (AUROC) and calibration plot were used to assess the model discriminative ability and predictive accuracy, respectively. Individual risk prediction for LTFU was determined using both regression formula and score chart rule. Youden index value was used to determine the cut-point for risk classification. The clinical utility of the model was evaluated using decision curve analysis (DCA). RESULTS: The incidence of LTFU was 11.19 (95% CI 8.95-13.99) per 100-persons years of observation. Potential prognostic determinants for LTFU were rural residence, not using prophylaxis (either cotrimoxazole or Isoniazid or both), patient on appointment spacing model (ASM), poor drug adherence level, normal Body mass index (BMI), and high viral load (viral copies > 1000 copies/ml). The AUROC was 85.9% (95% CI 82.0-89.6) for the prediction model and the risk score was 81.0% (95% CI 76.7-85.3) which was a good discrimination probability. The maximum sensitivity and specificity of the probability of LTFU using the prediction model were 72.07% and 83.49%, respectively. The calibration plot of the model was good (p-value = 0.350). The DCA indicated that the model provides a higher net benefit following patients based on the risk prediction tool. CONCLUSION: The incidence of LTFU among clients on ART in Gondar town was high (> 3%). The risk prediction model presents an accurate and easily applicable prognostic prediction tool for clients on ART. A prospective follow-up study and external validation of the model is warranted before using the model.

Measurement of corneal thickness using Pentacam HR versus Nidek CEM-530 specular microscopy.

OBJECTIVE: To compare corneal thickness (CT) measurements using the CEM-530 (Nidal, Gamagori, Japan) and Pentacam HR (Oculus, Wetzlar, Germany). METHODS: The CT of 209 healthy subjects (209 right eyes) aged 24 to 89 years (71.35 ± 10.72 years) was measured at the corneal apex (CA), pupil center (PC), and thinnest point (TP) with the Pentacam HR and at the corneal center with the CEM-530 in random order at the same time of day. RESULTS: A good correlation but statistically significant difference was found between the CEM-530 and Pentacam HR measurements at the CA (6.10 ± 8.12 µm, R2 = 0.8947), PC (7.46 ± 8.57 µm, R2 = 0.8826), and TP (12.44 ± 10.04 µm, R2 = 0.8392). Comparison of the two devices produced the following regression formulas: y = 0.8859x + 57.644 for the CA, y = 0.8852x +56.657 for the PC, and y = 0.8557x + 68.148 for the TP, where x is the CT obtained with the CEM-530 and y is that obtained with the Pentacam HR. CONCLUSIONS: These findings indicate that the CEM-530 produces a thicker corneal measurement than the Pentacam HR. The herein-proposed correcting factors are needed to reliably compare these devices.

Comparison of Errors of 35 Weight Estimation Formulae in a Standard Collective.

Issue: The estimation of foetal weight is an integral part of prenatal care and obstetric routine. In spite of its known susceptibility to errors in cases of underweight or overweight babies, important obstetric decisions depend on it. In the present contribution we have examined the accuracy and error distribution of 35 weight estimation formulae within the normal weight range of 2500-4000 g. The aim of the study was to identify the weight estimation formulae with the best possible correspondence to the requirements of clinical routine. Materials and Methods: 35 clinically established weight estimation formulae were analysed in 3416 foetuses with weights between 2500 and 4000 g. For this we determined and compared the mean percentage error (MPE), the mean absolute percentage error (MAPE), and the proportions of estimates within the error ranges of 5, 10, 20 and 30 %. In addition, separate regression lines were calculated for the relationship between estimated and actual birth weights for the weight range 2500-4000 g. The formulae were thus examined for possible inhomogeneities. Results: The lowest MPE were achieved with the Hadlock III and V formulae (0.8 %, STW 9.2 % or, respectively, -0.8 %, STW 10.0 %). The lowest absolute error (6.6 %) as well as the most favourable frequency distribution in cases below 5 % and 10 % error (43.9 and 77.5) were seen for the Halaska formula. In graphic representations of the regression lines, 16 formulae revealed a weight overestimation in the lower weight range and an underestimation in the upper range. 14 formulae gave underestimations and merely 5 gave overestimations over the entire tested weight range. Conclusion: The majority of the tested formulae gave underestimations of the actual birth weight over the entire weight range or at least in the upper weight range. This result supports the current strategy of a two-stage weight estimation in which a formula is first chosen after a pre-estimation of the weight range.

A New Sonographic Weight Estimation Formula for Small-for-Gestational-Age Fetuses.

OBJECTIVES: The purpose of this study was to develop a new specific weight estimation formula for small-for-gestational-age (SGA) fetuses that differentiated between symmetric and asymmetric growth patterns. METHODS: A statistical estimation technique known as component-wise gradient boosting was applied to a group of 898 SGA fetuses (symmetric, n = 750; asymmetric, n = 148). A new formula was derived from the data obtained and was then compared to other commonly used equations. RESULTS: The new formula derived is as follows: estimated fetal weight = e^[1.3734627 + 0.0057133 × biparietal diameter + 0.0011282 × head circumference + 0.0201147 × abdominal circumference + 0.0183081 × femur length - 0.0000177 × biparietal diameter(2) - 0.0000018 × head circumference(2) - 0.0000297 × abdominal circumference(2) -0.0001007 × femur length(2) + 0.0397563 × I(sex = male) + 0.0064505 × gestational age (days) + 0.0096528 × I(SGA = asymmetric)], where the function I denotes an indicator function, which is 1 if the expression is fulfilled (sex = male; SGA type = asymmetric) and otherwise 0. In the whole study group and the 2 subgroups, the new formula showed the lowest median absolute percentage error, mean percentage error, and random error and the best distribution of absolute percentage errors within prespecified error bounds. CONCLUSIONS: The new formula substantially improves weight estimation in SGA fetuses.

Age Assessment in Children: A Novel Cameriere's Stratagem.

AIM: Age is one of the essential factors in establishing the identity of a person, especially in children. Age estimation plays an important part in treatment planning, forensic dentistry, legal issues, and paleodemographic research. The present study was an attempt to estimate the chronological age in children of Davangere population by using Cameriere's India specific formula. MATERIALS AND METHODS: This was a retrospective observational study to estimate the chronological age in children of Davangere population. A total of 150 panoramic radiographs of patients aged between 6 and 15 years, including both sexes, were selected. Age was calculated by measuring open apices of seven right or left mandibular teeth using Adobe Photoshop software. RESULTS: Statistical analysis was performed to derive a regression equation for estimation of age, which showed that, of the variables X1, X2, X3, X4, X5, X6, X7, s, N0, the variables N0 and X4 were statistically noteworthy. Hence, these two variables were used to derive the linear regression formula: Age = 10.522 + 0.712(N0) - 5.040(X4). The model was found to be statistically significant, F(2, 147) = 207.96, p < 0.001, and accounted for approximately 74% of the variance of age (R2 = 0.739, adjusted R2 = 0.735). CONCLUSION: Cameriere's method can be used for age assessment in children for forensic as well as legal contexts and based on these variables a reliable age estimation equation could be proposed specifically for Davangere population. HOW TO CITE THIS ARTICLE: Attiguppe PR, Yavagal C, Maganti R, Mythri P. Age Assessment in Children: A Novel Cameriere's Stratagem. Int J Clin Pediatr Dent 2016;9(4):330-334.

A method for estimating age of medieval sub-adults from infancy to adulthood based on long bone length.

OBJECTIVES: To develop a series of regression equations for estimating age from length of long bones for archaeological sub-adults when aging from dental development cannot be performed. Further, to compare derived ages when using these regression equations, and two other methods. MATERIAL AND METHODS: A total of 183 skeletal sub-adults from the Danish medieval period, were aged from radiographic images. Linear regression formulae were then produced for individual bones. Age was then estimated from the femur length using three different methods: equations developed in this study, data based on a modern population (Maresh: Human growth and development (1970) pp 155-200), and, lastly, based on archeological data with known ages (Rissech et al.: Forensic Sci Int 180 (2008) 1-9). As growth of long bones is known to be non-linear it was tested if the regression model could be improved by applying a quadratic model. RESULTS: Comparison between estimated ages revealed that the modern data result in lower estimated ages when compared to the Danish regression equations. The estimated ages using the Danish regression equations and the regression equations developed by Rissech et al. (Forensic Sci Int 180 (2007) 1-9) were very similar, if not identical. This indicates that the growth between the two archaeological populations is not that dissimilar. DISCUSSION: This would suggest that the regression equations developed in this study may potentially be applied to archaeological material outside Denmark as well as later than the medieval period, although this would require further testing. The quadratic equations are suggested to yield more accurate ages then using simply linear regression equations.

Differences in Prediction Formulas for the MVV According to the Status of Ventilatory Function / 대한내과학회지

OBJECTIVES: The MVV reflects subjective dyspnea, exercise capacity, postoperative complication. But, the MVV embodies certain disadvantages and is dependent on coordination, endurance and motivation. A timed vital capacity for calculation of an indirect maximal voluntary ventilation is used. We evaluated differences in prediction formulas for the MUV according to the status of ventilatory function. METHODS: Forty-seven normal subjects, 68 patients with obstructive ventilatory impairment, and 23 patients with restrictive ventilatory impairment were studied. The relationships between the MVV and Flow or time parameters in forced expiratory volume and flow volume curves were compared among normal subjects and patients with obstructive or restrictive ventilatory impairment. RESULTS: 1) High correlation coefficients(R>or=0.87) were found between the FEV0.5, 0.75, 1 and the MVV in 47 normal subjects and 91 patients with ventilatory impairment. 2) The MVV can be conveniently estimated from the FEV1 values. The following regression formulas for the prediction of the MVV were obtained. Normal: MVV=44.01 X FEV1-21.09(r(2)=0.771, SEE=11.085) Obstructive ventilatory impairment: MVV=38.34 X FEV1-4.58(r(2)0.812, SEE=4.816) Restrictive ventilatory impairment: MVV=45.20 X FEV1-3.80(r(2)=0.899, SEE=6.929). 3) There were significant differences in prediction formulas for the MVV obtained by FEV1 between each group (P<0.05). CONCLUSION: These results suggest that different prediction formulas for the MVV, by multiplying the FEV1 by a constant, are respectively required in normal subjects and patients with obstructive or restrictive ventilatory impairment.

The Comparison of Aphakic Refraction Before and After Cataract Surgery

We reviewed the records of 101 eyes who underwent extracapsular cataract extraction without intraocular lens implantation at Kosin Medical Center from Feb. 1987 to Mar. 1990. Of these, 47 eyes that showed postoperative corrected visual acuity of 0.5 more and more than 2 months' follow-up periods, were recruited for this study. To detect the changes of preoperative predicted aphakic refractions and postoperative observed aphakic refractions. we studied the changes of pre- and postoperative axial lengths, keratometric measurements, and observed aphakic refractions at postoperative 2 months were compared with predicted aphakic refractions, using linear regression formula. The results were as follows: 1. Distribution of age were in the range of 24 to 79 years(mean, 59.4 years), and seventh decade(31.8%) was most common. 2. Postoperative keratometric measurements was decreased in power of mean +/- SD; 0.04 +/- 0.14 diopters(p>0.05). 3. Postoperative axial length was increased by 0.20 +/- 0.09mm(p<0.05). 4. The difference between pre- and postoperative refractive power was mean +/- SD; 0.58 +/- 0.16 diopters(p<0.05).

Evaluation for the Accuracy of the SRK/T Formula in PCL Implanted Patients(I)

The 1224 cataractous patients who had extracapsular cataract extraction and posterior chamber lens implantations were evaluated retrospectively irrespective of style, postoperative position of intraocular lens and surgeon. The 100 cataractous patients who had extracapsular cataract extraction and posterior chamber lens implantations in the bag accurately using single lens style by one surgeon(E.H.L) were evaluated prospectively. And then the predictive accuracy of the SRK/T intraocular lens power calculation formula was compared with other formulas (SRK, SRKII and Holladay) without consideration of individual A constant. The SRK/T formula was more accurate than other 3 formulas in all axial length, but there were no significant differences statistically. Especially for short and long eyes, SRK/T formula was more accurate than other 3 formulas.

A CORRELATIVE STUDY ON THE DIAMETER AND AREA OF CERVICAL SPINAL CANAL AND THE CORRESPONDING SPINAL CORD / 解剖学报

The cervical spinal canal at C_3-C_7 (200 in total) of 40 adult cervical spinal columns were measured on the axis radiograph. The diameter and area of spinal canal and corresponding spinal cord were investigated with vernier calipers and planimeter.The average values of the measurements are reported as follows:1. The sagittal and transverse diameter of the cervical spinal canal at C_3-C_7 are 13.71?1.31mm and 24.15?1.91mm, while those of the corresponding segment of spinal cord are 7.99?1.01mm and 13.35?1.64mm, respectively.2. The total area of the spinal canal and spinal cord at C_3-C_7 are 239.35?41.78 mm~1 and 106.6?9.9 mm~2, respectively. These data were studied with computer using multiple linear regression analysis program and a calculating formula of cervical spinal canal and the corresponding segment of spinal cord were inferred.Since sagittal and transverse diameters of vertebral canal and cervical spinal cord are measured, we may calculate the both area by using above mentioned formula. This will offer a new method for diagnosis of spinal canal stenosis and spondylosis.