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PubMed1999

Alcohol and visually guided saccades: gap effect and predictability of target location.

RATIONALE: Alcohol is known to affect most parameters of visually guided saccades, but it is unclear whether intoxicated subjects are able to utilize temporal or spatial pre-cues to compensate for their alcohol-related slowing of saccades. OBJECTIVES: We examined the effects of both temporal and spatial predictability on gain, latency, and peak velocity in sober and intoxicated subjects, e.g. by employing a temporal gap condition. METHODS: Saccades were recorded with subjects once sober and once intoxicated (0.8 g ethanol per kg body weight). Unpredictable and predictable target locations alternated in both the classical (no gap) and temporal gap condition (extinction of fixation point 200 ms before target onset). RESULTS: The gain was only slightly affected by alcohol, but increased for predictable target locations. After alcohol consumption, latencies increased, even in the gap condition and for predictable targets. However, intoxicated subjects took relatively more benefit from the gap than sober subjects did. In addition, they showed a "pretrial effect", i.e. their latencies depended on the condition for the previous saccade. For predictable target locations, latencies decreased and peak velocities increased both in sober and intoxicated subjects. Thus, intoxicated subjects were able to utilize both the spatial predictability and the temporal gap to speed up their saccades. CONCLUSIONS: These results lead to suggest that as far as the saccadic system is concerned alcohol predominantly affects the function of the superior colliculus (SC) and/or the oculomotor regions in the brain stem, either directly or indirectly. On the other hand, cortical areas assumed to mediate prediction and the gap effect seem to be less affected by alcohol intoxication.

Adult↗
PubMed2001

Predicting sensory events. The role of the cerebellum in motor learning.

There is growing evidence that the cerebellum is involved in the implicit learning of movement sequences. On the serial reaction time (RT) task patients with cerebellar lesions fail to demonstrate normal decreases in RT and we have shown a similar effect in monkeys with bilateral cerebellar lesions. However, it is not clear if this impairment is unique to sequence learning or whether the cerebellum is also involved in the learning of discrete responses to predictable visual targets. We investigated this possibility in another group of monkeys with bilateral lesions of the cerebellum centred on the lateral nuclei. Three animals were pre-operatively trained to make rapid manual responses to a single target appearing on a touch-sensitive VDU screen. In one condition, a target could appear at any of three possible locations (spatially unpredictable). In a second condition the target always appeared in the same place (spatially predictable). A third condition was similar to the second except that the onset of the target was temporally predictable whereas in the previous conditions this parameter was randomized. Following the lesions, the RT savings earned on the conditions in which the cues were predictable were abolished. This was despite a lack of significant increase in movement times. The results imply that the animals were either failing to predict the spatial location or time of presentation of the target, or that they were unable to use their prediction to improve their reaction times. The function of the cerebellum in motor sequence learning may therefore be part of a more general operation in learning to prepare responses to predictable sensory events.

Animals↗
PubMed2007

Predicting the biodistribution of radiolabeled cMORF effector in MORF-pretargeted mice.

PURPOSE: Pretargeting with phosphorodiamidate morpholino oligomers (MORFs) involves administration of a MORF-conjugated anti-tumor antibody such as MN14 as a pretargeting agent before that of the radiolabeled complementary MORF (cMORF) as the effector. The dosages of the pretargeting agent and effector, the pretargeting interval, and the detection time are the four pretargeting variables. The goal of this study was to develop a semiempirical description capable of predicting the biodistribution of the radiolabeled effector in pretargeted mice and then to compare predictions with experimental results from pretargeting studies in tumored animals in which the pretargeting interval and the detection time were both fixed but the dosages of both the effector and the pretargeting agent were separately varied. METHODS: Pretargeting studies in LS174T tumored mice were performed using the anti-CEA antibody MN14 conjugated with MORF and the cMORF radiolabeled with (99m)Tc. A description was developed based on our previous observations in the same mouse model of the blood and tumor levels of MORF-MN14, accessibility of MORF-MN14 to labeled cMORF, the tumor accumulation of labeled cMORF relative to MORF-MN14 levels therein, and the kidney accumulation of labeled cMORF. The predicted values were then compared with the experimental values. RESULTS: The predicted biodistribution of the radiolabeled effector and the experimental data were in gratifying agreement in normal organs, suggesting that the description of the pretargeting process was reliable. The tumor accumulations occasionally fell outside two standard deviations of that predicted, but after tumor size correction, good agreement between predicted and experimental values was observed here as well. CONCLUSION: A semiempirical description of the biodistribution of labeled cMORF was capable of predicting the biodistribution of the radiolabeled effector in the pretargeted tumored mouse model, demonstrating that the underlying pretargeting concepts are correct. We believe that the approach described herein may be applied to any of the alternative pretargeting approaches and animal tumor models currently under investigation. Furthermore, appreciation of the concepts may provide a rationale for selecting dosages and timings in human pretargeting studies as an alternative to pure empirical means.

Algorithms↗
PubMed2005

Prediction and validation of total and regional skeletal muscle mass by ultrasound in Japanese adults.

The present study was performed to develop regression-based prediction equations for skeletal muscle (SM) mass by ultrasound and to investigate the validity of these equations in Japanese adults. Seventy-two Japanese men (n=38) and women (n=34) aged 18-61 years participated in this study and were randomly separated into two groups: the model development group (n=48) and the validation group (n=24). The total and regional SM mass were measured using magnetic resonance imaging (MRI) 1.5 T-scanners with spin-echo sequence. Contiguous transverse images (about 150 slices) with a slice thickness of 1 cm were obtained from the first cervical vertebra to the ankle joints. The volume of SM was calculated from the summation of digitized cross-sectional area. The SM volume was converted into mass units (kg) by an assumed SM density of 1.04 kg l(-1). The muscle thickness (MTH) was measured by B-mode ultrasound (5 MHz scanning head) at nine sites on the anatomical SM belly. Strong correlations were observed between the site-matched SM mass (total, arm, trunk body, thigh, and lower leg) by MRI measurement and the MTH x height (in m) in the model development group (r=0.83-0.96 in men, r=0.53-0.91 in women, P<0.05). When the SM mass prediction equations were applied to the validation group, significant correlations were also observed between the MRI-measured and predicted SM mass (P<0.05). The predicted total SM mass for the validation group was 19.6 (6.5) kg and was not significantly different from the MRI-measured SM mass of 20.2 (6.5) kg. Bland-Altman analysis did not indicate a bias in prediction of the total SM mass for the validation group (r=0.00, NS). These results suggested that ultrasound-derived prediction equations are a valid method to predict SM mass and an alternative to MRI measurement in healthy Japanese adults.

Adolescent↗
PubMed2006

Symbols as self-emergent entities in an optimization process of feature extraction and predictions.

In the mammalian cortex the early sensory processing can be characterized as feature extraction resulting in local and analogue low-level representations. As a direct consequence, these map directly to the environment, but interpretation under natural conditions is ambiguous. In contrast, high-level representations for cognitive processing, e.g. language, require symbolic representations characterized by expression and syntax. The representations are binary, structured and disambiguated. However, do these fundamental functional distinctions translate into a fundamental distinction of the respective brain areas and their anatomical and physiological properties? Here we argue that the distinction between early sensory processing and higher cognitive functions may not be based on structural differences of cortical areas; instead similar learning principles acting on input signals with different statistics give rise to the observed variations of function. Firstly, we give an account of present research describing neuronal properties at early stages of sensory systems as a consequence of an optimization process over the set of natural stimuli. Secondly, addressing a stage following early visual processing we suggest to extend the unsupervised learning scheme by including predictive processes. These contain the widely used objective of temporal coherence as a special case and are a powerful approach to resolve ambiguities. Furthermore, in combination with a prior on the bandwidth of information exchange between units it leads to a condensation of information. Thirdly, as a crucial step, not only are predictive units optimized, but the selectivity of the feature extractors are adapted to allow optimal predictability. Thus, over and beyond making useful predictions, we propose that the predictability of a stimulus be in itself a selection criterion for further processing. In a hierarchical system the combined optimization process leads to entities that represent condensed pieces of knowledge and that are not analogue anymore. Instead, these entities work as arguments in a framework of transformations that realize predictions. Thus, the criteria of predictability and condensation in an optimization of sensory representations relate directly to the two defining properties of symbols of expression and syntax. In this paper, we sketch an unsupervised learning process that gradually transforms analogue local representations into discrete binary representations by means of four hypotheses. We propose that in this optimization process acting in a hierarchical system, entities emerge at, higher levels that fulfil the criteria defining symbols, instantiating qualitatively different representations at similarly structured low and high levels.

Animals↗
PubMed2000

The prediction of EEG signals using a feedback-structured adaptive rational function filter.

In this article, we present a feedback-structured adaptive rational function filter based on a recursive modified Gram-Schmidt algorithm and apply it to the prediction of an EEG signal that has nonlinear and nonstationary characteristics. For the evaluation of the prediction performance, the proposed filter is compared with other methods, where a single-step prediction and a multi-step prediction are considered for a short-term prediction, and the prediction performance is assessed in normalized mean square error. The experimental results show that the proposed filter shows better performance than other methods considered for the short-term prediction of EEG signals.

Algorithms↗
PubMed2003

Unique transitions between stimuli and responses in SRT tasks: evidence for the primacy of response predictions.

The present experiments aimed at separating the impact stimulus and response predictions have on serial learning and performance in SRT tasks. In Experiment 1, a unique transition between two of four responses in an otherwise random response sequence was triggered by ambiguous stimulus transitions, allowing local response predictions but no stimulus predictions. The data indicated explicit transition knowledge and strong performance benefits. In Experiments 2 and 3, unique transitions between two of four stimuli in otherwise random stimulus sequences allowed local stimulus predictions under conditions of ambiguous response transitions. The data indicated fragmentary explicit transition knowledge but no performance effects. Experiments 4a and 4b reveal that the inefficacy of the unique stimulus transitions in Experiments 2 and 3 was presumably due to the fact that the stimuli differed with respect to conjunctions of response relevant and response irrelevant features which participants did not have to attend. However, although in Experiments 4a and 4b unique transitions between response relevant stimuli were applied, substantial explicit transition knowledge but only marginal performance effects resulted. It is argued i) that in SRT tasks learning mechanisms are addressed that primarily strive for reliable predictions of forthcoming responses and ii) that for these mechanisms to work the predictors have to be attended. Response transitions are easily learned and used because both criteria are fulfilled. In contrast, pure stimulus transitions are learned only if the predictive stimuli are attended, and learned stimulus transitions become effective only to the extent that the predicted stimuli specify the required responses.

Adult↗
PubMed2002

Cholangitis score: a scoring system to predict severe cholangitis in gallstone pancreatitis.

BACKGROUND/PURPOSES: Emergency biliary decompression and stone extraction are mandatory for patients with gallstone pancreatitis who have ampullary stone impaction or persistent stones and pus in the bile duct (severe cholangitis). The aim of this study was to devise a simple scoring system for the prediction of complicating severe cholangitis in gallstone pancreatitis. METHODS: Clinical signs, laboratory data, and ultrasonography (US) findings at the time of admission, and the bile duct pathology at the time of bile duct exploration, were reviewed in 66 patients with gallstone pancreatitis. Variables which discriminated 26 patients with bile duct stones from 40 without were defined as predictive factors of bile duct stones. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff values of numerical variables. One point was allocated to each predictive factor, and the total score was defined as the cholangitis score (CS). Bile duct pathology identified at the time of bile duct exploration was graded into three categories: mild, moderate, and severe cholangitis. A threshold value of the CS, claimed to be predictive of severe cholangitis, was determined by using the ROC curve. RESULTS: The scoring system consisted of four predictive factors: (1) pyrexia (temperature > or =38 degrees C), (2) elevated serum bilirubin (> or =2.2 mg/dl), (3) dilated bile duct (> or =11 mm maximum diameter on US), and (4) bile duct stones detected on US. The scoring system predicted severe cholangitis with 92% sensitivity and 98% specificity in patients with scores of three or four points. CONCLUSIONS: Patients with gallstone pancreatitis who meet three or four of the above predictive factors at the time of admission are likely to have severe cholangitis, and should be rapidly treated by biliary decompression and stone extraction.

Acute Disease↗
PubMed1999

Comparison between measured and predicted resting metabolic rate in moderately active adolescents.

The aim of this study was to check the validity of predictive equations for the calculation of resting metabolic rate (RMR) in moderately active adolescents. The RMR was measured in a sample of 25 healthy 15.5-18.2-year-old boys practicing soccer. The RMR was assessed by indirect calorimetry for 30 min following an overnight fast. Body composition was estimated from skinfold thickness measurements. Among the available equations to predict RMR, we decided to use those a of Molnar et al., Harris-Benedict, Schofield, and Cunningham. Measured and predicted values were compared by means of a one-way ANOVA. Also the Bland-Altman test was performed in order to evaluate the accuracy of the prediction equations compared to the measured value. The measured RMR was found to be 1834 +/- 160 kcal/day (mean +/- SD), while the Molnar et al., Schofield, Harris-Benedict, and Cunningham predicted values were 1707 +/- 78, 1866 +/- 89, 1779 +/- 84 and 1830 +/- 87 kcal/day, respectively. On average, compared to the measured values only the Molnar et al. equation differed significantly. On an individual basis, all the equations demonstrated considerable variability between measured and predicted RMRs. The predicted values also differed significantly. As regards the moderately active subjects (16-18 years old), we recommend the use of the Schofield equation, based on simple anthropometric parameters and also that of Cunningham, even if the estimation or measurement of fat-free mass may be cumbersome for everyday pediatric use.

Adolescent↗
PubMed2006

Fast prediction of protein domain boundaries using conserved local patterns.

We have found certain conserved motifs and secondary structural patterns present in the vicinity of interior domain boundary points (dbps) by a data-driven approach without any a priori constraint on the type and number of such features, and without any requirement of sequence homology. We have used these motifs and patterns to rerank the solutions obtained by the well-known domain guess by size (DGS) algorithm. We predict, overall, five solutions. The average accuracy of overall (i.e., top five) predictions by our method [domain boundary prediction using conserved patterns (DPCP)] has improved the average accuracy of the top five solutions of DGS from 71.74 to 82.88 %, in the case of two-continuous-domain proteins, and from 21.38 to 80.56 %, for two-discontinuous-domain proteins. Considering only the top solution, the gains in accuracy are from 0 to 72.74 % for two-continuous-domain proteins with chain lengths up to 300 residues, and from 0 to 62.85 % for those with up to 400 residues. In the case of discontinuous domains, top_min solutions (the minimum number of solutions required for predicting all dbps of a protein) of DPCP improve the average accuracy of DGS prediction from 12.5 to 76.3 % in proteins with chain lengths up to 300 residues, and from 13.33 to 70.84 % for proteins with up to 400 residues. In our validation experiments, the performance of DPCP was also found to be superior to that of domain identification from secondary structure element alignment (DomSSEA), the best method reported so far for efficient prediction of domain boundaries using predicted secondary structure. The average accuracies of the topmost solution of DomSSEA are 61 and 52 % for proteins with up to 300 residues and 400, respectively, in the case of continuous domains; the corresponding accuracies for the discontinuous case are 28 and 21 %.

Amino Acid Motifs↗
PubMed2006

Comparison of self-report and clinician-rated measures of psychiatric symptoms and functioning in predicting 1-year hospital readmission.

This study compared the self-report Behavior and Symptom Identification Scale (BASIS-32) and clinician-rated Global Assessment of Functioning (GAF) in their ability to predict a measure of psychiatric outcome, 1-year psychiatric hospital readmission. BASIS-32 and GAF were completed at admission for 1034 patients in an inpatient psychiatric facility. Multiple informants analysis was used to determine the difference between the two in predicting readmission within 1 year. We also examined sensitivity, specificity, and predictive value positive of the two measures, and whether self-report added information above clinician rating in predicting outcome. While the odds of 1-year readmission decreased with increasing BASIS-32 score, there was no association between change in GAF score and 1-year readmission. Although neither measure used alone demonstrated high predictive value, using both scores improved predictive ability over using clinician rating alone. In this setting, self-report was better than clinician rating in predicting psychiatric outcome. Differences between the two in relation to other outcomes need to be examined.

Adolescent↗
PubMed2005

Prediction of behavioral problems in Chilean schoolchildren.

Five hundred and thirty five Chilean schoolchildren were evaluated with a test-retest procedure using teacher and parent questionnaires in first and sixth grade, respectively, and a measure of self-esteem in sixth grade. According to teachers' ratings, disobedience/aggression, shyness and hyperactivity persisted. Cross-predictions were found: disobedience/aggression increased the risk of cognitive/concentration problems, which predicted emotional immaturity, while hyperactivity predicted disobedience/aggression. Teacher's global opinion of poor achievement predicted cognitive/concentration problems, and poor conduct predicted hyperactivity. Behavioral problems rated by parents in first grade predicted their persistence. Detection of problems in first grade predicts sixth grade outcomes, providing information for implementing preventive interventions.

Analysis of Variance↗
PubMed2006

Predicting water quality impaired stream segments using landscape-scale data and a regional geostatistical model: a case study in Maryland.

In the United States, probability-based water quality surveys are typically used to meet the requirements of Section 305(b) of the Clean Water Act. The survey design allows an inference to be generated concerning regional stream condition, but it cannot be used to identify water quality impaired stream segments. Therefore, a rapid and cost-efficient method is needed to locate potentially impaired stream segments throughout large areas. We fit a set of geostatistical models to 312 samples of dissolved organic carbon (DOC) collected in 1996 for the Maryland Biological Stream Survey using coarse-scale watershed characteristics. The models were developed using two distance measures, straight-line distance (SLD) and weighted asymmetric hydrologic distance (WAHD). We used the Corrected Spatial Akaike Information Criterion and the mean square prediction error to compare models. The SLD models predicted more variability in DOC than models based on WAHD for every autocovariance model except the spherical model. The SLD model based on the Mariah autocovariance model showed the best fit (r(2) = 0.72). DOC demonstrated a positive relationship with the watershed attributes percent water, percent wetlands, and mean minimum temperature, but was negatively correlated to percent felsic rock type. We used universal kriging to generate predictions and prediction variances for 3083 stream segments throughout Maryland. The model predicted that 90.2% of stream kilometers had DOC values less than 5 mg/l, 6.7% were between 5 and 8 mg/l, and 3.1% of streams produced values greater than 8 mg/l. The geostatistical model generated more accurate DOC predictions than previous models, but did not fit the data equally well throughout the state. Consequently, it may be necessary to develop more than one geostatistical model to predict stream DOC throughout Maryland. Our methodology is an improvement over previous methods because additional field sampling is not necessary, inferences about regional stream condition can be made, and it can be used to locate potentially impaired stream segments. Further, the model results can be displayed visually, which allows results to be presented to a wide variety of audiences easily.

Carbon↗
PubMed2005

Prediction of pK(a) for neutral and basic drugs based on radial basis function Neural networks and the heuristic method.

PURPOSES: Quantitative structure-property relationships (QSPR) were developed to predict the pK(a) values of a set of neutral and basic drugs via linear and nonlinear methods. The ability of the models to predict pK(a) was assessed and compared. METHODS: The descriptors of 74 neutral and basic drugs in this study were calculated by the software CODESSA, which can calculate constitutional, topological, geometrical, electrostatic, and quantum chemical descriptors. Linear and nonlinear QSPR models were developed based on the heuristic method (HM) and radial basis function neural networks (RBFNN), respectively. The heuristic method was also used for the preselection of appropriate molecular descriptors. RESULTS: The obtained linear model had a correlation coefficient of r=0.884, F=37.72 with a root-mean-squared (RMS) error of 0.482 for the training set, and r=0.693, F=11.99, nd RMS=0.987 for the test set. The RMS in predicting the overall data set is 0.619. The nonlinear model gave better results; for the training set, r=0.886, F=202.314, and RMS=0.458, and for the test set r=0.737, F=15.41, and RMS=0.613. The RMS error in prediction for overall data set is 0.493. Prediction results from nonlinear model are in good agreement with experimental values. CONCLUSIONS: In present study, we developed a QSPR model to predict the important parameter (pK(a)) of neutral and basic drugs. The model is useful in predicting pK(a) during the discovery of new drugs when experimental data are unknown.

Neural Networks, Computer↗
PubMed1994

Prediction of stature from knee height for black and white adults and children with application to mobility-impaired or handicapped persons.

OBJECTIVE: No adequate methods exist for predicting stature to help assess the growth of handicapped (including mobility-impaired) children or to help in developing indexes of obesity or equations for estimating basal energy expenditure for adults. In this project, equations were developed to predict stature in white and black adults and children from nationally representative samples for application to mobility-impaired and handicapped persons. SAMPLES: Samples of healthy adults (n = 5,415) and children (n = 13,821) were selected from cycles I, II, and III of the National Health Examination Survey (NHES) conducted by the National Center for Health Statistics from 1960 to 1970. Balanced validation and cross-validation groups were created with regard to age, ethnic group, and sex. OUTCOME MEASURES: The NHES is the only national survey that contains body measurements biologically appropriate for predicting stature. These measurements include stature, sitting height, knee height, and buttocks to knee length. STATISTICAL ANALYSIS: Equations were computed from an all-possible-subsets of weighted regression procedure to select the predictor variables in the validation group based on the values of R2 and the root mean square error. RESULTS: Knee height predicted stature for white and black men, but the predictor variables for white and black women were knee height and age. For predicting stature in children 6 to 18 years of age, the predictor variable was knee height for all children. APPLICATIONS: The equations presented here were developed for use with mobility-impaired or handicapped persons, but the measurements were collected from ambulatory people by means of standard techniques. The use of recumbent anthropometric data from mobility-impaired or handicapped persons in the equations will expand the errors of prediction over those presented in this report. The standard error for a person is a guide to the range of probability within which a predicted value can occur.

Adolescent↗
PubMed1994

Incidence and prediction of induced ventricular tachyarrhythmias in idiopathic dilated cardiomyopathy.

The value of time-domain and spectral turbulence analyses of the signal-averaged electrocardiogram (SAECG) for predicting induction of sustained monomorphic ventricular tachycardia (VT) was prospectively investigated in 70 patients with idiopathic dilated cardiomyopathy. Sustained VT was induced in 9 patients (13%). The prevalence of abnormal time-domain and spectral analyses was 16 and 37%, respectively. The total predictive accuracy of time-domain and spectral analyses for VT induction was 86 and 67%, respectively (p < 0.01). The predictive accuracy of time-domain and spectral analysis was similar in patients without an intraventricular conduction defect (94 and 84%, respectively). However, the predictive accuracy of time-domain was higher than that of spectral analysis in patients with an intraventricular conduction defect (65 vs 25%; p < 0.05). The poor concordance between spectral analysis and programmed stimulation results was mainly due to the high number of false-positive recordings in the presence of an intraventricular conduction defect (9 of 20 cases). With the use of stepwise discriminant function analysis, an abnormal time-domain SAECG was the only variable predicting the induction of sustained VT (p < 0.0003). In dilated cardiomyopathy, an abnormal time-domain SAECG and induced sustained VT are rare, both time-domain signal-averaged electrocardiography and spectral analysis have a high predictive accuracy for VT induction in patients without an intraventricular conduction defect, and spectral analysis does not improve VT prediction in those with a conduction defect.

Analysis of Variance↗
PubMed1995

Predictive factors from cold knife conization for residual cervical intraepithelial neoplasia in subsequent hysterectomy.

OBJECTIVE: The optimal management of cervical intraepithelial neoplasia after cold knife conization remains controversial. Reliable predictors of residual dysplasia in the cervix after cold knife conization have not been consistently identified. This study was initiated to examine the accuracy of the traditional factors used to predict residual dysplasia in hysterectomy specimens after cold knife conization. STUDY DESIGN: A retrospective 10-year chart review identified a cohort of 1272 patients who underwent cold knife conization, of whom 311 had a subsequent hysterectomy within 1 year of conization. Residual disease was defined as cervical intraepithelial neoplasia or cancer in the hysterectomy specimen. All cone specimens were completely submitted for pathologic examination, and the following factors were analyzed for their predictive value: degree of dysplasia, margin involvement, endocervical gland involvement, and status of the endocervical curettage. The predictive value of age, race, gravidity, parity, socioeconomic status, cigarette smoking, and marital status were also examined. The chi 2 test, t test, and logistic regression were used for statistical analysis. RESULTS: Dysplasia or cancer were identified in 1066 (84%) of the 1272 patients who underwent cold knife conization. Of the 311 patients having a subsequent hysterectomy, 106 (34%) had residual disease in their hysterectomy specimen. By multivariate analysis only increasing age and degree of dysplasia were predictive of residual disease. The odds ratio of residual disease in the hysterectomy specimen for a 25-year-old woman was 2.7 (95% confidence interval 1.6 to 4.4) compared with a 40-year-old woman whose odds ratio was 4.9 (95% confidence interval 2.2 to 10.8). The presence of dysplasia in the cold knife conization specimen conferred an odds ratio of 12.1 (95% confidence interval 2.7 to 54.5) of identifying residual disease. Dysplasia involving the ectocervical margin, endocervical margin, and endocervical glands was not predictive of disease in the hysterectomy specimens. Endocervical curettage was not performed in 44% of the patients, preventing reliable statistical evaluation. Further analysis indicated that residual disease was found in 32% of the hysterectomy specimens with negative margins, in 31% with no endocervical gland involvement, and in 23% with a negative endocervical curettage sample. CONCLUSIONS: The presence or absence of dysplasia in the cold knife conization ectocervical margin, endocervical margin, and endocervical glands was not predictive of residual dysplasia in post-cold knife conization hysterectomy specimens. Increasing age and severity of disease in the cone specimen were the only factors that accurately predicted residual dysplasia. The traditional factors used to justify hysterectomy after cold knife conization may not be valid on the basis of these results.

Adolescent↗
PubMed1979

A comparison of four methods of predicting arch length.

1. Four arch length prediction equations (Nance, Johnston-Tanaka, Moyers, and Hixon-Oldfather) were compared by examining pretreatment casts, pretreatment intraoral radiographs, and posttreatment casts of forty-one patients of mixed-dentition age. 2. A comparison of correlation coefficients and slopes of the predicted arch length versus the actual arch lengths revealed that the Hixon-Oldfather method conformed closest to the ideal. 3. No combination of the four methods produced a more accurate equation than the single most accurate method. 4. Neither the sex of the patient nor the type of occlusion affected the prediction accuracy of any of the four equations. 5. All methods tend to overpredict the arch length size by 1 to 3 mm., with the exception of the Hixon-Oldfather equation, which underpredicted by approximately 0.5 mm. 6. An analysis of the intrainvestigator error showed a very low standard error of estimate for individual tooth measurements and for the prediction values. 7. A variance analysis showed that most of the variation was due to arch length (85%), a slight amount was due to the prediction method (8%), and 6% of the variation was due to the rater. 8. A low correlation was found between space available versus actual discrepancy and space available versus actual arch length. 9. High correlation coefficients were found for the predicted arch lengths when compared with the actual arch lengths. As expected, the correlation coefficients for the predicted widths of only the canines and premolars compared with the actual widths were not quite as high.

Bicuspid↗