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PubMed2006

Prediction of cytochrome p450-mediated hepatic drug clearance in neonates, infants and children : how accurate are available scaling methods?

Correct dosing of drugs in neonates, infants and children is hampered by a general lack of knowledge about drug disposition in this population. Suggested methods to improve our knowledge without performing conventional full-scale investigations include population pharmacokinetic studies, allometric scaling of drug disposition according to bodyweight and in silico prediction of pharmacokinetics. The last method entails scaling of pharmacokinetic parameters according to age-dependent changes in drug absorption and elimination capacity, plasma protein binding and physiological characteristics of the subjects. Maturation (or ontogeny) of the drug-metabolising part of the cytochrome P450 (CYP) enzyme system is thus an important factor in the calculations for most drugs. The aim of this commentary is to test and critically examine the proposed methods to estimate hepatic clearance (CL) as a function of age (0-20 years), with CYP3A-mediated metabolism as the case in point. Midazolam and alfentanil were used as model drugs. Allometric scaling failed to predict the CL of midazolam and alfentanil in neonates. Calculations using in vitro findings on CYP maturation gave better estimates for neonates but very divergent ones for older infants and children. This was chiefly due to very different data on CYP3A4/5 ontogeny in three published studies. In the age range where full adult CYP activity per gram of liver could be assumed, allometric scaling and in silico predictions gave similar results. These predictions were also in approximate agreement with clinical data.The findings with the two model drugs can very probably be generalised to most drugs cleared by CYP-dependent hepatic metabolism. Allometric scaling accounts for development of body size and function but not for the fact that the drug-metabolising capacity of the liver is generally low at birth. The crucial question in the prediction of CL is thus when the activity of the applicable CYP isoform(s) attains adult levels. There are still not enough data on this, particularly when different studies even on the same CYP isoform have given very divergent results. It may also be pointed out that CYP ontogeny is an area where we have at least some information. There are several other important developmental changes about which we know practically nothing. Thus, while allometric scaling is generally unreliable for prediction in neonates and infants, the alternative method of in silico prediction can at present be used only to obtain tentative initial estimates of drug CL. Neither of the methods can be used as a substitute for actual clinical studies.

Aging↗
PubMed2003

Physiological approaches to the prediction of drug-drug interactions in study populations.

The prediction of metabolic drug-drug interactions should include quantitative attributes, such as variability in the study populations, and the results should be presented in terms of probability and uncertainty. The simple algebraic equations used to calculate one mean value for the extent of drug-drug interaction are adequate for qualitative or semi-quantitative risk assessment. However, truly quantitative predictions continue to fail. The success of drug-drug interaction predictions requires understanding of the relationship between drug disposition and quantifiable influential factors on the change in systemic exposure. The complex interplay of influential factors, including variability estimates, on successful prediction of drug interaction have not been systematically examined. Therefore, physiologically relevant models of metabolic drug-drug interaction will likely play increasingly important roles in improving quantitative predictions and in the assessment of the influential factors underlying the interactions. The physiologically-based approach, with stochastic considerations, offers a powerful alternative to the empirical calculation of mean values. In addition to quantitative estimation of the interaction for assessing probability of risk, a reasonably validated predictive model is useful for prospective optimization of study designs. As a consequence, the definitive clinical trial would yield more meaningful information to support dosing recommendations. This review focuses on illustrating the importance of an integrated approach to building useful models for prediction of metabolism-based drug-drug interactions in human subjects.

Animals↗
PubMed2004

Dynamic perfusion MRI versus perfusion scintigraphy: prediction of postoperative lung function in patients with lung cancer.

OBJECTIVE: The purpose of this study was to determine the capability of dynamic perfusion MRI as an alternative to pulmonary perfusion scintigraphy for prediction of postoperative lung function in patients with lung cancer. SUBJECTS AND METHODS. Sixty patients with lung cancer (35 men, 25 women) underwent dynamic perfusion MRI, perfusion scintigraphy, and preoperative and postoperative pulmonary function tests (forced expiratory volume in 1 sec [FEV(1)]). Perfusion MRIs were obtained with a 3D turbo field-echo sequence (TR/TE, 2.7/0.6; flip angle, 40 degrees; matrix, 128 x 96) using a 1.5-T scanner. Regional blood flow was calculated from the signal intensity-time curves after bolus injection of contrast medium on MRI (Q(MRI)) and uptake ratios of radioisotope on perfusion scintigraphy (Q(PS)). Postoperative lung functions predicted by MRI (FEV(1,MRI)) and perfusion scintigraphy (FEV(1,PS)) were calculated from preoperative FEV(1) and regional Qs. To determine the capability of MRI as an alternative to scintigraphy, we evaluated correlations and the limits of agreement between predicted FEV(1,MRI) and postoperative FEV(1) and between predicted FEV(1,PS) and postoperative FEV(1). RESULTS: The correlation coefficient of postoperative FEV(1) with FEV(1,MRI) (r = 0.93, p < 0.0001) was better than that with FEV(1,PS) (r = 0.89, p < 0.0001). The limits of agreement between postoperative FEV(1) and predicted FEV(1,MRI) (0.9% +/- 10.4%) were smaller than those between postoperative FEV(1) and predicted FEV(1,PS) (2.1% +/- 13.2%). CONCLUSION: Dynamic perfusion MRI is a feasible alternative to pulmonary perfusion scintigraphy for predicting postoperative lung function in patients with lung cancer.

Adult↗
PubMed1995

The effects of orientation and storage time on the prediction of beef rib composition using electromagnetic scanning.

To investigate the effects of orientation of beef ribs in an electromagnetic field and storage time on the prediction of rib composition, 64 ribs (IMPS 103) were scanned (2.5 MHz) in three different orientations: posterior end first (POS), dorsal end first (DOR), and fat side first, blade end down (BLD). Scans were obtained after 1 and 5 d of storage. Scan peak, rib weight, 3/4 fat depth, length, and temperature were used to predict percentage and weight of dissectable and fat-free lean. The mean peak for the BLD scans was four to six times higher than the POS or DOR scans. Ribs scanned in the BLD orientation on d 5 had the highest coefficient of determination (CD; 94.0) and the lowest residual standard deviation (RSD; .22 kg) for prediction of lean weight. The POS and DOR scans were similar at d 5 (CD = 91.4 and 90.3, respectively) with RSD of .30 and .31 kg, respectively. Prediction of lean percentage resulted in lower CD than predicting lean weight. For percentage of lean, BLD scans at d 5 once again resulted in the best CD (81.6) and lowest RSD (1.5%). Prediction of percentage lean using POS or DOR orientation resulted in CD of 71.2 and 67.1 and RSD of 2.0 and 2.1%, respectively. The CD were similar for POS and DOR scans at d 1 and d 5. Predicting fat-free lean weight resulted in equal or lower CD than dissected lean and higher CD for lean percentage. It seems that orientation during scanning, when consistent, is not a major concern.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1997

Predicting carcass composition and individual feed requirement in live cattle widely varying in body size.

A total of 192 feeder steers of five breed types and body sizes commonly found in the United States cattle population were fed high-energy diets to three endpoints (275-, 300-, and 360-kg carcass weights) to determine their carcass composition. Before slaughter, ultrasound was used to predict fat thickness, longissimus muscle area, and marbling. Individual steer data were used for developing prediction equations, which were validated with three independent data sets. These data were used to develop and validate equations to predict carcass composition and DM requirements for individuals fed in pens and varying in breed type, body weight and size, and ADG. Equations to predict carcass weight during growth accounted for 84, 83, and 88% of the variation in the three data sets with 0, 1, and 3% bias. An equation to predict percentage of carcass fat from fat thickness and equivalent shrunk weight accounted for 96% of the variation in the percentage of carcass fat. An equation to predict yield grade from longissimus muscle area per 100 kg, fat thickness, and equivalent shrunk weight accounted for 93% of the variation. Dry matter requirement predicted by the system for individuals accounted for 48% of the variation in actual DMI with a 3% overprediction bias. The equations allow the user to allocate feed to individual animals in group-feeding environments along with marketing cattle on an individual basis at optimum endpoints given cattle types, feeding costs, and market prices.

Animals↗
PubMed2001

Predicting percentage of intramuscular fat using two types of real-time ultrasound equipment.

In the present study, 500 steers were used to develop models for predicting the percentage of intramuscular fat (PIMF) in live beef cattle. Before slaughter, steers were scanned across the 11th and 13th ribs using Aloka 500V (AL-500) and Classic Scanner 200 (CS-200) machines. Four to five images were collected per individual steer using each machine. After slaughter, a cross-sectional slice of the longissimus muscle from the 12th rib facing was used for chemical extraction to determine actual carcass percentage of intramuscular fat (CPIMF). Texture analysis software was used by two interpreters to select a region for determination of image parameters, which included Fourier, gradient, histogram, and co-occurrence parameters. Four prediction models were developed separately for each of AL-500 and CS-200 based on images captured by the respective machines. These included models developed without transformation of CPIMF (Model I), models based on logarithmic transformation of CPIMF (Model II), ridge regression procedure (Model III), and principal component regression procedure (Model IV). Model R2 and root mean square error of AL-500 Models I, II, III, and IV were 0.72, 0.84%; 0.72, 0.85%; 0.69, 0.91%; and 0.71, 0.86%; respectively. The corresponding R2 and root mean square error values of CS-200 Models I, II, III, and IV were 0.68, 0.87%; 0.70, 0.85%; 0.64, 0.94%; and 0.65, 0.91%; respectively. Initially, AL-500 and CS-200 prediction models were validated separately on an independent data set from 71 feedlot steers. The overall mean bias, standard error of prediction, and rank correlation coefficient across the four AL-500 models were 0.42%, 0.84%, and 0.88, respectively. For the four CS-200 models, the corresponding overall mean values were 0.67%, 0.81%, and 0.91, respectively. In a second validation test, only Model II of AL-500 and CS-200 was evaluated separately based on data from 24 feedlot steers. The overall mean bias, absolute difference, and standard error of prediction of AL-500 Model II were 0.71, 0.92, and 0.98%. For CS-200 Model II, the corresponding values were 0.59, 0.97, and 1.03%. Both AL-500 and CS-200 equipment can be used to accurately predict PIMF in live cattle. Further improvement in the accuracy of prediction equations could be achieved through increasing the development data set and the variation in PIMF of cattle used.

Adipose Tissue↗
PubMed2004

Evaluation of procedures to predict fat-free lean in swine carcasses.

The objectives were to develop equations for predicting fat-free lean in swine carcasses and to estimate the prediction bias that was due to genetic group, sex, and dietary lysine level. Barrows and gilts (n = 1,024) from four projects conducted by the National Pork Board were evaluated by six procedures, and their carcass fat-free lean was determined. Pigs of 16 genetic groups were fed within weight groups one of four dietary regimens that differed by 0.45% in lysine content and slaughtered at weights between 89 and 163 kg. Variables in equations included carcass weight and measures of backfat depth and LM. Fat-free lean was predicted from measures of fat and muscle depth measured with the Fat-O-Meater (FOM), Automated Ultrasonic System (AUS), and Ultrafom (UFOM) instruments, carcass 10th-rib backfat and LM area (C10R), carcass last-rib backfat (CLR), and live animal scan of backfat depth and LM area with an Aloka 500 instrument (SCAN). Equations for C10R (residual standard deviation, RSD = 2.93 kg) and SCAN (RSD = 3.06 kg) were the most precise. The RSD for AUS, FOM, and UFOM equations were 3.46, 3.57, and 3.62 kg, respectively. The least precise equation was CLR, for which the RSD was 4.04 kg. All procedures produced biased predictions for some genetic groups (P < 0.01). Fat-free lean tended to be overestimated in fatter groups and underestimated in leaner ones. The CLR, FOM, and AUS procedures overestimated fat-free lean in barrows and underestimated it in gilts (P < 0.01), but other procedures were not biased by sex. Bias due to dietary lysine level was assessed for the C10R, CLR, FOM, and SCAN procedures, and fat-free lean in pigs fed the lowlysine dietary regimen was overestimated by CLR, FOM, and SCAN (P < 0.05). Positive regressions of residuals (measured fat-free lean minus predicted fat-free lean) on measured fat-free lean were found for each procedure, ranging from 0.204+/-0.013 kg/kg for C10R to 0.605+/-0.049 kg/kg for UFOM, indicating that all procedures overestimated fat-free lean in fat pigs and underestimated it in lean pigs. The pigs evaluated represent the range of variation in pigs delivered to packing plants, and thus the prediction equations should have broad application within the industry. Buying systems that base fat-free lean predictions on measures of carcass fat depth and muscle depth or area will overvalue fat pigs and undervalue lean pigs.

Adipose Tissue↗
PubMed1994

Term prediction in routine ultrasound practice.

STUDY OBJECTIVE: Evaluation of the precision of routine ultrasound term prediction. DESIGN: Population based follow-up without intervention. SETTING: Ultrasound screening in routine clinical practice. MATERIAL: 1650 women residing in one Norwegian county giving birth during a 12-month period. All pregnancies were singleton with spontaneous onset of labor, all records contained a term predicted with routine ultrasound in the second trimester. OUTCOME MEASURE: Difference between actual and predicted day of delivery, and difference between ultrasound predicted term and term calculated from last menstrual period. MAIN RESULTS: More women delivered within two weeks of ultrasound term than two weeks of term calculated from the last menstrual period (87.5% and 79.3%, p < 0.001). Deliveries were significantly closer to the ultrasound predicted term than the term calculated from the last menstrual period, with the exception of deliveries in the 39th week after LMP where no significant difference was found between ultrasound term and LMP-term. No difference was found in the mean performance of 14 different ultrasound operators. CONCLUSIONS: In a population representative of deliveries in one county, routine ultrasound term prediction performed in three medium sized hospitals more accurately predicted day of delivery than term calculated from the date of last menstrual period.

Analysis of Variance↗
PubMed1994

Prediction of acetaminophen concentrations in overdose patients using a Bayesian pharmacokinetic model.

A pharmacokinetic program using population-based parameter estimates and a Bayesian forecasting model was retrospectively evaluated for predicting acetaminophen serum concentrations in overdose patients. Dynamic disposition factors known to affect acetaminophen disposition (emesis, activated charcoal, N-acetylcysteine, etc.) were included in the program. Twenty six patients who reported an acetaminophen ingestion of at least 70 mg/kg within 24 h of presentation to the hospital and had at least one measured acetaminophen concentration were included. Prediction of initial acetaminophen concentrations using only population-based parameter estimates resulted in a percent mean error (%ME) and percent mean absolute error (%MAE) of 9.3 and 42.2, respectively. Using only the initial concentration as feedback, the Bayesian forecasting model accurately predicted the second acetaminophen concentration (%ME = 4.0, %MAE = 23.6). The Bayesian model also accurately predicted all concentrations within 8 h of the ingestion (%ME = 10.6, %MAE = 24.0). The prediction of concentrations between 2 to 4 h and 4 to 4.5 h after ingestion with only population-based parameter estimates resulted in %ME of 17.0 and 13.2, respectively, and %MAE of 36.5 and 35.1, respectively. Our data suggests that acetaminophen serum concentrations occurring within the first 4.5 h after ingestion can be reliably predicted by the set of population-based parameter estimates evaluated. Once a single acetaminophen concentration is available, the Bayesian forecasting model can accurately predict subsequent concentrations within the first 8 h after an acetaminophen ingestion.

Acetaminophen↗
PubMed2002

Prediction of most recent evaluations of Holstein bulls from first available pedigree information.

The objectives of this study were to predict most recent evaluations of young bulls entering artificial insemination (AI) sampling programs from pedigree information available at time of sampling and investigate whether prediction equations differ among AI organizations. Data were pedigree information and most recent USDA evaluations on bulls entering AI sampling programs from 1989 through 1994. Pedigree information included earliest available parent average, predicted transmitting abilities (PTA) of sire, dam, and maternal grand sire. Most recent evaluations were from May 2000 evaluations and included PTA and daughter yield deviations for milk, fat, and protein. Regression coefficients on PTA of sire and PTA of dam were less than the expected coefficient of 0.50. Accuracy of prediction as determined by R-square values was less than 12%. Inclusion of PTA of maternal grand sire after PTA of sire and dam increased the accuracy of prediction by less than 1%, but regression coefficients on PTA of maternal grand sire differed from 0. Regressions on parent average were not different among AI organizations for prediction of PTA and daughter yield deviations. Partial regression coefficients on PTA of sire differed among AI organizations for prediction of fat and protein but did not differ for milk. Coefficients on PTA of dam did not differ among organizations. These results indicate that AI organizations put different emphasis on PTA of sire in selection of sons for fat and protein.

Animals↗
PubMedDate not supplied

A new method of predicting US and state-level cancer mortality counts for the current calendar year.

Every January for more than 40 years, the American Cancer Society (ACS) has estimated the total number of cancer deaths that are expected to occur in the United States and individual states in the upcoming year. In a collaborative effort to improve the accuracy of the predictions, investigators from the National Cancer Institute and the ACS have developed and tested a new prediction method. The new method was used to create the mortality predictions for the first time in Cancer Statistics, 2004 and Cancer Facts & Figures 2004. The authors present a conceptual overview of the previous ACS method and the new state-space method (SSM), and they review the results of rigorous testing to determine which method provides more accurate predictions of the observed number of cancer deaths from the years 1997 to 1999. The accuracy of the methods was compared using squared deviations (the square of the predicted minus observed values) for each of the cancer sites for which predictions are published as well as for all cancer sites combined. At the national level, the squared deviations were not consistently lower for every cancer site for either method, but the average squared deviations (averaged across cancer sites, years, and sex) was substantially lower for the SSM than for the ACS method. During the period 1997 to 1999, the ACS estimates of deaths were usually greater than the observed numbers for all cancer sites combined and for several major individual cancer sites, probably because the ACS method was less sensitive to recent changes in cancer mortality rates (and associated counts) that occurred for several major cancer sites in the early and mid 1990s. The improved accuracy of the new method was particularly evident for prostate cancer, for which mortality rates changed dramatically in the late 1980s and early 1990s. At the state level, the accuracy of the two methods was comparable. Based on these results, the ACS has elected to use the new method for the annual prediction of the number of cancer deaths at the national and state levels.

Cause of Death↗
PubMed2026

Addition of CAD polygenic risk score to coronary artery calcium score enhances prediction of MACE.

BACKGROUND: Coronary heart disease (CHD) is prevalent in the United States, highlighting the need for accurate risk prediction to inform primary prevention strategies. While multivariate risk models like the Framingham Risk Score and ACC/AHA Pooled Cohort Equations are commonly utilized, novel risk markers, such as the coronary artery calcium score (CACS) and polygenic risk score (PRS), are increasingly gaining recognition. OBJECTIVES: This study aimed to compare the diagnostic utility of CACS and CAD PRS, both individually and in combination, for predicting major adverse cardiovascular events (MACE). METHODS: We conducted a retrospective analysis of a cohort comprising 1,380 predominantly Caucasian participants from the Sanford Health System. CAD PRS was constructed using genetic variants, while CACS was assessed via cardiac computed tomography (CT). Statistical analyses evaluated the relationship between each modality and MACE. RESULTS: Both CAD PRS and CACS were significantly associated with future MACE. Following the adjustment for covariates, the area under the curve (AUC) for both the CACS and PRS models was comparable, indicating similar predictive capabilities for MACE. However, the combination of CAD PRS with CACS significantly enhanced predictive accuracy, outperforming either modality alone. CONCLUSIONS: This study underscores the value of integrating CACS and CAD PRS in predicting MACE. The synergistic effect of CAD PRS combined with CACS markedly improves predictive power. Further research and prospective studies are necessary to validate these findings and assess their clinical implications. Investigating the interactions between PRS and CACS will be crucial for refining cardiovascular risk prediction and optimizing prevention strategies.

cardiac genetics↗
PubMed2006

Evaluating microbial safety of slow partial-cooking processes for bacon: use of a predictive tool based on small-scale isothermal meat inoculation studies.

The objective of this study was to develop a predictive tool for evaluating the safety of slow cooking of pork products and identifying associated critical limits. Small-scale (25 g) ground pork isothermal inoculation studies were done to determine Salmonella serovars, Escherichia coli O157:H7, and Staphylococcus aureus estimated critical times (time until growth reached a predefined increase of concern). Estimated critical time values ranged from 720 min at 21 degrees C (S. aureus) to 120 min at 40.6 degrees C (E. coli O157:H7) and were used to develop a multiple-temperature-interval predictive tool for non-isothermal processes. To test predictions, cured-pumped pork bellies were inoculated with Salmonella serovars, E. coli O157:H7, and S. aureus, subjected to slow partial cooking, and quantitatively analyzed for pathogens. Processes lasted 6 to 18 h, with the product interior temperature within the 21 to 46 degrees C range for 263 to 1080 min (high-humidity processes) and 217 to 921 min (low-humidity processes). Growth of Salmonella serovars (>0.3 log), E. coli O157:H7 (>0.3 log), and S. aureus (>1.3 log) in the pork belly interior was predicted for 10, 14, and 5 of 18 trials, respectively. The tool was fail-safe, because pathogen growth, relative to time zero, did not occur anytime regardless of whether it was predicted. For the pork belly surface, the tool performed similarly. Estimated critical time values obtained by fitting the Baranyi equation to isothermal experiment data were also determined and, if used in the predictive tool, would result in even more conservative predictions. Our study substantiates the safety of the tested bacon slow partial-cooking processes and the potential usefulness of our isothermal-based tool in process safety evaluation.

Animals↗
PubMedDate not supplied

The predictive power of narrative data in occupational therapy evaluation.

OBJECTIVE: This study examined whether adding the Canadian Occupational Performance Measure (COPM) to existing occupational therapy evaluation measures used in a subacute skilled nursing facility unit enhanced the accuracy of therapists' predictions of the functional status of clients at discharge. METHOD: This study utilized a prospective comparison design. Two independent predictive variables were developed using the standard Functional Independent Measure (FIM), and an enhanced FIM that included narrative information from the Canadian Occupational Performance Measure (FIM/COPM). These variables were subsequently compared with the actual FIM discharge (DFIM) scores for 31 clients. The primary author (D.S.) gathered data from chart review and conducted the statistical analysis. The data were analyzed using descriptive correlations (Pearson r) and comparison statistics (Wilcoxon signed rank test). RESULTS: Comparison statistics (Wilcoxon signed rank test) revealed a statistically significant difference between the standard FIM predictive score and the discharge FIM score. No statistically significant difference was found between the FIM/COPM predictive score and the discharge FIM score. These findings suggest that predictive scores based solely on information attained from the standard FIM resulted in less accuracy in outcome predictions. Correlational analyses further supported these conclusions. CONCLUSION: The findings support the study hypothesis that use of the COPM in combination with the FIM enhances accuracy in prediction of outcomes for rehabilitative services for persons in adult physical disabilities settings.

Activities of Daily Living↗
PubMedDate not supplied

Predicting survival of patients with sepsis by use of regression and neural network models.

OBJECTIVES: (1) To predict at the time of diagnosis of sepsis the subsequent occurrence of multiple organ failure and patient death; and (2) to compare the prediction accuracies of standard multiple logistic regression (MLR) and neural network (NN) models. METHODS: The data were collected during a 5-year period for all patients (n=173) who met prospectively determined criteria for sepsis and had positive blood culture results while admitted in the surgical intensive care unit at the University Hospital of Geneva, Switzerland. These data formed the basis for a retrospective cohort study described elsewhere. The MLR model was adapted from existing data. An NN model of the feed-forward, back-propagation type was constructed for predicting the outcome of sepsis with bloodstream infection. Both models were constructed from randomly chosen subsets of patients and subsequently were evaluated on the remaining (independent) patients. RESULTS: Survival after sepsis was predicted with an accuracy of 80% by the NN model, which used only information collected at the time of the diagnosis of sepsis. The development of multiple organ failure after the diagnosis of sepsis was predicted accurately (81.5%) with either the MLR or the NN model. Both the MLR and the NN methods depended on the interpretation of a likelihood quantity, requiring the choice of a threshold to make a survival prediction. The accuracy of the MLR models was very sensitive to the threshold value. The accuracy of the NN models was not sensitive to the choice of threshold, because they generated likelihood predictions that were distributed far from the middle range where the threshold was placed. CONCLUSION: Compared with MLR models, the NN models were slightly more accurate and much less sensitive to the arbitrary threshold parameter.

Bacterial Infections↗
PubMed1999

Predictive value of PAI-1 plasma activity and thallium perfusion imaging for restenosis after percutaneous transluminal angioplasty in clinically asymptomatic patients.

BACKGROUND: The main long-term complication of percutaneous transluminal coronary angioplasty (PTCA) is restenosis that occurs in 30-50 percent of all primary successful cases. The purpose of this study was to evaluate the predictive value of changes in plasminogen activator inhibitor-1 (PAI-1) activity and of thallium dipyridamole perfusion imaging performed 3 months after successful angioplasty. All patients were asymptomatic at evaluation. The results of these two noninvasive tests were compared with the angiographic outcome after 6 months. METHOD AND PATIENTS: Twenty-five patients were included in this prospective study. All patients had single vessel disease, successful angioplasty and were free of clinical symptoms 3 months after angioplasty that would suggest late restenosis. In 12/25 patients (48%) angiographic restenosis (percent diameter stenosis >50%) was determined by follow-up angiography 6 months after angioplasty. PAI-1 plasma activity was determined by a functional titration assay and increase or decrease of PAI-1 plasma activity was evaluated between values obtained before and 3 months after angioplasty. In 7/25 (28%) patients PAI-1 plasma activity increased to more than 90% of pre-angioplasty values. This increase correlated with angiographic restenosis evaluated 6 months after angioplasty (sensitivity 42%, specificity 85%, positive predictive value 71%, and negative predictive value 61%). T1-201-perfusion imaging was performed 3 months after angioplasty. This test was indicative for subsequent restenosis in 5/25 patients (sensitivity 33%, specificity 100%, positive predictive value 62%, and negative predictive value 100%). In 10/25 (40%) patients at least one of the two non-invasive tests performed 3 months after angioplasty predicted angiographic restenosis at 6 months: the combined use of PAI-1 and T1-201-perfusion imaging resulted in increased sensitivity (67%) and high specificity (85%). CONCLUSION: The results of this study indicate that an increase of PAI-1 plasma activity may improve the predictive value for restenosis of T1-201-scintigraphy performed 3 months after angioplasty even in asymptomatic patients.

Angioplasty, Balloon, Coronary↗
PubMed1999

Prediction accuracy of soft tissue profile in orthognathic surgery.

The purpose of this study was to compare soft tissue prediction accuracy of model surgery combined with computer software prediction with that of computer software prediction alone and to assess surgical accuracy by comparing the immediate postsurgical cephalogram with the planned movement of skeletal hard tissue. The predicted and actual soft tissue changes and the corresponding skeletal changes of 16 patients were compared using the Quick Ceph Image cephalometric treatment simulation software. A custom analysis was created to measure the hard tissue and soft tissue changes that occurred as a result of the surgical procedure. On average, the predictions were not significantly different from the actual postsurgical profile changes. Surgical changes of hard tissues from presurgery to postsurgery were accurate as planned except for the position of N-ANS. All lower soft tissue points moved significantly during treatment. Quick Ceph Image offers a rapid and reliable method of profile prediction that does not require artistic skill. If predictions are interpreted with caution and transferred accurately to the model surgery, they can provide an excellent visual aid during presurgical treatment planning and patient presentation.

Adolescent↗
PubMed1999

[Hyperbilirubinemia in full-term newborns. Predictive factors].

OBJECTIVE: Nowadays economical criteria lead to early maternal hospital discharge, even before 48 hours after labor, producing an increase in neonatal readmissions for hyperbilirubinemia. We tried to predict the healthy term newborns that may develop a significant hyperbilirubinemia (> or = 17 mg/dl in the first 4 days of life). METHODS: Bilirubin in umbilical cord blood, transcutaneous measurements of bilirubin at 24, 48 and between 60 and 96 hours of life and bilirubin in blood obtained from heel-sticks at 96 hours was analyzed in 610 newborns. Moreover, serum bilirubin was determined at the same time-points in 169 newborns submitted to blood extractions for different reasons. The transcutaneous bilirubinometer used was a Minolta/Air-Shields JM-102. RESULTS: A significant hyperbilirubinemia was present in 2.95% of the newborns. The correlation between serum and transcutaneous bilirubin was high (r = 0.92; p < 0.0001). Umbilical cord blood bilirubin with a cut-off point of 2.2 mg/dl was not an useful predictor of neonatal jaundice. At 24 and 48 hours of life serum bilirubin levels > or = 6 mg/dl and > or = 9 mg/dl, respectively, predicted a subsequent hyperbilirubinemia with a sensitivity of 100% at both time-points, specificity of 47.5% and 64.3%, positive predictive value of 7.3% and 16.4%, respectively, and a negative predictive value of 100% for both. Transcutaneous measurement at 48 hours with a cut-off point of 13 (equivalent to a bilirubinemia of 9 mg/dl) predicts hyperbilirubinemia with a sensitivity of 94.4%, specificity of 51.7%, positive predictive value of 6.0% and negative predictive value of 99.6%. CONCLUSIONS: If the newborn presents a bilirubinemia > or = 6 mg/dl at 24 hours and > or = 9 mg/dl or a transcutaneous measurement > or = 13 at 48 hours a new bilirubin measurement must be performed between 48 and 72 hours of life.

Bilirubin↗