Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Predictive”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42Linked to original sources
PubMedDate not supplied

Hyperacute extensive middle cerebral artery territory infarcts. Role of computed tomography in predicting outcome.

OBJECTIVE: To assess the prognostic value of computed tomography (CT) in hyperacute middle cerebral artery (MCA) infarcts. METHODS: The CT features, total CT score, and National Institutes of Health Stroke Scale (NIHSS) score were correlated with the 30-day mortality in 16 patients with a hyperacute MCA infarct. RESULTS: Admission NIHSS scores were significantly lower in the survival group (P = 0.016). The extent of infarct, attenuation of corticomedullary differentiation, and total CT score were associated with 30-day mortality (P < 0.05). In prediction of mortality, extent of an infarct > 67% gave sensitivity, specificity, positive predictive value, and negative predictive value rates of 86%, 100%, 100%, and 90%, respectively. Attenuation of corticomedullary differentiation gave sensitivity, specificity, positive predictive value, and negative predictive value rates of 86%, 89%, 86%, and 89%, respectively. An NIHSS score > 28 gave sensitivity, specificity, positive predictive value, and negative predictive value rates of 86%, 67%, 67%, and 86%, respectively. A CT score > 4 gave sensitivity, specificity, positive predictive value, and negative predictive value rates of 86%, 78%, 75%, and 88%, respectively. CONCLUSIONS: Computed tomography features and the admission NIHSS score are important predictors of survival in hyperacute extensive MCA infarcts.

Aged↗
PubMed1995

Predictive performance of four pharmacokinetic methods for calculating digoxin dosage.

An evaluation was made of the performance of the Sheiner, Koup, Dobbs and Paulson methods for predicting total body clearance of digoxin in 59 patients with and without congestive heart failure (CHF). The predicted clearances were then used to predict the steady-state serum concentrations of digoxin. Actual serum concentrations were measured at steady state following single oral daily doses of digoxin for at least 1 month. Predictive performance was determined for each method by calculating the mean prediction error (ME) and the mean squared prediction error (MSE). Ninety-five per cent confidence intervals and correlation coefficients were also calculated. The prediction bias and precision of the methods were compared statistically by calculating the 95% confidence intervals of the delta ME and delta MSE. For patients with CHF, the Sheiner method was the least biased and the most precise for predicting observed serum levels. For patients without CHF, no significant difference between the Sheiner and Koup methods, and between the Dobbs and Paulson methods were seen, although the former two methods were less biased and more precise than the latter two. The Sheiner method was used as the basis for evaluating the performance of the three other methods in predicting digoxin clearance from patients with and without CHF. This revealed that the Koup, Dobbs and Paulson methods tended to overpredict clearances in patients with CHF; on the other hand, for patients without CHF, the Koup method was the least biased and the most precise of the three methods.

Adult↗
PubMed2005

Prediction of gestational diabetes mellitus in a high-risk group by insulin measurement in early pregnancy.

AIMS: We hypothesized that an increased serum insulin level in early pregancy reflects an increased demand on the compensatory capacity of the pregnant woman, and can serve as a predictor of gestational diabetes mellitus (GDM). METHODS: A 2-h, 75-g oral glucose tolerance test (OGTT), with fasting and 2-h postprandial serum insulin determination, was performed in 71 pregnant women with one or more risk factors for GDM before gestation week 16. In 64 patients, subsequent OGTTs were performed at gestation weeks 24-28, and in the event of a negative result, at gestation weeks 32-34. RESULTS: Insulin determination at fasting and at 120 min had sensitivities of 69.2% and 92.3%, and specificities of 96.4% and 85.7%, respectively, for the prediction of GDM at gestation weeks 24-28. The sensitivities decreased to 33.3% and 75.0%, respectively, for the prediction of GDM at gestation weeks 32-34. Insulin determination at fasting and at 120 min had positive predictive values of 0.90 and 0.75, respectively, for the prediction of GDM at gestation weeks 32-34. The negative predictive values of fasting and 120-min serum insulin determination at gestation week < or = 16 were 0.87 and 0.96, respectively, for the prediction of GDM at gestation weeks 24-28. Increased serum insulin levels both at fasting and 120 min before gestation week 16 were very strong predictive factors for GDM by gestation weeks 32-34 with an odds ratio of 16.6 and 13.3, respectively. CONCLUSIONS: Serum insulin determination at gestation week < or = 16 is an easy and reliable method with which to predict GDM in a high-risk group. Despite a negative OGTT, patients with an elevated fasting and/or 120-min serum insulin level at gestation week < or = 16 should be managed in the same way as those with GDM. Considering the very high negative predictive value of the method, patients with a normal fasting and/or 120-min serum insulin level at gestation week < or = 16 should undergo an OGTT only at gestation weeks 32-34.

Adult↗
PubMed2006

Predictive ability of sequential surveys in determining donor loss from increasingly stringent variant Creutzfeldt-Jakob disease deferral policies.

BACKGROUND: Predonation screening questions about travel increase the safety of the blood supply from diseases such as variant Creutzfeldt-Jakob disease (vCJD) and malaria. This study examines the ability of sequential surveys to predict actual travel deferrals and the operational validity of travel questions. STUDY DESIGN AND METHODS: To assess donor travel histories before implementing key deferral policies, two donor surveys were carried out at Canadian Blood Services collection sites in February 1999 (8026 donors) and March 2001 (13,623 donors). In-person interviews were carried out with 1530 donors to assess the operational validity of the short travel question. Time-series analysis was used to determine whether there was a change in deferrals when deferral policies were implemented. Predicted donor loss estimates based on survey results were compared with actual deferrals. RESULTS: Deferrals increased significantly (p < 0.05) when vCJD deferral policies were implemented in October 1999 and September 2001, but not in October 2000. Survey data accurately predicted deferrals 6 months after implementation from the initial policy (2.51% predicted vs. 2.51% actual), but there were fewer deferrals than predicted for the second (2.89% predicted vs. 2.26% actual, p < 0.01) and third deferral policies (3.10% predicted vs. 1.89% actual, p < 0.01). There was 96 percent agreement between donor responses to a short screening question and a detailed travel history. CONCLUSION: The initial survey accurately predicted the actual donor deferral rate, but the deferral rate was less than predicted for subsequent, more stringent donor deferral policies. Donors answered a short travel question suitable for donor screening similarly to a very detailed travel history.

Adolescent↗
PubMed2002

Predictive values, sensitivity and specificity of abdominal fluid variables in determining the need for surgery in horses with an acute abdominal crisis.

OBJECTIVE: To determine the predictive values, sensitivity and specificity of abdominal fluid variables associated with the need for surgery in horses with an acute abdominal crisis. DESIGN: Retrospective study. ANIMALS: Two-hundred and thirty-six horses examined for signs of abdominal pain between January 1993 and June 1999. METHODS: Breed, age and gender of the horse and colour, total protein concentration and total nucleated cell count of an abdominal fluid sample were recorded. Colour of the abdominal fluid was classified as normal if it was yellow and transparent. Turbid fluid or fluid that was serosanguinous or other colours was classified as abnormal. Protein concentration < or = 20 g/L and a total nucleated cell count < or = 5 x 10(9) cells/L were considered normal and values above these were considered abnormal. An abdominal fluid sample was classified as abnormal if one or more of the three variables were considered abnormal. Cases were defined as surgical when lesions identified at surgery or necropsy examination would not have resolved with medical treatment alone. Cases were defined as medical in horses that survived without surgical intervention, and those with a lesion found at surgery or necropsy that would have resolved with medical treatment alone. A third category was identified during the study as those diagnosed with Actinobacillus equuli--induced peritonitis. These horses were included in the study but not in the data analysis. DATA ANALYSIS: The association between the sensitivity, specificity and positive and negative predictive value of colour, total protein, and total nucleated cell count in the abdominal fluid and the need for surgery was calculated. RESULTS: There were 100 females and 136 males of mixed breeds, ranging from 3 days to 26 years of age that had an abdominocentesis performed during the specified period. There were 97 horses with a lesion classified as surgical, 91 horses with a lesion classified as medical and 48 horses with a diagnosis of A equuli-induced peritonitis. Colour of the abdominal fluid was recorded in all horses, protein concentration was recorded in 194 horses and total nucleated cell count was recorded in 179 horses. Abnormal abdominal fluid colour had a sensitivity, specificity, positive and negative predictive value of 92%, 74%, 79% and 89% respectively, associated with the need for surgery. Sensitivity, specificity, positive and negative predictive values for a serosanguinous abdominal fluid sample associated with the need for surgery were 48%, 99%, 98% and 64% respectively. Abnormal abdominal fluid protein concentration had a sensitivity, specificity, positive and negative predictive value of 86%, 75%, 77% and 85% respectively, associated with the need for surgery. The sensitivity, specificity, positive and negative predictive value associated with the need for surgery in horses with an abnormal total nucleated cell count in the abdominal fluid were 59%, 75%, 67% and 67%, respectively. An abdominal fluid sample classified as abnormal had a sensitivity, specificity, positive and negative predictive value of 92%, 74%, 79% and 89% respectively, associated with the need for surgery. CONCLUSION: Results of this study suggest that abdominal fluid sample analysis contributes to the decision to proceed to surgery, but is not a diagnostic panacea. Colour and protein concentration of abdominal fluid were the most useful variables in abdominal fluid for differentiating medical and surgical lesions. Colour and protein had a greater value in horses with a disease likely to respond to medical treatment (negative predictive value) than those with a lesion requiring surgery (positive predictive value) except when the fluid was serosanguinous. Abdominal fluid colour and protein are clinically relevant and easily measured in the field, providing immediate information without the need for sophisticated laboratory techniques.

Abdomen, Acute↗
PubMed1998

Interspecies scaling: predicting volumes, mean residence time and elimination half-life. Some suggestions.

Extrapolation of animal data to assess pharmacokinetic parameters in man is an important tool in drug development. Clearance, volume of distribution and elimination half-life are the three most frequently extrapolated pharmacokinetic parameters. Extensive work has been done to improve the predictive performance of allometric scaling for clearance. In general there is good correlation between body weight and volume, hence volume in man can be predicted with reasonable accuracy from animal data. Besides the volume of distribution in the central compartment (Vc), two other volume terms, the volume of distribution by area (Vbeta) and the volume of distribution at steady state (VdSS), are also extrapolated from animals to man. This report compares the predictive performance of allometric scaling for Vc, Vbeta and VdSS in man from animal data. The relationship between elimination half-life (t(1/2)) and body weight across species results in poor correlation, most probably because of the hybrid nature of this parameter. To predict half-life in man from animal data, an indirect method (CL=VK, where CL=clearance, V is volume and K is elimination rate constant) has been proposed. This report proposes another indirect method which uses the mean residence time (MRT). After establishing that MRT can be predicted across species, it was used to predict half-life using the equation MRT=1.44 x t(1/2). The results of the study indicate that Vc is predicted more accurately than Vbeta and VdSS in man. It should be emphasized that for first-time dosing in man, Vc is a more important pharmacokinetic parameter than Vbeta or VdSS. Furthermore, MRT can be predicted reasonably well for man and can be used for prediction of half-life.

Animals↗
PubMed2026

Genome-based predictions of metabolic preferences and substrate phenotypes in psychrotrophic bacteria from permafrost environments.

Genomes reveal vast functional potential, but harbor genomic noise that obscures prediction of metabolic and environmental preferences. Genomic databases are skewed towards clinically relevant and easily cultivated bacteria, limiting predictions for diverse and underrepresented environmental taxa. Psychrotrophic bacteria, which can survive and grow in cold, nutrient-limited, dry, and saline environments, are especially underrepresented despite their relevance for understanding microbial responses to changing cold environments and potential biotechnological value given growth at low temperatures. Assembling complete genomes of 48 isolates from Alaskan permafrost, seasonally frozen active layer soils, and terrestrial ice, we used Kyoto Encyclopedia of Genes and Genomes (KEGG) ortholog annotations to evaluate the predictability of metabolic resource-use traits observed using phenotypic tests. Genome-predicted values for glycolytic versus gluconeogenic catabolic preference index, or sugar-acid preference (SAP), explained over 50% of the variance in empirically observed SAP. SAP was inversely correlated to genomic GC content, which follows phylum-level trends, indicating that coarse metabolic preference covaries with phylogeny. Regularized elastic net models offered a more granular view, linking KEGG genes to specific substrate utilization and sensitivity phenotypes and yielding moderate but reproducible accuracy (AUC 0.70-0.79) for 11 substrates, demonstrating that specific substrate responses may be predictable from relatively small subsets of KO genes. These results extend recent advances, such as the SAP metric, and highlight associations among genomic GC content, phylum, and broad metabolic strategy. Linking genomic content to phenotype using isolates is a necessary step toward predictive models of microbial function in environmental communities, and this work can be used for hypothesis generation, with applications towards more expansive data sets.IMPORTANCECold region soils and ice host psychrotrophic bacteria with metabolic traits and adaptations that enable persistence in harsh, resource-limited environments. However, these taxa are underrepresented in genomic reference databases dominated by well-studied, mesophilic organisms. This gap limits inference of ecological strategies and our ability to predict how these microbes may influence the large, thaw-vulnerable carbon reservoirs in permafrost. Here, we show that genomic GC content is associated with the sugar-versus-acid catabolic preference (SAP) of isolates across major phyla, suggesting that broad genomic features may provide a coarse signal of metabolic strategy. We demonstrate that a modified SAP metric, using binary (positive/negative) substrate utilization rather than detailed growth rate measurements, is moderately predictive, thus extending its application to slow-growing or difficult-to-culture taxa. Together, these advances broaden the toolkit for linking genome content to resource-use traits (phenotype) in poorly characterized, cold-adapted bacteria and offer a tractable entry point to broad prediction and hypothesis generation.

Genome, Bacterial↗
PubMed2001

Development and validation of a Bayesian index for predicting major adverse cardiac events with percutaneous transluminal coronary angioplasty.

OBJECTIVE: To create a risk model for predicting major adverse complicating events of percutaneous transluminal coronary angioplasty (PTCA), and to test the accuracy of the model on a prospective cohort of patients SETTING: Tertiary cardiac centre METHODS: Available software can predict probabilities of events using Bayes's theorem. To establish the accuracy of these predictive tools, a Bayes table was created to evaluate major adverse complicating events (MACE)-death, emergency coronary artery bypass grafting (CABG), or Q wave infarct occurring during the in-patient episode-on the first 1500 patients in the department PTCA database (development group); the predictive value of this model was then tested with the subsequent 1000 patients (evaluation group). The following probabilities were assessed to determine their association with MACE: age, sex, left ventricular function, American Heart Association lesion morphology classification, cardiogenic shock, previous CABG, diabetes, hypertension, multivessel PTCA. MAIN OUTCOME MEASURES: To establish the discriminatory ability of the predictive index, calibration plots and receiver operating characteristic (ROC) curves were obtained to compare the development and evaluation groups. RESULTS: The ROC curve plotted to determine the discriminatory value of the Bayesian table created from the development group (n = 1500) in predicting MACE in the evaluation group (n = 1000) showed a moderately predictive area under the curve of 0.76 (SEM 0.07). This predictive accuracy was confirmed with separately constructed calibration plots. CONCLUSIONS: Accurate predictions of MACE can be identified in populations undergoing percutaneous intervention. The database used allows operators to obtain consent from patients appropriately from their own experience rather than from other published data. If a national PTCA database existed along similar lines, individual operators and interventional centres could compare themselves with nationally available data.

Age Factors↗
PubMedDate not supplied

Predicting length of stay for psychiatric diagnosis-related groups using neural networks.

OBJECTIVE: To test the effect of diagnosis on training an artificial neural network (ANN) to predict length of stay (LOS) for psychiatric patients involuntarily admitted to a state hospital. DESIGN: A series of ANNs were trained representing schizophrenia, affective disorders, and diagnosis-related group (DRG) 430. In addition to diagnosis, variables used in training included demographics, severity of illness, and others identified to be significant in predicting LOS. RESULTS: Depending on diagnosis, ANN-predictions compared with actual LOS indicated accuracy rates ranging from 35% to 70%. The validity of ANN predictions was determined by comparing LOS estimates with the treatment team's predictions at 72 hours following admission, with the ANN predicting as well as or better than did the treatment team in all cases. CONCLUSIONS: One problem in traditional approaches to predicting LOS is the inability of a derived predictive model to maintain accuracy in other independently derived samples. The ANN reported here was capable of maintaining the same predictive efficiency in an independently derived cross-validation sample. The results of ANNs in a cross-validation sample are discussed and the application of this tool in augmenting clinical decision is presented.

Adult↗
PubMed2003

Massive hemoptysis: prediction of nonbronchial systemic arterial supply with chest CT.

PURPOSE: To evaluate the diagnostic accuracy of chest computed tomography (CT) in the prediction of a nonbronchial systemic arterial supply in patients with massive hemoptysis. MATERIALS AND METHODS: Forty consecutive patients with massive hemoptysis underwent contrast material-enhanced CT. Massive hemoptysis was defined as the expectoration of 300-600 mL of blood per day. Two CT features were considered to be suggestive of a nonbronchial systemic arterial supply: (a) pleural thickness of more than 3 mm adjacent to the parenchymal lesion and (b) enhancing vascular structures within the extrapleural fat layer. Conventional angiography was used as the standard of reference. CT scans were evaluated by two radiologists in consensus. The CT findings were compared with those of conventional angiography. The sensitivity, specificity, predictive values, and accuracy of CT for predicting the presence of a nonbronchial systemic arterial supply were assessed. RESULTS: In the determination of a nonbronchial systemic arterial supply, CT had a sensitivity of 80%, specificity of 84%, positive predictive value of 73%, negative predictive value of 91%, and accuracy of 84%. Sensitivity was highest for predicting the branches of subclavian and axillary arterial supply and was lowest for predicting the internal mammary arterial supply. Specificity and accuracy were highest for predicting the intercostal arterial supply. CONCLUSION: CT demonstrates acceptable sensitivity, specificity, and accuracy in the prediction of a nonbronchial systemic arterial supply in patients with massive hemoptysis.

Adult↗
PubMed2004

Use of cross-sectional imaging in predicting facial nerve sacrifice during surgery for parotid neoplasms.

BACKGROUND: Neoplasms of the parotid gland are difficult management issues because of the wide variation in their biological behavior and the potential for sacrifice of the facial nerve during resection. Because of the significant associated morbidity, prediction of facial nerve sacrifice is critically important for planning surgical procedures and preoperative counseling of patients. We hypothesize that along with the knowledge of the tumor type we would be able to accurately predict the likelihood of facial nerve sacrifice using cross-sectional imaging. METHODS: All patients included in this study were previously untreated patients with parotid neoplasms operated on between January 1997 and July 2002. Only those patients with an available preoperative imaging were included and this resulted in 44 patients for review. Nine patients with preoperative deficits in facial nerve function were excluded from this study since these patients would require facial nerve sacrifice regardless of the radiological prediction. The prediction of facial nerve sacrifice was determined using a prediction of tumor location and an algorithm. The predicted results were compared to the operative record. RESULTS: For all lesions, cross-sectional imaging predicted the need for sacrifice of the facial nerve with a sensitivity of 0.83 (95% CI, 0.36-0.99), specificity of 0.90 (95% CI, 0.72-0.97), PPV of 0.63 (95% CI, 0.26-0.90), and NPV of 0.96 (95% CI, 0.79-0.99). For malignant lesions only, prediction of sacrifice of the facial nerve had a sensitivity of 0.83 (95% CI, 0.36-0.99), specificity of 0.80 (95% CI, 0.51-0.95), PPV of 0.63 (95% CI, 0.26-0.90), and NPV of 0.92 (95% CI, 0.62-0.99). CONCLUSION: Cross-sectional imaging and application of our algorithm is a sensitive method for identifying patients with parotid neoplasms who require facial nerve sacrifice. CT and MRI have a high negative predictive value for facial nerve sacrifice.

Algorithms↗
PubMed1995

Comparison of myocardial contrast echocardiography and low-dose dobutamine stress echocardiography in predicting recovery of left ventricular function after coronary revascularization in chronic ischemic heart disease.

BACKGROUND: Dobutamine stress echocardiography (DSE) and myocardial contrast echocardiography (MCE) can predict recovery of left ventricular function after myocardial infarction. DSE also has been shown to predict left ventricular functional recovery after revascularization in chronic ischemic heart disease, whereas MCE has not been evaluated in such patients. This study was performed to compare DSE and MCE in the prediction of left ventricular functional recovery after revascularization in patients with chronic ischemic heart disease. METHODS AND RESULTS: MCE and DSE were performed in 35 patients with chronic coronary artery disease and significant wall motion abnormalities (mean ejection fraction, 0.36 +/- 0.09). Regional wall motion was scored by use of a 16-segment model wherein 1 = normal or hyperkinetic, 2 = hypokinetic, 3 = akinetic, and 4 = dyskinetic. Each segment was evaluated for contractile reserve by DSE and perfusion by MCE. Revascularization (coronary artery bypass graft [n = 13] and percutaneous transluminal coronary angioplasty [n = 10]) was successful in 23 patients. Follow-up echocardiograms were done to assess wall motion 30 to 60 days later. In 238 segments with resting wall motion abnormalities, perfusion was more likely to present than contractile reserve (97% versus 91%, P < .02). Revascularization resulted in functional recovery in 77 of 95 hypokinetic segments (81%) but only 18 of 57 akinetic segments (32%, P < .0001). DSE and MCE were not significantly different in predicting functional recovery of hypokinetic segments. In akinetic segments, DSE and MCE had similar sensitivities (89% versus 94%, respectively) and negative predictive values (93% and 97%, respectively) in predicting functional recovery. However, DSE had a higher specificity (92% versus 67%, P < .02) and positive predictive value (85% versus 55%, P < .02) than MCE in predicting functional recovery. CONCLUSIONS: Both contractile reserve by DSE and perfusion by MCE are predictive of functional recovery in hypokinetic segments after coronary revascularization in patients with chronic coronary revascularization in patients with chronic coronary artery disease. In akinetic segments, myocardial perfusion by MCE may exist in segments that do not recover contractile function after revascularization. Thus, contractile reserve during low-dose dobutamine infusion is a better predictor of functional recovery after revascularization in akinetic segments than perfusion.

Angioplasty, Balloon, Coronary↗
PubMedDate not supplied

Predicting the cost of illness: a comparison of alternative models applied to stroke.

Predictions of cost over well-defined time horizons are frequently required in the analysis of clinical trials and social experiments, for decision models investigating the cost-effectiveness of interventions, and for macro-level estimates of the resource impact of disease. With rare exceptions, cost predictions used in such applications continue to take the form of deterministic point estimates. However, the growing availability of large administrative and clinical data sets offers new opportunities for a more general approach to disease cost forecasting: the estimation of multivariable cost functions that yield predictions at the individual level, conditional on intervention(s), patient characteristics, and other factors. This raises the fundamental question of how to choose the "best" cost model for a given application. The central purpose of this paper is to demonstrate how to evaluate competing models on the basis of predictive validity. This concept is operationalized according to three alternative criteria: 1) root mean square error (RMSE), for evaluating predicted mean cost; 2) mean absolute error (MAE), for evaluating predicted median cost; and 3) a logarithmic scoring rule (log score), an information-theoretic index for evaluating the entire predictive distribution of cost. To illustrate these concepts, the authors conducted a split-sample analysis of data from a national sample of Medicare-covered patients hospitalized for ischemic stroke in 1991 and followed to the end of 1993. Using test and training samples of about 500,000 observations each, they investigated five models: single-equation linear models, with and without log transform of cost; two-part (mixture) models, with and without log transform, to directly address the problem of zero-cost observations; and a Cox proportional-hazards model stratified by time interval. For deriving the predictive distribution of cost, the log transformed two-part and proportional-hazards models are superior. For deriving the predicted mean or median cost, these two models and the commonly used log-transformed linear model all perform about the same. The untransformed models are dominated in every instance. The approaches to model selection illustrated here can be applied across a wide range of settings.

Cerebrovascular Disorders↗
PubMedDate not supplied

Magnetic resonance imaging as a tool to predict meniscal reparability.

One hundred six patients who underwent high field strength magnetic resonance imaging and subsequent arthroscopy of the knee were evaluated to determine the accuracy of magnetic resonance imaging in predicting meniscal tear reparability. Each scan was independently read by three examiners with varying degrees of expertise: a musculoskeletal radiologist, a senior orthopaedic surgeon, and a general radiologist. Each suspected tear was characterized by its morphologic type, maximum length, and minimum distance from the meniscosynovial junction. A prediction was then made of whether the tear was reparable. There were 115 meniscal tears noted in the 106 patients studied. The examiners' ability to correctly estimate tear type was only fair, with correct estimates made only 14% to 67% of the time. The overall correlation of the three examiners to correctly predict the method of treatment was fair. The average accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of magnetic resonance imaging in predicting meniscal reparability were 74%, 29%, 89%, 50%, and 80%, respectively; for predicting meniscectomy, these values were 69%, 68%, 75%, 90%, and 43%, respectively. There were no significant differences between the three examiners in the accuracy of their treatment predictions. The results of this study suggest that magnetic resonance imaging is only moderately reliable for the prediction of meniscus reparability. In addition, the training of the reader does not appear to significantly influence the results.

Adolescent↗
PubMed2004

GASP: Gapped Ancestral Sequence Prediction for proteins.

BACKGROUND: The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments. RESULTS: Here we present a new algorithm, GASP (Gapped Ancestral Sequence Prediction), for predicting ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments. Alignments may be of any size and contain gaps. GASP first assigns the positions of gaps in the phylogeny before using a likelihood-based approach centred on amino acid substitution matrices to assign ancestral amino acids. Important outgroup information is used by first working down from the tips of the tree to the root, using descendant data only to assign probabilities, and then working back up from the root to the tips using descendant and outgroup data to make predictions. GASP was tested on a number of simulated datasets based on real phylogenies. Prediction accuracy for ungapped data was similar to three alternative algorithms tested, with GASP performing better in some cases and worse in others. Adding simple insertions and deletions to the simulated data did not have a detrimental effect on GASP accuracy. CONCLUSIONS: GASP (Gapped Ancestral Sequence Prediction) will predict ancestral sequences from multiple protein alignments of any size. Although not as accurate in all cases as some of the more sophisticated maximum likelihood approaches, it can process a wide range of input phylogenies and will predict ancestral sequences for gapped and ungapped residues alike.

Amino Acid Sequence↗
PubMed2004

Predicting co-complexed protein pairs using genomic and proteomic data integration.

BACKGROUND: Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same protein complex. High-throughput methods such as yeast two-hybrid (Y2H) and affinity purification coupled with mass spectrometry (APMS) have been used to detect interacting proteins on a genomic scale. However, both Y2H and APMS methods have substantial false-positive rates. Aside from high-throughput interaction screens, other gene- or protein-pair characteristics may also be informative of physical interaction. Therefore it is desirable to integrate multiple datasets and utilize their different predictive value for more accurate prediction of co-complexed relationship. RESULTS: Using a supervised machine learning approach--probabilistic decision tree, we integrated high-throughput protein interaction datasets and other gene- and protein-pair characteristics to predict co-complexed pairs (CCP) of proteins. Our predictions proved more sensitive and specific than predictions based on Y2H or APMS methods alone or in combination. Among the top predictions not annotated as CCPs in our reference set (obtained from the MIPS complex catalogue), a significant fraction was found to physically interact according to a separate database (YPD, Yeast Proteome Database), and the remaining predictions may potentially represent unknown CCPs. CONCLUSIONS: We demonstrated that the probabilistic decision tree approach can be successfully used to predict co-complexed protein (CCP) pairs from other characteristics. Our top-scoring CCP predictions provide testable hypotheses for experimental validation.

Computational Biology↗
PubMed2005

Better prediction of protein contact number using a support vector regression analysis of amino acid sequence.

BACKGROUND: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of Cbeta atoms in other residues within a sphere around the Cbeta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. RESULTS: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either "contacted" or "non-contacted", the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. CONCLUSION: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary protein sequence and higher order consecutive protein structural and functional properties.

Algorithms↗
PubMed2006

The potential of restaging in the prediction of pathologic response after preoperative chemoradiotherapy for rectal cancer.

BACKGROUND: We performed this study to prospectively evaluate the postchemoradiotherapy performance of transrectal ultrasonography (TRUS), pelvic computed tomography (CT) scan and magnetic resonance imaging (MRI), and endoscopic biopsies for predicting the pathologic complete response of rectal cancer patients. METHODS: Four weeks after completion of preoperative chemoradiotherapy, 46 consecutive patients with mid to low rectal cancer were prospectively evaluated by proctoscopy, TRUS, and pelvic CT scan and MRI. On the basis of T and N status, patients were classified as T0 or T1-4 and N-negative or N-positive. For each staging modality used, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. Findings were compared with the pathologic tumor-node-metastasis stage. RESULTS: On histopathologic analysis, 12 patients had pT0 and 34 had pT1-4 lesions; out of 45 assessable patients, 9 were N-positive. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in predicting T status (T0 vs. T >or=1) were 77%, 33%, 74%, 36%, and 64%, respectively, for TRUS; 100%, 0%, 74%, not assessable, and 74% for CT; and 100%, 0%, 77%, not assessable, and 77% for MRI. The corresponding figures in predicting N status (N-negative vs. N-positive) were, respectively, 37%, 67%, 21%, 81%, and 61% for TRUS; 78%, 58%, 32%, 91%, and 62% for CT; and 33%, 74%, 25%, 81%, and 65% for MRI. CONCLUSIONS: Current rectal cancer staging modalities after chemoradiotherapy allow good prediction of node-negative cases, although none of them is able to predict the pathologic complete response on the rectal wall.

Adenocarcinoma↗