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PubMed2006

The diagnosis of periodontal disease in private practice.

BACKGROUND: Periodontal disease is an inflammatory reaction to the bacteria in dental plaque. The present study compared the prevalence of periodontal disease in patients using as a diagnostic either probing depth measurements, an inflammatory marker such as numbers of white blood cells in plaque samples, or microbiological markers such as the microscopic count and the benzoyl-DL-arginine naphthylamide (BANA) test. METHODS: Teeth with the most inflammation and/or deepest pockets in each quadrant were probed and subgingival plaque was sampled from 1,043 consecutive new patients enrolled in a private practice. Multivariate "diagnostic" models were developed based upon the probing depth (general linear models), percentage of white blood cell-positive and percentage of BANA-positive plaques (logistic regression models) to determine the prevalence of patients with periodontal disease. RESULTS: Plaque samples were removed from 3,694 sites. Fifty-two percent of sampled pockets were >4 mm; 49% of sites were inflamed, using the presence of white blood cells, and 28% were infected using the BANA test. Diagnostic models were highly significant at P<0.0001. The white blood cell model was the most parsimonious as demonstrated by the lowest Akaike information criteria statistic and had the highest receiver operator characteristic (ROC) curve relative to the probing depth and BANA models. CONCLUSIONS: Periodontal disease can be diagnosed chairside by the presence of white blood cells in plaque samples, a finding that reflects the inflammatory nature of the disease process. This approach would reduce the misclassification of subjects as having periodontal disease (130 patients in the present study who had pockets) but minimal evidence of an inflammatory response.

Benzoylarginine-2-Naphthylamide↗

PubMed1997

The predictive and explanatory power of inductive decision trees: a comparison with artificial neural network learning as applied to the noninvasive diagnosis of coronary artery disease.

BACKGROUND: This paper compares two machine learning systems, an inductive decision tree (IDT) and a back-propagation neural network (ANN), in the noninvasive assessment of coronary artery disease given a set of diagnostic input attributes. A collection of 490 patient cases were accumulated from the reference of diagnostic stress myocardial scintigraphy performed in a nuclear medicine department. All cases had correlating angiography, the results of which were used to derive the target diagnoses. Input attributes included 4 baseline clinical characteristics, 4 nonimaging stress components, and 3 scintigraphic findings. METHODS: We chose 4 possible angiographic criteria for coronary artery disease and assessed the ability of each learning system to develop a diagnostic model. The 2 machine learning systems were compared on the basis of predictive performance and explanatory power. RESULTS: Cross-validation experiments showed the 2 machine learning systems to have equivalent predictive power at the same level as the clinical scan reading. For the 70% stenosis criterion, the IDT had a sensitivity of 94 +/- 3% (mean +/- 95% confidence interval) and a specificity of 59 +/- 8%, and the ANN had a sensitivity of 97 +/- 2% and a specificity of 51 +/- 13%. However the IDT system exhibited excellent explanatory power; producing simple representations of the diagnostic models which agree with previous research. CONCLUSION: In comparison with the more widely used ANNs, the IDT learning system may bring advantages to certain problems in diagnostic classification.

Coronary Angiography↗

PubMed2006

[Application of serum protein fingerprint model and support vector machine in diagnosis of thyroid cancer].

OBJECTIVE: To detect new biomarkers and to establish a serum protein fingerprint model for early detection and diagnosis of thyroid cancer. METHODS: The serum samples of 40 thyroid cancer patients, 9 thyroid adenoma patient, and 32 healthy individuals were randomly divided into 2 sets: training set (n = 66, including 32 thyroid cancer patients, 9 thyroid adenoma patients, and 25 healthy individuals) and test set (n = 15). The serum protein were bound to WCX2 chip and tested by surface enhanced laser desorption/ionization time of flight-mass spectrometry (SELDI-TOF-MS). The data of spectra were analyzed by support vector machine (SVM) to establish a diagnostic model. RESULTS: The detective model combined with 3 biomarkers could differentiate the serum of thyroid cancer from that of healthy individual with a specificity of 86% and a sensitivity of 100%. The diagnostic model combined with 3 biomarkers could differentiate thyroid cancer from thyroid adenoma with a specificity of 88.9% and a sensitivity of 96.9%. The positive predictive value to differentiate papillary thyroid carcinoma from the thyroid cancer of other types was 97%, and the positive predictive value of thyroid carcinoma of other pathological types was 71%. CONCLUSION: The combination of SELDI with bioinformatics tools is a novel, effective, and highly specific and sensitive method for thyroid cancer detection and diagnosis.

Biomarkers, Tumor↗

PubMed2004

Biochemistry in diagnosis and management of abnormal early pregnancy.

PURPOSE OF REVIEW: This review examines the biochemical parameters of early pregnancy failure and the role that biochemical markers have to play in the selection of patients for expectant management. RECENT FINDINGS: Earlier studies have concentrated on the role that human chorionic gonadotrophin and progesterone have to play in early pregnancy failure. Recent studies, however, have explored newer markers such as the inhibins and insulin growth factor binding proteins. Diagnostic models have now been created incorporating demographic, morphological, and biochemical parameters for the prediction of successful expectant management of early pregnancy failure. SUMMARY: Examining the role of newer biochemical markers in early pregnancy failure has led to an improved understanding of the mechanisms behind it. Incorporation of these newer markers into diagnostic models has aided selection of patients for whom expectant management is appropriate.

17-alpha-Hydroxyprogesterone↗

PubMed1998

Regression modelling of diagnostic likelihood ratios for the evaluation of medical diagnostic tests.

The use of diagnostic likelihood ratios has been advocated in the epidemiologic literature for the past decade. Diagnostic likelihood ratios provide valuable information about the predictive properties of a diagnostic test while having the attractive feature of being independent of the prevalence of disease in the study population. We propose a new regression method that allows for direct assessment of covariate effects on likelihood ratios for binary diagnostic tests. This may be particularly useful in assessing how factors that are under the control of the clinician can be altered to maximize the predictive ability of the test. Similarly, patient characteristics that influence the ability of the test to discriminate between diseased and nondiseased subjects may be identified using the regression model. The regression method is flexible in that it can accommodate clustered data arising from a variety of study designs. We illustrate the method with data from an audiology study.

Audiology↗

PubMed1994

The clinical evaluation for diagnosing obstructive airways disease in high-risk patients.

OBJECTIVE: We measured the ability of the medical history, physical examination, and peak flowmeter in diagnosing any degree of obstructive airways disease (OAD). DESIGN: Prospective comparison of historical and physical findings with independently measured spirometry. SETTING: University outpatient clinic. PATIENTS: Ninety-two adult consecutive outpatient volunteers with a self-reported history of smoking, asthma, chronic bronchitis, or emphysema. MEASUREMENTS: All subjects completed a pulmonary history questionnaire and received peak flow (PF) and spirometric testing. The subjects were independently examined for 12 pulmonary physical signs by four internists blinded to all other results. Multivariable analysis was used to create a diagnostic model to predict OAD as diagnosed by spirometry (FEV1 < 80 percent of predicted not secondary to restrictive disease, or FEV1/FVC less than 0.7). RESULTS: The best model diagnosed OAD when any of three variables were present--a history of smoking more than 30 pack-years, diminished breath sounds, or peak flow less than 350 L/min. This model had a sensitivity of 98 percent and specificity of 46 percent. In addition, the model detected all subjects with probable restrictive lung disease. Thirty-one percent of subjects had none of these variables and were at very low (3 percent) risk of OAD. Fifty percent of subjects with one or more abnormal variables had OAD. CONCLUSIONS: The history, physical examination, and peak flowmeter can be used to screen high-risk patients for OAD. Using this diagnostic model, 31 percent of subjects could be classified at very low risk of OAD while half of those referred for spirometry would have abnormal results.

Airway Obstruction↗

PubMed2003

[The value of autofluorescence spectrum analysis of gastric juice in diagnosing gastric carcinoma: a preliminary result].

OBJECTIVE: To reveal the difference of autofluorescence spectrums of gastric juice derived from malignancy and benignancy for screening and diagnosis of gastric carcinoma. METHOD: Gastric juice from 202 patients with different gastric diseases were collected, then detected their autofluorescence spectrums (the excitation wavelength is 288 nm, whereas the range of emission wavelength is 300 - 800 nm) after diluted by 1:10. The diagnostic model for gastric cancer was made by Classification and Regression Trees V2.0 software. RESULTS: There were three peaks (the emission wavelength were 320 - 360 nm, 576 nm and 670 - 690 nm respectively) in the autofluorescence spectrums of all patients, though the intensity of the first peak (with the emission wavelength of 320 - 360 nm) were enhanced distinctively in malignance than those in benignancy. The diagnostic model's sensitivity and specificity of prior probability were 91.4% and 83.2% respectively, whereas the sensitivity and specificity of posterior probability were 85.7% and 82.6%. CONCLUSION: Detection of autofluorescence spectrum of gastric juice has great prospect in the diagnosis and screening gastric carcinoma.

Adult↗

PubMed2006

[Detection and clinical significance of serum proteomic patterns of breast cancers by surface enhanced laser desorption/ionization time of flight mass spectrometry].

OBJECTIVE: To detect the serum proteomic patterns in breast cancer patients by surface enhanced laser desorption/ionization time of flight (SELDI-TOF-MS) protein chip array techniques, to screen biomarker candidates and build diagnostic models in order to evaluate their clinical significance. METHODS: SELDI-TOF-MS technique and weak cation exchanger (WCX2) protein chip were used to detect the serum proteomic patterns of 38 patients with breast cancer, 33 patients with benign breast diseases and 43 normal control subjects. Biomarker Wizard 3.01 and Biomarker Pattern Software 5.01 were used in combination to analyze the data and to develop diagnostic models. RESULTS: Four protein peaks pattern (M2077_07, M1827_38, M2650_51 and M2060_62 mass/charge ratio [m/z]) was observed in the model I, and it could be used to distinguish breast cancer from non cancerous diseases. Its sensitivity and specificity were 73.7% (28/38) and 73.7% (56/76), respectively. The model II was formed by 5 protein peaks (M2251_62, M3405_56, M3428_16, M4666_98, M16239_8 m/z). When it was used in differential diagnosis between stage I breast cancer and benign breast diseases, the sensitivity and specificity were 84.8% (28/33) and 55.6% (5/9), respectively. Another 5 peaks (M1701_48, M3116_17, M1676_88, M5890_33, M2921_02 m/z) could build the model III to distinguish stage I and stage II approximately IV breast cancers. Its sensitivity and specificity were 88.9% (8/9) and 86.2% (25/29), respectively. CONCLUSION: Our findings suggested that application of SELDI-TOF-MS can be of great potential for early breast cancer screening, diagnosis and preoperative staging, and deserves further studies.

Adult↗

PubMedDate not supplied

Use of stereolithographic models as diagnostic and restorative aids for predictable immediate loading of implants.

Implant dentistry has evolved into one of the most predictable treatment alternatives in all of medical science. Advances in the surgical and prosthetic components, implant designs and surface technologies, and imaging techniques have allowed for significant modifications to occur with respect to one- and two-stage surgical protocols, accelerating treatment times to the benefit of patient and clinician. This article presents a technique to improve surgical and restorative accuracy, allowing for predictable placement and immediate loading of implants through use of CT imaging, stereolithographic models, and CT-derived surgical templates.

Computer-Aided Design↗

PubMed1984

Statistical modelling and diagnostic aids.

This paper considers the problems involved in constructing operational aids for diagnosis. A collaborative approach is proposed which involves utilisation of the expertise of clinician and statistician, working jointly on the analysis of hard data for a particular diagnostic application. The application of this approach to a problem involving cerebral disease diagnosis based on CT scan data is described.

Bayes Theorem↗

PubMed1994

ROC curve regression analysis: the use of ordinal regression models for diagnostic test assessment.

Diagnostic tests commonly are characterized by their true positive (sensitivity) and true negative (specificity) classification rates, which rely on a single decision threshold to classify a test result as positive. A more complete description of test accuracy is given by the receiver operating characteristic (ROC) curve, a graph of the false positive and true positive rates obtained as the decision threshold is varied. A generalized regression methodology, which uses a class of ordinal regression models to estimate smoothed ROC curves has been described. Data from a multi-institutional study comparing the accuracy of magnetic resonance (MR) imaging with computed tomography (CT) in detecting liver metastases, which are ideally suited for ROC regression analysis, are described. The general regression model is introduced and an estimate for the area under the ROC curve and its standard error using parameters of the ordinal regression model is given. An analysis of the liver data that highlights the utility of the methodology in parsimoniously adjusting comparisons for covariates is presented.

Algorithms↗

PubMedDate not supplied

Neuromusculoskeletal conditions of the upper extremity: are they due to repetitive occupational trauma?

The significance of neuromusculoskeletal conditions in the workplace is the subject of much discussion among occupational medicine professionals. There are differing philosophies as to what constitutes appropriate diagnostic criteria for identification of these conditions. The traditional diagnostic model requires the presence of objective pathology. An emerging symptom-based model accepts that symptoms by themselves can constitute a diagnostic entity. The extent to which these conditions are considered to be associated with occupational activity depends greatly upon which of the two models is employed. This chapter presents an overview of each diagnostic model and a discussion of the impact each has on the prevalence of identified conditions and the manner in which the various diagnostic requirements can affect treatment, prevention, and disability rating protocols.

Arm↗

PubMed2005

Prediction of findings at defecography in patients with genital prolapse.

OBJECTIVE: Defecography may be useful in pre-operative assessment of patients with genital prolapse. Defecography is an invasive and embarrassing procedure for patients and little effort has been made to optimalise selection criteria for defecography. This study investigated whether discrimination of high and low probability of abnormal defecography is possible based on the quantified findings from patient history, pelvic examination and a validated questionnaire. DESIGN: Prospective observational study. SETTING: Three teaching hospitals in The Netherlands. POPULATION: Eighty-two patients undergoing surgical correction of uterine prolapse Stages 2-4. METHODS: A history and pelvic examination were obtained from all patients. A validated questionnaire was used to assess the presence of defecation and micturition symptoms. Using multivariate logistic regression analyses with receiver operating characteristic curves, a diagnostic model to predict the presence of an abnormal defecography was systematically constructed and validated. MAIN OUTCOME MEASURE: Presence of abnormal finding at defecography. RESULTS: The most important predictors for abnormal defecography were prolapse of the posterior vaginal wall, history of abdominal or pelvic surgery and the presence of constipation. With these variables, a prediction rule could be constructed which predicted the prevalence of an abnormal defecography (area under curve = 0.73; 95% CI 0.61-0.83). CONCLUSIONS: This study shows that a diagnostic model based on findings obtained from a non-invasive workup can accurately predict the presence of an abnormal defecography. Such a model provides the possibility to tailor the request for defecography to the individual patient.

Defecography↗

PubMedDate not supplied

[Significance of comparing the results of caloric and vestibulometric rotation tests].

The use of modified, less laborious, easier endured vestibulometric tests made it possible to facilitate diagnosing Menière's disease and neurinomas of the vestibular nerve. Comparison of nystagmometric findings recorded in the same patient during caloric and rotation tests using the diagnostic model of a bithermal test permitted some assumptions to be made in relation to the mechanisms for nystagmogenesis associated with pathologic states in ear labyrinth and vestibular portion craniocerebral (VIII) nerve. It is found that in the majority of Meniere's disease cases (61%) there is a decrease in an intensity of caloric nystagmus induced by Lasix dehydration effect. This phenomenon can be explained by a reduced difference in energy levels of two complexes of vestibular nuclei and, therefore, by an attenuated afferents to peripheral compartment of vestibular system. In neurinoma of aural nerve, the phenomenon of vestibular recruitment (20%) was noted. The diagnostic model of a bithermal test makes it possible to explain an effect of smoothing out the nystagmic responses induced by an intensive stimulus when used a sinusoidal stepwise test. The observed vestibular recruitment results from the severe disorder of one of the afferent inputs due to destruction of induced by tumor pressure.

Adult↗

PubMed1994

Synthesis, characterization, and use of immobilized polyacrolein microspheres in diagnostics: a model determination of alpha 1-antitrypsin in human serum.

Polyacrolein microspheres covalently coupled onto solid surfaces, e.g., glass, silicon crystals, and polystyrene, have been prepared and characterized. These surfaces were synthesized by derivatization of the substrate surfaces with SiCl3(CH2)3CN or Si(OEt)3-(CH2)4NH2. The terminal nitrile groups were then reduced to primary amine groups. Polyacrolein microspheres of various diameters (0.08 and 0.4 microns) were then covalently bound in a monolayer structure to the modified surfaces. This binding of the microspheres to the derivatized surfaces is achieved via polyvalent Schiff-base bonds formed by the interaction between aldehyde groups of the microspheres and omega-primary amine groups of the modified surfaces. Residual amine groups were blocked with acetic acid N-hydroxysuccinimide ester. The residual aldehyde groups of the immobilized microspheres can then be used for covalent binding of amino ligands, e.g., proteins, in a single step and at physiological pH (or any other desired pH). The potential use of the immobilized polyacrolein microsphere surfaces for diagnostics has been demonstrated by determination of alpha 1-antitrypsin in human serum with trypsin bound to the immobilized microspheres. The comparison between this new method for the determination of alpha 1-antitrypsin and the routine methods is discussed.

Acrolein↗

PubMed2004

Presurgical diagnosis of posterior deep infiltrating endometriosis based on a standardized questionnaire.

BACKGROUND: To derive a diagnostic model based on symptoms and history as assessed by a standardized questionnaire to predict posterior deep infiltrating endometriosis (DIE) among women with chronic pelvic pain symptoms. METHODS: 134 women scheduled for laparoscopy for chronic pelvic pain symptoms completed a standardized self-administered questionnaire, specifically designed for the study. We compared the symptoms of the women with posterior DIE diagnosed at laparoscopy with those of the women with other disorders, and used multiple logistic regression analysis to select the best combination of symptoms for predicting posterior DIE. Cross-validation was performed with the jackknife method. RESULTS: 51 women (38.1%) were diagnosed with posterior DIE and 83 with other disorders (61.9%). The following variables were independent predictors for posterior DIE: painful defecation during menses, severe dyspareunia (visual analogic scale > or =8), pain other than noncyclic, and previous surgery for endometriosis. The cross-validation procedure leads to a simplified diagnostic model that uses two independent predictors: painful defecation during menses and severe dyspareunia. The sensitivity of this model for diagnosing posterior DIE was 74.5%, its specificity was 68.7%, its positive likelihood ratio was 2.4, and its negative likelihood ratio was 0.4. It correctly classified 70.9% of our sample into a high-risk (with either severe dyspareunia or painful defecation during menses) and a low-risk (neither symptom) group. CONCLUSIONS: Standardized evaluation of painful symptoms is useful for screening women so that they may have adequate exploration and counselling before laparoscopic surgery for pelvic pain symptoms.

Adult↗

PubMed2001

Assessing landscape health: a case study from northeastern Italy.

This article investigates the concept of biophysical landscape health for what are termed "highly governed landscapes." It proposes a definition of landscape health along with a preliminary diagnostic model and methods. The idea of landscape health derives from the emerging integrative science of ecosystem health, which seeks to diagnose ecosystem condition as humans diagnose human health. Highly governed landscapes, such as the reclaimed areas of coastal northeastern Italy, are landscapes that have been subject to even greater degrees of human manipulation than normal cultural landscapes. These highly altered landscapes are not easily served by existing environmental paradigms and concepts of health are seen to have numerous advantages. This paper condenses a broader investigation of landscape health into three main sections. A brief review of the literature is followed by a case study, which details two different phases of landscape transformation in the Lower Piave area of northeastern Italy. A definition and general parameters of biophysical landscape health are then presented after this background stage. Some key parameters of biophysical health include absence of distress and risk factors, sustainability, biodiversity, resilience, and balance. For certain parameters, a preliminary landscape health diagnostic framework is presented that includes potential diagnostic methods and thresholds based on findings from this case study. At the paper's conclusion, a summary diagnostic model is presented, which suggests a process needed to implement landscape health assessment into practice.

Animals↗

PubMed1979

Patterns and issues in multiaxial psychiatric diagnosis.

The multiaxial diagnostic model, consisting in the systematic formulation of a patient's condition according to separate clinical variables of aspects, is receiving increasing attention in several parts of the world. This innovative model promises to improve diagnostic reliability and validity and involves many methodological challenges. This paper reviews patterns and issues in the conceptualization of axial content, number and organization of axes, dimensional versus categorical scaling, and evaluation and further development of multiaxial systems.

Humans↗