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PubMed1999

Identifying depression as a symptom of sleep apnea.

Sleep apnea syndrome is a common, life-threatening disorder, causing significant physical, emotional, and social problems. The symptoms of obstructive sleep apnea syndrome can lead to an erroneous diagnosis of dysthymia. For patients with sleep apnea syndrome, standard antidepressant treatments may exacerbate the condition. DSM-IV's diagnostic model needs only a small change to allow consideration of sleep apnea syndrome as a cause of a mood disorder.

Depression↗

PubMed2006

Reading impairment and visual processing deficits in schizophrenia.

Individuals with schizophrenia show magnocellular visual pathway abnormalities similar to those described in dyslexia, predicting that reading disturbance should be a common concomitant of schizophrenia. To date, however, reading deficits have not been well established, and, in fact, reading is often thought to be normal in schizophrenia based upon results of tests such as the WRAT, which evaluate single word reading. This study evaluated "real world" reading ability in schizophrenia, relative to functioning of the magnocellular visual pathway. Standardized psychoeducational reading tests and contrast sensitivity measures were administered to 19 patients and 10 controls. Analyses of between group differences were further refined by classification of participants into reading vs. non-reading impaired groups using a priori and derived theoretical models. Patients with schizophrenia, as a group, showed highly significant impairments in reading (p<0.04-p<0.001), with particular deficits on tests of rate, comprehension and phonological awareness. Between 21% and 63% of patients met criteria for dyslexia depending upon diagnostic model vs. 0-20% of the controls. The degree of deficit correlated significantly with independent measures of magnocellular dysfunction. Reading impairment in schizophrenia reaches the level of dyslexia and is associated with compromised magnocellular processing as hypothesized. Findings related to symptoms, functioning and recommendations for reading ability assessment are discussed.

Adolescent↗

PubMed2026

Identification of a novel human gut microbes and microbial metabolites related genes signature for prognostic implication in head and neck squamous carcinomas.

BACKGROUND: The gut microbiota acts as a critical driver influencing the pathogenesis, therapeutic response, and clinical outcomes across various cancer types. This study aimed to investigate the prognostic value of human gut microbes and microbial metabolites related genes (HGMMMRGs) in head and neck squamous cell carcinoma (HNSCC). METHODS: We constructed a prognostic risk model comprising 19 core HGMMMRGs using LASSO penalized regression and a multivariate Cox proportional hazards model. The predictive performance of the model was evaluated through Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, nomograms, and concordance index. In addition, functional enrichment analysis was performed on the differentially expressed risk genes. Furthermore, the relationship between the immune microenvironment of HNSCC and the risk diagnostic model was examined. Western blot analysis was used to assess the expression levels of IL10 in both HNSCC tissues and adjacent normal tissues. Finally, the correlation between IL10 and the gut microbiota was explored. RESULTS: This study developed a risk score model integrating 19 HGMMMRG genes, which can serve as a tool to guide prognosis and immune microenvironment assessment in HNSCC patients. Survival analysis showed that patients in the high-risk group had significantly worse outcomes (P < 0.05). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed significant enrichment of differentially expressed genes (DRLs) and immune-related pathways. Western blot analysis further confirmed that IL10 was highly expressed in HNSCC, and the abundance of Faecalibacterium prausnitzii and Enterococcus durans colonies was correlated with IL10 expression. CONCLUSION: We developed a prognostic model for HGMMMRGs that can be effectively used to predict OS in patients with HNSCC. Second, Faecalibacterium prausnitzii and Enterococcus durans can influence the prognosis of patients with HNSCC by mediating the expression IL10 and thereby affecting the prognosis of HNSCC patients. Thus, human gut microbes and microbial metabolite-related genes may be another promising strategy for the treatment of patients with HNSCC.

HNSCC↗

PubMed1973

Use of computer-assisted model in diagnosis of drug hypersensitivity jaundice.

Of 374 patients with jaundice seen in the liver unit over a four-year period 21 were finally thought to be hypersensitive to one of seven different drugs. The clinical, laboratory, and histological features were often difficult to distinguish from those of viral hepatitis, tumour of the extrahepatic biliary tree, or primary biliary cirrhosis. A computer-assisted diagnostic model made use of minor differences, and made a correct diagnosis in all patients. Even when information about drug ingestion was left out it was still correct in 81% of patients. Sixty-four other patients gave a history of ingestion of potentially hepatotoxic drugs of whom 62 were correctly diagnosed by the computer. In the complete series of 374 patients only two were incorrectly computed to have drug jaundice when there was no history of drug ingestion.Two additional patients became jaundiced after exposure to drugs, but were found to have primary biliary cirrhosis.

Biliary Tract↗

PubMed2007

Prevalence of ECG abnormalities in an international survey of patients with suspected or confirmed heart failure at death or discharge.

BACKGROUND: Most patients suspected of having heart failure (HF) will get a 12-lead electrocardiogram (ECG) but its utility for excluding HF or assisting in its management has rarely been investigated. METHODS: The EuroHeart Failure survey identified 11,327 patients hospitalised with a suspected diagnosis of HF from 115 hospitals in 24 countries. ECGs were obtained from 9315 patients, of whom 5934 had cardiac imaging tests. The utility of the ECG was assessed for excluding or diagnosing major structural heart disease (MSHD) or major left ventricular systolic dysfunction (MLVSD) and for therapeutic decision making. FINDINGS: MSHD was present in 70% and MLVSD in 54% of patients overall but in only 21% and 5%, respectively, if the ECG was entirely normal. However, <2% of patients had a normal ECG. No single ECG characteristic identified a probability <25% of MSHD or <20% of MLVSD. Patients with QRS width >or=120 ms or anterior pathological Q-waves had a probability >80% of MSHD and >70% of MLVSD. Diagnostic models suggested that electrocardiographic criteria alone were not accurate for the diagnosis or exclusion of important heart disease in this population. However, 2468 patients (42%) had an electrocardiographic finding that should be used to guide the choice of therapy. CONCLUSIONS: A normal ECG is rare in patients with suspected HF but has limited diagnostic value in this setting. The ECG has an important role in guiding therapy.

Adolescent↗

PubMedDate not supplied

[Bipolar disorder and psychoanalytical concepts of depression and mania].

The categorical diagnostic model of bipolar disorders (DSM IV) has brought about increasing questioning, since its use gains troubles related not only to clinical experience, but to epidemiological studies as well. Regarding this, other models have emerged, such as the bipolar spectrum by Akiskal that covers the classic bipolar disorder on one side to unipolar disorder on the other, including soft bipolar disorders as well. The authors start from this notion of bipolar spectrum to set out the relationship between bipolar disease and psychoanalytical concepts of depression and mania. They develop Freud's basic theories and those of the British School that constitute a strong and coherent theoretical structure. Psychoanalysis proposes a unitary psychopathological model that manifests itself as depression or maniac reaction as secondary defense, to account for both the clinical expression and the psychodynamic comprehension of mood disorders.

Bipolar Disorder↗

PubMedDate not supplied

Comprehensive diagnosis: a conceptual basis for future diagnostic systems.

A discussion of the objectives of diagnosis, participants and architecture leads to the consideration of diagnostic schemas of increasing complexity. Examined first is the conventional case of single-label diagnosis. The case of multiple illness formulation is considered concerning the plurality of mental disorders as well as of general medical disorders. The formulation of a whole clinical condition where contextualized pathology and problems are described is then followed by the consideration of positive aspects of health as well as quality of life. Finally, a comprehensive diagnostic model is reviewed. It integrates a standardized multiaxial formulation (illness, disabilities, contextual factors and quality of life) and an idiographic personalized formulation (culturally informed and contextualized clinical problems, patient's assets pertinent to care, and expectations of health restoration and promotion as jointly understood by clinician, patient and family). Such integrative diagnostic schemas may offer a richer informational basis for clinical description and care as well as a more effective focus for the surveillance of population health.

Comorbidity↗

PubMed1999

Risk-adjusted capitation based on the Diagnostic Cost Group Model: an empirical evaluation with health survey information.

OBJECTIVE: To evaluate the predictive accuracy of the Diagnostic Cost Group (DCG) model using health survey information. DATA SOURCES/STUDY SETTING: Longitudinal data collected for a sample of members of a Dutch sickness fund. In the Netherlands the sickness funds provide compulsory health insurance coverage for the 60 percent of the population in the lowest income brackets. STUDY DESIGN: A demographic model and DCG capitation models are estimated by means of ordinary least squares, with an individual's annual healthcare expenditures in 1994 as the dependent variable. For subgroups based on health survey information, costs predicted by the models are compared with actual costs. Using stepwise regression procedures a subset of relevant survey variables that could improve the predictive accuracy of the three-year DCG model was identified. Capitation models were extended with these variables. DATA COLLECTION/EXTRACTION METHODS: For the empirical analysis, panel data of sickness fund members were used that contained demographic information, annual healthcare expenditures, and diagnostic information from hospitalizations for each member. In 1993, a mailed health survey was conducted among a random sample of 15,000 persons in the panel data set, with a 70 percent response rate. PRINCIPAL FINDINGS: The predictive accuracy of the demographic model improves when it is extended with diagnostic information from prior hospitalizations (DCGs). A subset of survey variables further improves the predictive accuracy of the DCG capitation models. The predictable profits and losses based on survey information for the DCG models are smaller than for the demographic model. Most persons with predictable losses based on health survey information were not hospitalized in the preceding year. CONCLUSIONS: The use of diagnostic information from prior hospitalizations is a promising option for improving the demographic capitation payment formula. This study suggests that diagnostic information from outpatient utilization is complementary to DCGs in predicting future costs.

Adolescent↗

PubMed2005

Evaluating concentration estimation errors in ELISA microarray experiments.

BACKGROUND: Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability. Evaluating estimation error is critical to interpreting biological significance and improving the ELISA microarray process. Estimation error evaluation must be automated to realize a reliable high-throughput ELISA microarray system. In this paper, we present a statistical method based on propagation of error to evaluate concentration estimation errors in the ELISA microarray process. Although propagation of error is central to this method and the focus of this paper, it is most effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization, and statistical diagnostics when evaluating ELISA microarray concentration estimation errors. RESULTS: We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of concentration estimation errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error. We summarize the results with a simple, three-panel diagnostic visualization featuring a scatterplot of the standard data with logistic standard curve and 95% confidence intervals, an annotated histogram of sample measurements, and a plot of the 95% concentration coefficient of variation, or relative error, as a function of concentration. CONCLUSIONS: This statistical method should be of value in the rapid evaluation and quality control of high-throughput ELISA microarray analyses. Applying propagation of error to a variety of ELISA microarray concentration estimation models is straightforward. Displaying the results in the three-panel layout succinctly summarizes both the standard and sample data while providing an informative critique of applicability of the fitted model, the uncertainty in concentration estimates, and the quality of both the experiment and the ELISA microarray process.

Algorithms↗

PubMed1999

[Arthrodesis of the talocalcaneal joint in adults. Indications, procedure, outcome].

Affections of the rear-foot-complex may occur because of various etiologies and show differing pathogenetic patterns. Besides posttraumatic changes, the rheumatoid arthritis, primary disorders and neurologic complications are registered. Biomechanically the hindfoot-complex is characterised by the joint play of ligamentous, bony and tendineal structures. Referring to diagnostics the clinical and radiologic examination are predominant. In the literature there is no uniform opinion concerning the therapeutic algorithm. The arthrodesis as a surgical procedure is commonly used, nevertheless important differences may be stated with regard to the choice of the osteosynthesis or the number of the joints to be fused. We present biomechanical models, diagnostic examinations and operative procedures in this context. Our own results of patients who underwent surgical interventions involving joints of the lower rear-foot using the Kitaoka hindfoot-score are demonstrated.

Adult↗

PubMed1997

Medical monitoring in long-term space missions.

The following principles, derived from the experience of medical support during past spaceflights, can provide a basis for a system of health monitoring and diagnosis during long-term and interplanetary missions: a system of preflight medical screening; medical screening on a systemic basis, which may include purposeful diagnosis in subsystems following the method of hierarchic structure; use of an individual approach; correction of the medical program with respect to the space crew status; assessment of the interrelations of the entire complex of parameters; utilization of the methods of correlation, classification and identification to elicit interrelations between different functions; evaluation of shifts in body functions and their adequacy to ambient conditions; continuity of medical examinations during all pre-flight stages, during flight and after completion of flight; analysis of information and anamnestic data by means of data bases; confidentiality of medical conclusions. Discussed are a classification of unfavorable microgravity-related syndromes, possible impairments due to abnormal situations, and some approaches to the prediction of the risk of various diseases, in relation to the construction of a conceptual diagnostic model for interplanetary missions. In the interest of medical monitoring special significance is attributed to the knowledge of individual norms for each crew member and of his unique peculiarities. Such data can be compiled by means of statistical analysis (single and multidimensional analysis) of the results of medical examinations and of observations during selection, training and tests. Selection of necessary physiological parameters, functional loads and data processing techniques which can be used in combination with other data sources for inflight diagnosis should be based on the following principles: the use of informative, non-invasively registered parameters and functional tests to reveal adverse states or most probable diseases; the possibility to assess the dynamics of physiological parameters and the status of the regulatory systems, and to predict possible developments in the body; the possibility to check the efficiency of countermeasures; the possibility to differentiate a physiological state adapted to the current environment from a pathological state; the possibility to differentiate between specific and non-specific reactions; the possibility to differentiate defensive, adaptive or compensatory phenomena from pathological manifestations. This paper describes the application of single- and multidimensional, statistical methods to process diagnostic information, to reduce the vector dimension of the chosen parameters, and to classify and identify individual and crew physiological standards providing the ability to assign an individual to a suitable team. Thus it will be possible to acquire comprehensive and statistically reliable information in compact format, and thus to perform a more incisive analysis and diagnosis of various states by comparing them with the baseline preflight data. These theoretical considerations constitute the basis for a conceptual model for medical diagnosis in long-term orbital and interplanetary missions. The paper contains a section dealing with the practical aspects of medical monitoring and diagnostic examinations during Mir missions. The program of medical monitoring for long-term Mir missions incorporates on-line monitoring during intravehicular and extravehicular activities, routine daily examinations, periodic extensive medical examinations accomplished on schedule or an indication. The Mir program includes cardiovascular investigations at rest and during functional loading, testing of the cosmonaut muscular systems, validation of the standard training protocols, occasional blood and urine analysis, incl. serum immunoglobulins, and blood cell counts. (ABSTRACT TRUNCATED)

Animals↗

PubMed2026

Circulating tumor-associated autoantibody signatures for diagnosis and prognosis in small-cell lung cancer and lung adenocarcinoma.

BACKGROUND: Tumour-associated autoantibodies (TAAbs) are promising biomarkers for cancer detection, but their induction and clinical relevance in lung cancer remain unclear. METHODS: Serum samples from 695 individuals were analysed for TAAb profiling by protein-array screening and two-stage ELISA validation. Diagnostic models were constructed with identified TAAbs and compared with conventional tumour markers. Potential mechanisms, clinical and prognostic features of TAAb seropositivity were analysed and its presence in prediagnostic sera was evaluated to assess the potential for early detection. RESULTS: Six TAAbs for small cell lung cancer (SCLC) and four for lung adenocarcinoma (LUAD) were identified, demonstrating excellent diagnostic performance (AUC > 0.8) and outperforming ProGRP and CEA. TAAb induction correlated with antigen overexpression, somatic mutations and HLA class II amino acid polymorphisms. TAAb panel seropositivity was associated with older age and advanced stage in both subtypes, and predicted poor survival in SCLC but a favourable outcome in advanced LUAD. In prediagnostic sera, the TAAb concentration increased progressively, with detectability up to 2 years before clinical diagnosis. CONCLUSIONS: Distinct TAAb panels were identified for SCLC and LUAD, serving as accurate diagnostic markers that enable early detection and as indicators of prognosis in different clinical contexts.

Humans↗

PubMed2004

The relation between trauma center outcome and volume in the National Trauma Databank.

BACKGROUND: Regionalization of trauma care services aims to improve outcomes by limiting trauma care delivery to a select group of dedicated trauma centers. However, the evidence linking trauma center volume and outcome is not conclusive. The objective of this study was to examine the volume-mortality relation for patients with severe trauma in the National Trauma Databank. METHODS: This study was based on data for adult patients 18 years of age or older in the National Trauma Databank with an Injury Severity Score (ISS) of 15 or more who sustained either blunt or penetrating trauma. The main outcome measure was in-hospital survival as a function of trauma center volume. Logistic regression modeling was used to analyze the relation between survival and hospital volume for patients sustaining either severe blunt or severe penetrating trauma. RESULTS: For the blunt trauma cohort, model diagnostics showed that the single highest-volume center was an outlier. After exclusion of the patients from this center, no association could be demonstrated between trauma volume and outcome (p = 0.465) for blunt trauma. A separate multivariate analysis of patients with penetrating trauma also could not demonstrate a significant volume-mortality association (p = 0.919). Both regression models exhibited excellent discrimination and acceptable calibration. CONCLUSION: The findings of this study do not support the position that higher trauma center volumes are associated with improved survival. The implication of this study is that the hospital volume criteria established by the American College of Surgeons may need to be reexamined.

Adolescent↗

PubMed2004

A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis.

MOTIVATION: Cancer diagnosis is one of the most important emerging clinical applications of gene expression microarray technology. We are seeking to develop a computer system for powerful and reliable cancer diagnostic model creation based on microarray data. To keep a realistic perspective on clinical applications we focus on multicategory diagnosis. To equip the system with the optimum combination of classifier, gene selection and cross-validation methods, we performed a systematic and comprehensive evaluation of several major algorithms for multicategory classification, several gene selection methods, multiple ensemble classifier methods and two cross-validation designs using 11 datasets spanning 74 diagnostic categories and 41 cancer types and 12 normal tissue types. RESULTS: Multicategory support vector machines (MC-SVMs) are the most effective classifiers in performing accurate cancer diagnosis from gene expression data. The MC-SVM techniques by Crammer and Singer, Weston and Watkins and one-versus-rest were found to be the best methods in this domain. MC-SVMs outperform other popular machine learning algorithms, such as k-nearest neighbors, backpropagation and probabilistic neural networks, often to a remarkable degree. Gene selection techniques can significantly improve the classification performance of both MC-SVMs and other non-SVM learning algorithms. Ensemble classifiers do not generally improve performance of the best non-ensemble models. These results guided the construction of a software system GEMS (Gene Expression Model Selector) that automates high-quality model construction and enforces sound optimization and performance estimation procedures. This is the first such system to be informed by a rigorous comparative analysis of the available algorithms and datasets. AVAILABILITY: The software system GEMS is available for download from http://www.gems-system.org for non-commercial use. CONTACT: alexander.statnikov@vanderbilt.edu.

Algorithms↗

PubMed2004

Evaluation of multiple models to distinguish closely related forms of disease using DNA microarray data: an application to multiple myeloma.

MOTIVATION: Standard laboratory classification of the plasma cell dyscrasia monoclonal gammopathy of undetermined significance (MGUS) and the overt plasma cell neoplasm multiple myeloma (MM) is quite accurate, yet, for the most part, biologically uninformative. Most, if not all, cancers are caused by inherited or acquired genetic mutations that manifest themselves in altered gene expression patterns in the clonally related cancer cells. Microarray technology allows for qualitative and quantitative measurements of the expression levels of thousands of genes simultaneously, and it has now been used both to classify cancers that are morphologically indistinguishable and to predict response to therapy. It is anticipated that this information can also be used to develop molecular diagnostic models and to provide insight into mechanisms of disease progression, e.g., transition from healthy to benign hyperplasia or conversion of a benign hyperplasia to overt malignancy. However, standard data analysis techniques are not trivial to employ on these large data sets. Methodology designed to handle large data sets (or modified to do so) is needed to access the vital information contained in the genetic samples, which in turn can be used to develop more robust and accurate methods of clinical diagnostics and prognostics. RESULTS: Here we report on the application of a panel of statistical and data mining methodologies to classify groups of samples based on expression of 12,000 genes derived from a high density oligonucleotide microarray analysis of highly purified plasma cells from newly diagnosed MM, MGUS, and normal healthy donors. The three groups of samples are each tested against each other. The methods are found to be similar in their ability to predict group membership; all do quite well at predicting MM vs. normal and MGUS vs. normal. However, no method appears to be able to distinguish explicitly the genetic mechanisms between MM and MGUS. We believe this might be due to the lack of genetic differences between these two conditions, and may not be due to the failure of the models. We report the prediction errors for each of the models and each of the methods. Additionally, we report ROC curves for the results on group prediction. AVAILABILITY: Logistic regression: standard software, available, for example in SAS. Decision trees and boosted trees: C5.0 from www.rulequest.com. SVM: SVM-light is publicly available from svmlight.joachims.org. Naïve Bayes and ensemble of voters are publicly available from www.biostat.wisc.edu/~mwaddell/eov.html. Nearest Shrunken Centroids is publicly available from http://www-stat.stanford.edu/~tibs/PAM.

Journal Article↗

PubMed1982

DSM III and consultation-liaison psychiatry: toward a comprehensive medical model of the patient.

The descriptive and multiaxial approaches in DSM III encourage comprehensive conceptualization of the patient. The use of explicit criteria for diagnosing syndromes facilitates communication between psychiatry and general medicine. The DSM III category Psychological Factors Affecting Physical Condition should be further elaborated into (a) Psychiatric Factors Affecting Physical Condition, and (b) Physical Condition Affecting Psychiatric Disorder. In addition, the phase of the illness these factors affect should be specified, i.e., the precipitation, course, and recovery. Somatoform Disorder should not be a diagnosis of exclusion, and the diagnostic criteria should clearly specify that conversion symptoms may be superimposed on a pre-existing physical disorder. The DSM III axes are not coherent: they include diagnostic categories, statements concerning possible relationships, and factors that might affect outcome. We propose an alternative to the DSM III Axes based on the Patient Evaluation Grid (PEG), a system comprised of four axes, including Biological Dimension, Personal Dimension, Environmental Dimension, and Assessment of Interaction Among Dimensions. Developing a comprehensive diagnostic model for both medical and psychiatric patients that can be shared by all physicians may be an important function of the liaison psychiatrist.

Depressive Disorder↗

PubMed1998

Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions. Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis.

OBJECTIVE: To compare the reliability of a new 7-point checklist based on simplified epiluminescence microscopy (ELM) pattern analysis with the ABCD rule of dermatoscopy and standard pattern analysis for the diagnosis of clinically doubtful melanocytic skin lesions. DESIGN: In a blind study, ELM images of 342 histologically proven melanocytic skin lesions were evaluated for the presence of 7 standard criteria that we called the "ELM 7-point checklist." For each lesion, "overall" and "ABCD scored" diagnoses were recorded. From a training set of 57 melanomas and 139 atypical nonmelanomas, odds ratios were calculated to create a simple diagnostic model based on identification of major and minor criteria for the "7-point scored" diagnosis. A test set of 60 melanomas and 86 atypical nonmelanomas was used for model validation and was then presented to 2 less experienced ELM observers, who recorded the ABCD and 7-point scored diagnoses. SETTINGS: University medical centers. PATIENTS: A sample of patients with excised melanocytic lesions. MAIN OUTCOME MEASURES: Sensitivity, specificity, and accuracy of the models for diagnosing melanoma. RESULTS: From the total combined sets, the 7-point checklist gave a sensitivity of 95% and a sepcificity of 75% compared with 85% sensitivity and 66% specificity using the ABCD rule and 91% sensitivity and 90% specificity using standard pattern analysis (overall ELM diagnosis). Compared with the ABCD rule, the 7-point method allowed less experienced observers to obtain higher diagnostic accuracy values. CONCLUSIONS: The ELM 7-point checklist provides a simplification of standard pattern analysis because of the low number of features to identify and the scoring diagnostic system. As with the ABCD rule, it can be easily learned and easily applied and has proven to be reliable in diagnosing melanoma.

Humans↗

PubMed2002

[Consultation or liaison psychotherapy service--what difference does it make for an outpatient pain clinic?].

OBJECTIVES: Even if the effectiveness of psychotherapy emphasising a cognitive behavioral approach is clearly shown by randomised controlled trials, it is difficult to motivate chronic pain patients to use this type of treatment. We compared the effectiveness of consultation and liaison models of co-operation between an outpatient pain clinic and a psychosomatic department in creating motivation to psychotherapy. METHODS: In a retrospective design we collected data of all patients seen in the pain clinic during two periods of 6 months before ( N=165) and after ( N=277) changing from a consultation to a liaison model. Clinical data were documented by the MASK system (Hildebrandt u. Pfingsten 1993). Depression was screened using a depression scale (vgl. Zerssen 1973), somatic complaints by listing of complaints (vgl. Zerssen u. Koeller 1976) and two short screening questionnaires. RESULTS: In the liaison model diagnostic sessions with the consulting psychotherapist were significantly more often recommended by physicians from anaesthesia departments (25.6% vs 13.9%; p<0.01) and accepted by patients (63.3 vs 30.4%; p<0.01). In both systems 80% of the patients accepted the suggested psychotherapy. After changing to the liaison type of co-operation, there was a significant decrease in the prescription of opioid and benzodiazepine drugs. CONCLUSIONS: The liaison model of co-operation was significantly more effective to enhance physician's and patient's motivation for a psychosomatic approach to pain treatment. Psychotherapy is better accepted by patients suffering from chronic pain if it is offered in a multidisciplinary context and in the familiar surroundings of the pain clinic.

Adolescent↗