Dataset Information

What do clinicians treat: Diagnoses or symptoms? The incremental validity of a symptom-based, dimensional characterization of emotional disorders in predicting medication prescription patterns.

ABSTRACT: BACKGROUND:Although practice guidelines are based on disorders specified in diagnostic manuals, such as the DSM, practitioners appear to follow symptoms when making treatment decisions. Psychiatric medication is generally prescribed in a transdiagnostic manner, further highlighting how symptoms, not diagnoses, often guide clinical practice. A quantitative approach to nosology promises to provide better guidance as it describes psychopathology dimensionally and its organization reflects patterns of covariation among symptoms. AIM:To investigate whether a quantitative classification of emotional disorders can account for naturalistic medication prescription patterns better than traditional diagnoses. METHODS:Symptom dimensions and DSM diagnoses of emotional disorders, as well as prescribed medications, were assessed using interviews in a psychiatric outpatient sample (N=318, mean age 42.5years old, 59% female, 81% Caucasian). RESULTS:Each diagnosis was associated with prescription of multiple medication classes, and most medications were associated with multiple disorders. This was largely due to heterogeneity of clinical diagnoses, with narrow, homogenous dimensions underpinning diagnoses showing different medication profiles. Symptom dimensions predicted medication prescription better than DSM diagnoses, irrespective of whether this was examined broadly across all conditions, or focused on a specific disorder and medication indicated for it. CONCLUSIONS:Psychiatric medication was prescribed in line with symptoms rather than DSM diagnoses. A quantitative approach to nosology may better reflect treatment planning and be a more effective guide to pharmacotherapy than traditional diagnoses. This adds to a diverse body of evidence about superiority of the quantitative system in practical applications and highlights its potential to improve psychiatric care.

SUBMITTER: Waszczuk MA

PROVIDER: S-EPMC5643213 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

What do clinicians treat: Diagnoses or symptoms? The incremental validity of a symptom-based, dimensional characterization of emotional disorders in predicting medication prescription patterns.

Waszczuk Monika A MA Zimmerman Mark M Ruggero Camilo C Li Kaiqiao K MacNamara Annmarie A Weinberg Anna A Hajcak Greg G Watson David D Kotov Roman R

Comprehensive psychiatry 20170418

<h4>Background</h4>Although practice guidelines are based on disorders specified in diagnostic manuals, such as the DSM, practitioners appear to follow symptoms when making treatment decisions. Psychiatric medication is generally prescribed in a transdiagnostic manner, further highlighting how symptoms, not diagnoses, often guide clinical practice. A quantitative approach to nosology promises to provide better guidance as it describes psychopathology dimensionally and its organization reflects p ...[more]

PMID: 28495012

Similar Datasets

Project description:A growing literature suggests robust associations between dimensions of emotion regulation and emotional disorder psychopathology. However, limited research has investigated associations of emotion regulation dimensions across several emotional disorders (transdiagnostic associations), or the incremental validity of emotion regulation versus the higher-order construct of neuroticism. The current study used exploratory structural equation modeling and a large clinical sample (N = 1,138) to: (a) develop a multidimensional emotion regulation measurement model, (b) evaluate the differential associations between latent emotion regulation dimensions and five latent emotional disorder symptom dimensions (social anxiety, depression, agoraphobia/panic, obsessions/compulsions, generalized worry), and (c) determine the incremental contribution of emotion regulation in predicting symptom dimensions beyond neuroticism. The best-fitting measurement model of emotion regulation included four dimensions: Problematic Responses, Poor Recognition/Clarity, Negative Thinking, and Emotional Inhibition/Suppression. Although many zero-order associations between the four latent emotion regulation dimensions and five latent symptom dimensions were significant, few associations remained significant in a structural regression model that included neuroticism. Specifically, Negative Thinking and Problematic Responses incrementally predicted depression symptoms, while Emotional Inhibition/Suppression predicted both social anxiety and depression symptoms. Associations between neuroticism and the emotional disorder dimensions were similar regardless of whether the emotion regulation dimensions were held constant. These results suggest that self-reported emotion regulation dimensions are associated with the severity and expression of a range of emotional disorder symptoms, but that some emotion regulation dimensions have limited incremental validity after accounting for general emotional reactivity. Studies of emotion regulation should assess neuroticism as a key covariate.

Project description:ImportanceBecause more patients are presenting with self-guided research of symptoms, it is important to assess the capabilities and limitations of these available health information tools.ObjectiveTo determine the accuracy of the most popular online symptom checker for ophthalmic diagnoses.Design, setting, and participantsIn a cross-sectional study, 42 validated clinical vignettes of ophthalmic symptoms were generated and distilled to their core presenting symptoms. Cases were entered into WebMD symptom checker by both medically trained and nonmedically trained personnel blinded to the diagnosis. Output from the symptom checker, including the number of symptoms, ranking and list of diagnoses, and triage urgency were recorded. The study was conducted on October 13, 2017. Analysis was performed between October 15, 2017, and April 30, 2018.Main outcomes and measuresAccuracy of the top 3 diagnoses generated by the online symptom checker.ResultsThe mean (SD) number of symptoms entered was 3.6 (1.6) (range, 1-8). The median (SD) number of diagnoses generated by the symptom checker was 26.8 (21.8) (range, 1-99). The primary diagnosis by the symptom checker was correct in 11 of 42 (26%; 95% CI, 12%-40%) cases. The correct diagnosis was included in the online symptom checker's top 3 diagnoses in 16 of 42 (38%; 95% CI, 25%-56%) cases. The correct diagnosis was not included in the symptom checker's list in 18 of 42 (43%; 95% CI, 32%-63%) cases. Triage urgency based on the top diagnosis was appropriate in 7 of 18 (39%; 95% CI, 14%-64%) emergent cases and 21 of 24 (88%; 95% CI, 73%-100%) nonemergent cases. Interuser variability for the correct diagnosis being in the top 3 listed was at least moderate (Cohen κ = 0.74; 95% CI, 0.54-0.95).Conclusions and relevanceThe most popular online symptom checker may arrive at the correct clinical diagnosis for ophthalmic conditions, but a substantial proportion of diagnoses may not be captured. These findings suggest that further research to reflect the real-life application of internet diagnostic resources is required.

Project description:AimHospital discharges with a diagnosis of cardiomyopathy have more than doubled in Sweden since 1987. We validated the cardiomyopathy diagnoses over this time period to investigate that the increase was real and not a result of improved recognition of the diagnosis and better diagnostic methods.Methods and resultsEvery fifth year from 1989 to 2009, records for all patients with a cardiomyopathy diagnosis were identified by searching the local registers in three hospitals in Västra Götaland, Sweden. The diagnoses were validated according to criteria defined by the European Society of Cardiology from 2008. The population comprised 611 cases with cardiomyopathy diagnoses [mean age 58.9 (SD 15.5) years, 68.2% male], divided into three major groups: dilated, hypertrophic, and other cardiomyopathies. Hypertrophic cardiomyopathy and hypertrophic obstructive cardiomyopathy were analysed as a group. Cardiomyopathies for which there were few cases, such as restrictive, arrhythmogenic right ventricular, left ventricular non-compaction, takotsubo, and peripartum cardiomyopathies, were analysed together and defined as 'other cardiomyopathies'. Relevant co-morbidities were registered. The use of echocardiography was 99.7%, of which 94.6% was complete echocardiography reports. The accuracy rates of the diagnoses dilated cardiomyopathy, hypertrophic cardiomyopathy, and other cardiomyopathies were 85.5%, 87.5%, and 100%, respectively, with no differences between the three hospitals or years studied; nor did the prevalence of co-morbidities differ.ConclusionsThe accuracy rate of the cardiomyopathy diagnoses from in-hospital records from >600 patients in western Sweden during a 20 year period was 86.6%, with no significant trend over time, strengthening epidemiological findings that this is likely due to an actual increase in cardiomyopathy diagnoses rather than changes in coding practices. The use of echocardiography was high, and there was no significant difference in co-morbidities during the study period. The accuracy rate of the cardiomyopathy diagnoses during the 20 year period was high. The use of diagnostic tools did not increase under the study period, and once cardiomyopathy diagnoses were suspected, echocardiography was performed in almost all cases. In this study, the occurrence of cardiomyopathy was increasing over time without significant increase of co-morbidity, supporting that an actual increase of cardiomyopathy has occurred.

Dataset Information

What do clinicians treat: Diagnoses or symptoms? The incremental validity of a symptom-based, dimensional characterization of emotional disorders in predicting medication prescription patterns.

Publications

What do clinicians treat: Diagnoses or symptoms? The incremental validity of a symptom-based, dimensional characterization of emotional disorders in predicting medication prescription patterns.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets