Variability in clinical diagnoses during the ICD-8 and ICD-10 era

The operational paradigm in psychiatry: How valid is it?

BACKGROUND

One of the criticisms of the operational/diagnostic criteria, generalised since DSM-III, has been that they were shaped solely to achieve the best inter-peer reliability with no considerations for validity. This does not fully reflect reality since throughout the development of the criteria, there was an effort to define and fulfil some validity requirements. However, despite several attempts to create alternative diagnostic systems, there is still a widespread misunderstanding of the epistemological foundations that support this paradigm.

METHODS

In this article, we intend to analyse the epistemological context in which the operational criteria (OC) emerged and some of the validation processes they have undergone since their conception.

RESULTS

On the epistemological basis of these operational criteria (OC) the influence of Hempel has been widely discussed. However, the group from St. Louis and, also the DSM-III editors, never openly acknowledged his role and his contribution and revealed other influences such as other medical specialties (that used and validated several OC in the diagnosis of their diseases). On the other hand, contrary to what has often been mentioned there has been a continuous attempt to validate the OC since their conception. In the implementation and development of the operational paradigm, a more instrumental trend was followed, focused on utility, but with successive attempts to achieve realistic validity by searching for biological or psychological causality. The methodologies were initially expert-driven and gradually more data-driven and included some variables external to the construct itself, such as familial aggregation, diagnostic consistency over time, prognostic and other psychometric measures.

Towards New Methodology for Cross-Validation of Clinical Evaluation Scales and Functional MRI in Psychiatry

Objective biomarkers have been a critical challenge for the field of psychiatry, where diagnostic, prognostic, and theranostic assessments are still based on subjective narratives. Psychopathology operates with idiographic knowledge and subjective evaluations incorporated into clinical assessment inventories, but is considered to be a medical discipline and, as such, uses medical intervention methods (e.g., pharmacological, ECT; rTMS; tDCS) and, therefore, is supposed to operate with the language and methods of nomothetic networks. The idiographic assessments are provisionally "quantified" into "structured clinical scales" to in some way resemble nomothetic measures. Instead of fostering data merging and integration, this approach further encapsulates the clinical psychiatric methods, as all other biological tests (molecular, neuroimaging) are performed separately, only after the clinical assessment has provided diagnosis. Translational cross-validation of clinical assessment instruments and fMRI is an attempt to address the gap. The aim of this approach is to investigate whether there exist common and specific neural circuits, which underpin differential item responses to clinical self-rating scales during fMRI sessions in patients suffering from the two main spectra of mental disorders: schizophrenia and major depression. The current status of this research program and future implications to promote the development of psychiatry as a medical discipline are discussed.

A Tale of Three Spectra: Basic Symptoms in Clinical-High-Risk of Psychosis Vary Across Autism Spectrum Disorder, Schizotypal Personality Disorder, and Borderline Personality Disorder

Background and Hypothesis

The clinical-high-risk (CHR) approach was developed to prevent psychosis through the detection of psychosis risk. CHR services are transdiagnostic in nature, therefore the appropriate management of comorbidity is a central part of care. Differential diagnosis is particularly challenging across 3 common comorbidities, schizotypal personality disorder (SPD), autism spectrum disorder (ASD), and borderline personality disorder (BPD). Phenomenological research indicates a disturbance of "basic self" may differentiate between these commonly comorbid disorders and can be captured by Huber's basic symptoms (BS) concept. We investigated whether BS vary across these disorders and may inform differential diagnosis in young person's meeting CHR criteria.

Study Design

A total of 685 participants meeting CHR criteria from the NAPLS-3 cohort completed the COGDIS items of the schizophrenia proneness instrument, a measure of BS, as well as the structured interview for DSM-5 (SCID-5). A logistic regression model was used to investigate the variation of COGDIS across SPD, ASD, and BPD, while controlling for age and SIPs positive severity.

Study Results

Meeting COGDIS criteria was positively associated with SPD (OR = 1.72, CI = [1.31-2.28], P = .001) but not ASD nor BPD.

Conclusions

Our results indicate that "basic self-disturbance" as indicated by COGDIS differs across SPD, ASD, and BPD. COGDIS may be useful to inform the management of comorbidities in CHR services, by providing insight into subtle subjective experiences that may benefit from disorder-specific interventions.

Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006-2022 UK Biobank data

Objectives

Adverse childhood experiences (ACEs) and anxiety-depression co-morbidity are attracting widespread attention. Previous studies have shown the relationship between individual psychiatric disorders and ACEs. This study will analyze the correlation between anxiety-depression co-morbidity and different levels of ACEs.

Methods

Seven categories of ACE and four classifications of psychiatric disorders were defined in a sample of 126,064 participants identified by the UK Biobank from 2006-2022, and correlations were investigated using logistic regression models. Then, to explore nonlinear relationships, restricted spline models were developed to examine differences in sex and age across cohorts (n = 126,064 for the full cohort and n = 121,934 for the European cohort). Finally, the impact of the category of ACEs on psychiatric disorders was examined.

Results

After controlling for confounders, ACEs scores showed dose-dependent relationships with depression, anxiety, anxiety-depression co-morbidity, and at least one (any of the first three outcomes) in all models. ACEs with different scores were significantly positively correlated with the four psychiatric disorders classifications, with the highest odds of anxiety-depression co-morbidity (odds ratio [OR] = 4.87, 95% confidence intervals [CI]: 4.37 ~ 5.43), p = 6.08 × 10-178. In the restricted cubic spline models, the risk was relatively flat for females at ACEs = 0-1 and males at ACEs = 0-2/3 (except in males, where ACEs were associated with a lower risk of anxiety, all other psychiatric disorders had an increased risk of morbidity after risk smoothing). In addition, the risk of having anxiety, depression, anxiety-depression co-morbidity, and at least one of these disorders varies with each category of ACEs.

Conclusion

The prevalence of anxiety-depression comorbidity was highest across ACE scores after controlling for confounding factors and had a significant effect on each category of ACEs.

A unidirectional mapping of ICD-8 to ICD-10 codes, for harmonized longitudinal analysis of diseases

Periodic revisions of the international classification of diseases (ICD) ensure that the classification reflects new practices and knowledge; however, this complicates retrospective research as diagnoses are coded in different versions. For longitudinal disease trajectory studies, a crosswalk is an essential tool and a comprehensive mapping between ICD-8 and ICD-10 has until now been lacking. In this study, we map all ICD-8 morbidity codes to ICD-10 in the expanded Danish ICD version. We mapped ICD-8 codes to ICD-10, using a many-to-one system inspired by general equivalence mappings such that each ICD-8 code maps to a single ICD-10 code. Each ICD-8 code was manually and unidirectionally mapped to a single ICD-10 code based on medical setting and context. Each match was assigned a score (1 of 4 levels) reflecting the quality of the match and, if applicable, a "flag" signalling choices made in the mapping. We provide the first complete mapping of the 8596 ICD-8 morbidity codes to ICD-10 codes. All Danish ICD-8 codes representing diseases were mapped and 5106 (59.4%) achieved the highest consistency score. Only 334 (3.9%) of the ICD-8 codes received the lowest mapping consistency score. The mapping provides a scaffold for translation of ICD-8 to ICD-10, which enable longitudinal disease studies back to and 1969 in Denmark and to 1965 internationally with further adaption.

Profile changes in admissions to a psychiatric hospitalisation unit over 15 years (2006-2021), considering the impact of the pandemic caused by SARS-CoV-2

The objective of this current work was to explore whether modification of the diagnostic criteria upon the publication of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the impact of the COVID-19 pandemic had influenced the diagnostic and sociodemographic profiles of mental health admissions. For that purpose, we designed an observational, longitudinal, and retrospective study of the data recorded in the discharge reports of the Brief Hospitalization Unit at Castellon (Spain), between January 2006 and December 2021. The sample consisted of 7,037 participants, with a mean age of 42.1 years. The mean age of admissions, number of women, and presentation of affective disorders, addictions, and dementias all increased significantly during the DSM-5 period. Beyond diagnoses, the reduction in readmissions before the pandemic could be attributed to the use of long-acting injectable antipsychotics. In contrast, the pandemic did not change the percentage of readmissions or the volume of admissions. Also, during the pandemic period, the significant results obtained indicate that the average stay was reduced, affective disorders decreased, and addictions increased. Therefore, clinicians should consider these diagnostic and sociodemographic fluctuations when adapting clinical care, taking into account gender perspective, ageing of patients and increasing of dual and affective disorders.

Perspectives before incremental trans-disciplinary cross-validation of clinical self-evaluation tools and functional MRI in psychiatry: 10 years later

Translational validity (or trans-disciplinary validity) is defined as one possible approach to achieving incremental validity by combining simultaneous clinical state-dependent measures and functional MRI data acquisition. It is designed under the assumption that the simultaneous administration of the two methods may produce a dataset with enhanced synchronization and concordance. Translational validation aims at "bridging" the explanatory gap by implementing validated psychometric tools clinically in the experimental settings of fMRI and then translating them back to clinical utility. Our studies may have identified common diagnostic task-specific denominators in terms of activations and network modulation. However, those common denominators need further investigation to determine whether they signify disease or syndrome-specific features (signatures), which, at the end of the day, raises one more question about the poverty of current conventional psychiatric classification criteria. We propose herewith a novel algorithm for translational validation based on our explorative findings. The algorithm itself includes pre-selection of a test based on its psychometric characteristics, adaptation to the functional MRI paradigm, exploration of the underpinning whole brain neural correlates in healthy controls as compared to a patient population with certain diagnoses, and finally, investigation of the differences between two or more diagnostic classes.

How to construct neuroscience-informed psychiatric classification? Towards nomothetic networks psychiatry

Psychiatry remains in a permanent state of crisis, which fragmented psychiatry from the field of medicine. The crisis in psychiatry is evidenced by the many different competing approaches to psychiatric illness including psychodynamic, biological, molecular, pan-omics, precision, cognitive and phenomenological psychiatry, folk psychology, mind-brain dualism, descriptive psychopathology, and postpsychiatry. The current "gold standard" Diagnostic and Statistical Manual of Mental Disorders/International Classification of Diseases taxonomies of mood disorders and schizophrenia are unreliable and preclude to employ a deductive reasoning approach. Therefore, it is not surprising that mood disorders and schizophrenia research was unable to revise the conventional classifications and did not provide more adequate therapeutic approaches. The aim of this paper is to explain the new nomothetic network psychiatry (NNP) approach, which uses machine learning methods to build data-driven causal models of mental illness by assembling risk-resilience, adverse outcome pathways (AOP), cognitome, brainome, staging, symptomatome, and phenomenome latent scores in a causal model. The latter may be trained, tested and validated with Partial Least Squares analysis. This approach not only allows to compute pathway-phenotypes or biosignatures, but also to construct reliable and replicable nomothetic networks, which are, therefore, generalizable as disease models. After integrating the validated feature vectors into a well-fitting nomothetic network, clustering analysis may be applied on the latent variable scores of the R/R, AOP, cognitome, brainome, and phenome latent vectors. This pattern recognition method may expose new (transdiagnostic) classes of patients which if cross-validated in independent samples may constitute new (transdiagnostic) nosological categories.

Stability of admission diagnoses; data from a specialized in-patient treatment facility for dual diagnosis

AIM

We investigated the stability of diagnoses during admission over an 11-year period in patients admitted to a highly specialized integrated dual diagnosis treatment facility in Denmark using diagnosis coded in patient charts.

MATERIALS AND METHODS

Admission and discharge diagnoses from patient files were examined for stability of primary diagnosis and association with year of admission, age, sex, and duration of admission, in 1570 patients from 2007 to 2017.

RESULTS

A vast proportion (69.6%) of the patients retained their diagnosis during a 3-month admission. Stability was highest for schizophrenia spectrum diagnoses and lowest for unspecified diagnosis. Type of primary diagnosis, age, and length of admission was associated with lower likelihood of a stable primary diagnosis.

CONCLUSIONS

Long-term admission for psychiatric patients with substance use disorder (SUD) was significantly associated with stability of diagnosis. The finding calls for longer observation of dual diagnosis patients to ensure that relevant diagnosis is given, and consequently that the appropriate clinical treatment such as psychopharmacological as well as non-pharmacological intervention can be applied.

Exploring schizophrenia spectrum psychopathology in borderline personality disorder

We have previously argued that the current borderline personality disorder (BPD) diagnosis is over-inclusive and clinically and conceptually impossible to distinguish from the schizophrenia spectrum disorders. This study involves 30 patients clinically diagnosed with BPD as their main diagnosis by three BPD dedicated outpatient treatment facilities in Denmark. The patients underwent a careful and time-consuming psychiatric evaluation involving several senior level clinical psychiatrists and researchers and a comprehensive battery of psychopathological scales. The study found that the vast majority of patients (67% in DSM-5 and 77% in ICD-10) in fact met the criteria for a schizophrenia spectrum disorder, i.e., schizophrenia (20%) or schizotypal (personality) disorder (SPD). The schizophrenia spectrum group scored significantly higher on the level of disorders of core self as measured by the Examination of Anomalous Self-Experiences Scale (EASE). The BPD criterion of "identity disturbance" was significantly correlated with the mean total score of EASE. These findings are discussed in the light of changes from prototypical to polythetic diagnostic systems. We argue that the original prototypes/gestalts informing the creation of BPD and SPD have gone into oblivion during the evolution of polythetic criteria.

How to Construct a Bottom-Up Nomothetic Network Model and Disclose Novel Nosological Classes by Integrating Risk Resilience and Adverse Outcome Pathways with the Phenome of Schizophrenia

Current case definitions of schizophrenia (DSM-5, ICD), made through a consensus among experts, are not cross-validated and lack construct reliability validity. The aim of this paper is to explain how to use bottom-up pattern recognition approaches to construct a reliable and replicable nomothetic network reflecting the direct effects of risk resilience (RR) factors, and direct and mediated effects of both RR and adverse outcome pathways (AOPs) on the schizophrenia phenome. This study was conducted using data from 40 healthy controls and 80 patients with schizophrenia. Using partial least squares (PLS) analysis, we found that 39.7% of the variance in the phenomenome (lowered self-reported quality of life) was explained by the unified effects of AOPs (IgA to tryptophan catabolites, LPS, and the paracellular pathway, cytokines, and oxidative stress biomarkers), the cognitome (memory and executive deficits), and symptomatome (negative symptoms, psychosis, hostility, excitation, mannerism, psychomotor retardation, formal thought disorders); 55.8% of the variance in the symptomatome was explained by a single trait extracted from AOPs and the cognitome; and 22.0% of the variance in the latter was explained by the RR (Q192R polymorphism and CMPAase activity, natural IgM, and IgM levels to zonulin). There were significant total effects (direct + mediated) of RR and AOPs on the symptomatome and the phenomenome. In the current study, we built a reliable nomothetic network that reflects the associations between RR, AOPs, and the phenome of schizophrenia and discovered new diagnostic subclasses of schizophrenia based on unified RR, AOPs, and phenome scores.

Self-Disorders in Asperger Syndrome Compared to Schizotypal Disorder: A Clinical Study

OBJECTIVE

There are historical and theoretical indications of a difference in subjective experience between autism spectrum disorder (ASD) and the schizophrenia spectrum. However, this difference has not been empirically explored. Therefore, to explore potential differences in subjective experience between the 2 spectra, we examined the presence/absence of self-disorders in Asperger syndrome/autism spectrum disorder (As/ASD) compared to schizotypal disorder (Sd). Self-disorders represent changes in basic self-awareness which have been found to accumulate within the schizophrenia spectrum.

METHODS

All participants were recruited from clinical units and interviewed with a focus on the exploration of presence/absence of self-disorders, with the Examination of Anomalous Self-Experience (EASE) scale, and a general assessment of present psychopathology, with Schedules for Clinical Assessment in Neuropsychiatry (SCAN).

RESULTS

A total of 51 participants (As/ASD, n = 22; Sd, n = 29) were included in the statistical analyses. When controlling for age, gender, years of education, mental problems before the age of 16, and special needs school attendance, there was a clear difference in presence/absence of self-disorders between the 2 groups, with significantly higher levels in the Sd group. Further, there was an overlap in SCAN-rated symptoms between the 2 groups.

CONCLUSION

Our results indicate a significant difference between As/ASD and Sd at the level of the basic self, which, in turn, indicates that an exploration of anomalous self-experience is a valuable supplement in the clinical differentiation between As/ASD and Sd.

The Reification of Diagnosis in Psychiatry

Invited commentary on: The neuro-immune and neurotoxic fingerprint of major neuro-cognitive psychosis or deficit schizophrenia: a supervised machine learning study, by Maes et Al.