Diagnostic Stability Research Articles

Diagnostic change 2 years after a first episode of psychosis

IntroductionPsychiatric diagnoses are derived from expert opinion (1). Since no objective tests or markers are on the horizon, clinical psychiatry is anchored to “the patient’s altered experience, expression and existence, associated with suffering in self and/or others”(2). Many studies have examined diagnostic stability over time. In the last years investigators have been reporting prospective and retrospective consistencies of diagnoses between two time points, specially in first episodes of psychosis (3).ObjectivesTo examine the prospective and retrospective stability of diagnostic categories 2 years after the first episode of psychosisMethodsData were examined from the First Episode Psychosis Program of Navarra (PEPsNA), a prospective observational study of a cohort of patients with first-episode psychosis in Navarra (Spain). Diagnosis was assigned using DSM-IV-TR at baseline and 24 months later. Diagnoses were divided into 5 categories: Affective psychosis, Schizophrenia spectrum psychosis, Schizoaffective disorder, acute psychosis and other diagnoses. Diagnostic change was examined using prospective and retrospective consistencyResultsA total of 78 first-episode psychosis cases with baseline and 24 months follow-up were identified. Table 1 shows the diagnosis movement matrix, and Figure 1 its graphical representation. Of cases, 71.8% (56/78) had the same baseline and 24 months follow-up diagnosis. Prospective and retrospective consistencies are shown in Table 2ConclusionsThe prospective and retrospective consistencies of Schizophrenia spectrum psychosis and acute psychosis were higher than others. Affective psychosis and Schizoaffective disorder show very variable consistencies

Prognostic significance of psychotic relapse in patients with first-episode acute and transient psychosis: New empirical support for ICD-11

This study examined the impact of psychotic relapse on the diagnostic stability of acute and transient psychotic disorders (ATPD), and how this potential risk factor could differentiate ‘acute polymorphic psychotic disorder without symptoms of schizophrenia’ (APPD; ICD-10 code F23.0) from the remaining non-APPD subtypes (F23.1–9). A two-year cohort study was performed on 68 patients with first-episode ATPD. At the end of follow-up, the diagnostic stability of ATPD was 55.9% and the overall rate of psychotic relapse was 61.8%. Statistical analysis showed that recurrence was an independent risk factor for diagnostic shift in ATPDs (relative risk [RR] = 1.67, 95% confidence interval [CI] = 1.17–2.39; p = 0.005) and that this risk differed among their subtypes insofar as its appearance significantly increased the likelihood of diagnostic change in patients with non-APPD subtypes (RR = 2.52, 95% CI = 1.56–4.07; p < 0.001), but not in those with APPD (RR = 0.95, 95% CI = 0.57–1.57; p = 0.844). Our findings confirm the negative implications of recurrence in patients with ATPD, encourage long-term intervention targeting relapse prevention in this population, and provide new empirical evidence in support of narrowing the ATPD category to APPD in the upcoming ICD-11.

What Do We Know about the Long-Term Course of Early Onset Bipolar Disorder? A Review of the Current Evidence.

Aim: Early onset of psychopathology is often an index of a more severe clinical course and worse prognosis. This review examined the course of bipolar disorder (BD) with onset in childhood and adolescence, with a focus on persistence of symptoms, severity of illness, comorbidity, and functional impairment. Methods: The databases of PubMed, Embase, and PsycInfo were systematically searched for publications since 1990 reporting on long-term (12 months or longer) assessments of patients with early onset BD. Results: Forty-two relevant publications were identified, which reported on data derived from 15 different patient cohorts, including 7 prospective research psychopathology studies, 4 medical record reviews, 2 follow-ups of clinical trial samples, 1 managed care database, and 1 nationwide registry, for a total of 10,187 patients. The length of follow-ups ranged from 1.0 to 15 years. Diagnostic stability of BD ranged from 73% to 100% over ten years. Recovery rate from an index episode was 81.5–100% and recurrence rate was 35–67%. Suicide attempt cumulative prevalence in five years was 18–20%. Earlier age at the first episode predicted a more severe clinical course. Conclusions: Early onset BD persists over time through adolescence, with homotypic diagnostic continuity over the years, but heterogeneity in the severity of the clinical course. Whether early identification and treatment improves distal prognosis remains to be further investigated.

Heterogeneity of borderline personality disorder symptoms in help-seeking adolescents

BackgroundThe heterogeneous presentation of borderline personality disorder (BPD) represents a clinical challenge. There is an ongoing scientific debate whether the heterogeneity can best be understood in terms of qualitative (categorical) or quantitative (dimensional) differences between individuals. The present study examined the latent structure of BPD in adolescents.MethodsFive-hundred and six outpatients aged 12 to 17 years with risk-taking and/or self-harming behavior were assessed at baseline and one-year follow-up. Latent class analysis (corresponding with the categorical approach), factor analysis (corresponding with the dimensional approach), and factor mixture models (allowing for both categorical and dimensional aspects) were applied to the DSM-IV BPD criteria.ResultsThe best fitting model distinguished between a majority class with high probabilities for all BPD criteria (“borderline group”) and a minority class with high probabilities for the impulsivity and anger criteria only (“impulsive group”). Sex significantly affected latent class membership, and both a latent factor and age explained within-class variability. The borderline group primarily consisted of females, frequently reported adverse childhood experiences, scored high on the emotion dysregulation and inhibitedness personality traits, and was associated with internalizing psychopathology. In contrast, the impulsive group primarily consisted of males, scored high on the dissocial behavior personality trait, and was associated with externalizing psychopathology. After one year, the two groups showed similar clinical improvement.ConclusionsThe study provides evidence for two distinct subgroups of adolescents with BPD features that resemble the subtypes of the ICD-10 emotionally unstable personality disorder. More research is needed to further investigate the diagnostic stability of the two groups over time and potential differential treatment indications.

Wilson disease tissue classification and characterization using seven artificial intelligence models embedded with 3D optimization paradigm on a weak training brain magnetic resonance imaging datasets: a supercomputer application.

Wilson's disease (WD) is caused by copper accumulation in the brain and liver, and if not treated early, can lead to severe disability and death. WD has shown white matter hyperintensity (WMH) in the brain magnetic resonance scans (MRI) scans, but the diagnosis is challenging due to (i) subtle intensity changes and (ii) weak training MRI when using artificial intelligence (AI). Design and validate seven types of high-performing AI-based computer-aided design (CADx) systems consisting of 3D optimized classification, and characterization of WD against controls. We propose a "conventional deep convolution neural network" (cDCNN) and an "improved DCNN" (iDCNN) where rectified linear unit (ReLU) activation function was modified ensuring "differentiable at zero." Three-dimensional optimization was achieved by recording accuracy while changing the CNN layers and augmentation by several folds. WD was characterized using (i) CNN-based feature map strength and (ii) Bispectrum strengths of pixels having higher probabilities of WD. We further computed the (a) area under the curve (AUC), (b) diagnostic odds ratio (DOR), (c) reliability, and (d) stability and (e) benchmarking. Optimal results were achieved using 9 layers of CNN, with 4-fold augmentation. iDCNN yields superior performance compared to cDCNN with accuracy and AUC of 98.28 ± 1.55, 0.99 (p < 0.0001), and 97.19 ± 2.53%, 0.984 (p < 0.0001), respectively. DOR of iDCNN outperformed cDCNN fourfold. iDCNN also outperformed (a) transfer learning-based "Inception V3" paradigm by 11.92% and (b) four types of "conventional machine learning-based systems": k-NN, decision tree, support vector machine, and random forest by 55.13%, 28.36%, 15.35%, and 14.11%, respectively. The AI-based systems can potentially be useful in the early WD diagnosis. Graphical Abstract.

Stability of co-occurring psychiatric diagnoses in autistic men and women

BackgroundDespite a high prevalence of psychiatric conditions in autistic adults, research examining the diagnostic stability of psychiatric conditions diagnosed prior to autism is limited. MethodThe present study examined the occurrence of (1) psychiatric diagnoses obtained before autism was diagnosed, (2) psychiatric conditions co-occurring with autism following its diagnosis, and (3) psychiatric conditions that were diagnosed before autism but no longer co-occurred with autism following its diagnosis. Participants (N = 1019, 51.5% female) provided information on psychiatric conditions predating their diagnosis of autism and psychiatric conditions co-occurring with autism. This information was combined to identify prior diagnoses that were no longer present post-autism diagnosis. ResultsResults showed that 50.2% of participants (62.7% of females and 37% of males) had at least one prior diagnosis. Mood and personality disorders were the most frequent prior diagnoses. Moreover, 59.3% (67% of females and 51% of males) reported having at least one diagnosis co-occurring with autism. Mood and anxiety disorders were the most frequent co-occurring diagnoses. Finally, 37.7% (47% of females and 27.3% of males) reported at least one previously diagnosed psychiatric condition that was no longer listed as a condition co-occurring with autism following its diagnosis. Personality disorders were most frequently no longer reported as diagnoses co-occurring with autism, despite being listed as prior diagnoses. ConclusionsThis study provides quantitative estimates of the temporal stability of specific psychiatric conditions before and after a diagnosis of autism in adults.

Stability of Subjective Executive Functioning in Older Adults with aMCI and Subjective Cognitive Decline.

Subjective memory concerns are characteristic of individuals with amnestic mild cognitive impairment (aMCI) and subjective cognitive decline (SCD), though subjective changes in executive functions have also been reported. In a cohort study, we examined the temporal stability of subjective report of executive functioning in a high education (mean=16.8years) sample of cognitively normal (CN) older adults and those with aMCI or SCD. Participants (CN, n=22; aMCI, n=21; SCD, n=24) and their informants completed the BRIEF-A and neuropsychological tests at two time points separated by approximately 1 year. Analyses focused on those with diagnostic stability (95.7%). Participants with aMCI and SCD, and their informants, endorsed worse executive functions relative to CN at both time points. No group by time interaction was observed for subjective or objective measures of executive function. Diagnostically stable CN older adults, and those with prodromal dementia conditions, report stable executive functioning at 1-year follow-up.

Parent-reported Autism Diagnostic Stability and Trajectories in the Longitudinal Study of Australian Children.

This study aimed to explore the stability of parent-reported diagnosis of Autism Spectrum Disorder (ASD) and factors influencing the trajectories in two cohorts from the prospective Longitudinal Study of Australian Children (LSAC). Parent-reported ASD diagnosis was collected for children from 6 years of age in a Birth cohort and 10 years of age in a Kinder cohort; allowing for exploration of diagnostic stability at age 6, 8, 10, and 12 years (Birth cohort) and 10, 12, 14, 16 years (Kinder cohort). Children were grouped based on persisting, desisting, inconsistent and late (diagnosis after 6 years-Birth cohort; after 10 years-Kinder) subgroups over four timepoints. Multinomial logistic regression explored predictors of diagnostic trajectories; generalized estimating equations examined trajectories of emotional and behavioral problems. Of 66 Birth cohort children parent-reported to have ASD at age 6, with data at all four time points, 14% did not at 12 years; of 73 Kinder cohort children at age 10 years, 26% no longer had parent-reported ASD at 16 years. Children with late diagnoses showed increasing trajectories of emotional and behavioral problems, while children with persisting or desisting diagnoses showed decreasing trajectories. Between 86% and 74% had a reported ASD diagnosis after 6 years. Findings indicate that children with ASD need services and supports that can adapt to their changing needs, which may be increasing, decreasing or different. This has implications for the provision of services and funding. LAY SUMMARY: This study explored how consistent parent-reported ASD diagnosis is over time in two groups of children from the Longitudinal Study of Australian Children (LSAC). Although up to 26% of children no longer had parent-reported ASD after 6-years follow up, persisting or late trajectories were more common. The outcome of late onset trajectories requires ongoing review. Autism Res 2021, 14: 773-786. © 2021 International Society for Autism Research and Wiley Periodicals LLC.

The complexity of early diagnostic decision making: A follow-up study of young children with language difficulties.

Due to the complexity of early diagnostic decision making, we examined the predictive value of an early diagnostic classification and early abilities on later best estimate diagnosis for 22 clinically referred children with language difficulties. Four years after initial evaluation (Time 1), the clinical files of these children were reviewed. A best-estimate (BE) diagnosis of language disorder (LD), intellectual disability (ID), or autism spectrum disorder (ASD) was established, with ASD being most common. Early clinical classifications were relatively unstable or difficult to establish at a young age. The magnitude of children's cognitive and receptive language delay was a significant predictor of a later BE diagnosis of ID and LD respectively. A BE diagnosis of ASD, by contrast, could not be predicted from children's early social communication problems nor the presence of restricted and repetitive behaviors and interests. Taken together, the results of this study suggest that language difficulties can be an early marker of a neurodevelopmental disorder which is often not identified at the age of first referral. Eligibility for treatment should, therefore, be based on biopsychosocial case formulation rather than DSM or ICD diagnostic classification. In this study a dimensional approach was used to characterize the abilities of young children referred with mild to profound receptive and/or expressive language difficulties. Later on, a categorical approach was adopted to establish best estimate diagnoses. Our clinical, broadly defined sample reflects the heterogeneous intake of young children referred for diagnostic assessment. Other studies on diagnostic stability often only focus on one diagnostic category (and are explicitly excluding children with specific other diagnoses), not taking into account the difficulties of early differential diagnostic decision making and stability across different categories over time. Investigations of differential diagnosis within a clinical group, instead of only differentiating children with a specific diagnosis from typically developing children, may be more informative for clinicians.

Clinical outcomes in brief psychotic episodes: a systematic review and meta-analysis.

Patients with brief psychotic episodes (BPE) have variable and fluctuating clinical outcomes which challenge psychiatric care. Our meta-analysis aims at providing a comprehensive summary of several clinical outcomes in this patient group. A multistep systematic PRISMA/MOOSE-compliant literature search was performed for articles published from inception until 1st March 2021. Web of Science database was searched, complemented by manual search of original articles reporting relevant outcomes (psychotic recurrence, prospective diagnostic change or stability, remission, quality of life, functional status, mortality and their predictors) for patients diagnosed with acute and transient psychotic disorders (ATPD), brief psychotic disorders (BPD), brief intermittent psychotic symptoms (BIPS) and brief limited intermittent psychotic symptoms (BLIPS). Random-effects methods and Q-statistics were employed, quality assessment with Newcastle-Ottawa Scale, assessment of heterogeneity with I2 index, sensitivity analyses (acute polymorphic psychotic disorders, APPD) and multiple meta-regressions, assessment of publication bias with funnel plot, Egger's test and meta-regression (psychotic recurrence and sample size). A total of 91 independent articles (n = 94 samples) encompassed 37 ATPD, 24 BPD, 19 BLIPS and 14 BIPS samples, totalling 15 729 individuals (mean age: 30.89 ± 7.33 years, mean female ratio: 60%, 59% conducted in Europe). Meta-analytical risk of psychotic recurrence for all BPE increased from 15% (95% confidence interval (CI) 12-18) at 6 months, 25% (95% CI 22-30) at 12 months, 30% (95% CI 27-33) at 24 months and 33% (95% CI 30-37) at ⩾36 months follow-up, with no differences between ATPD, BPD, BLIPS and BIPS after 2 years of follow-up. Across all BPE, meta-analytical proportion of prospective diagnostic stability (average follow-up 47 months) was 49% (95% CI 42-56); meta-analytical proportion of diagnostic change (average follow-up 47 months) to schizophrenia spectrum psychoses was 19% (95% CI 16-23), affective spectrum psychoses 5% (95% CI 3-7), other psychotic disorders 7% (95% CI 5-9) and other (non-psychotic) mental disorders 14% (95% CI 11-17). Prospective diagnostic change within APPD without symptoms of schizophrenia was 34% (95% CI 24-46) at a mean follow-up of 51 months: 18% (95% CI 11-30) for schizophrenia spectrum psychoses and 17% (95% CI 10-26) for other (non-psychotic) mental disorders. Meta-analytical proportion of baseline employment was 48% (95% CI 38-58), whereas there were not enough data to explore the other outcomes. Heterogeneity was high; female ratio and study quality were negatively and positively associated with risk of psychotic recurrence, respectively. There were no consistent factor predicting clinical outcomes. Short-lived psychotic episodes are associated with a high risk of psychotic recurrences, in particular schizophrenia spectrum disorders. Other clinical outcomes remain relatively underinvestigated. There are no consistent prognostic/predictive factors.

Forecasting residential electricity demand in the Philippines using an error correction model

This study uses an Error Correction Model (ECM) to forecast residential electricity demand in the Philippines using household final consumption expenditure, residential electricity price, and temperature as explanatory variables. Results show that there is a long-run relationship between household final consumption expenditure and residential electricity demand. Estimates from the ECM are consistent with economic theory, and the model passed standard diagnostic and parameter stability tests. Forecast performance based on within-sample and out-of-sample forecasts of the ECM is also shown to be superior, relative to a benchmark Autoregressive Distributed Lag (ARDL) model. Simulations show that by 2040, residential electricity consumption will range from 42,500 gigawatthours (GWh) based on a weak income growth scenario and 62,000 GWh based on a combined changes scenario.

One-Year Follow-Up Diagnostic Stability of Autism Spectrum Disorder Diagnosis in a Clinical Sample of Children and Toddlers.

Some studies show that the diagnosis of Autism Spectrum Disorder could be considered reliable and stable in children aged 18 to 24 months. Nevertheless, the diagnostic stability of early ASD diagnosis has not yet been fully demonstrated. This observational study examines the one-year diagnostic stability of autism spectrum disorder diagnosis in a clinical sample of 147 children diagnosed between 18 and 48 months of age. The ADOS-2 scores were used in order to stratify children in three levels of symptom severity: Autism (AD; comparison score 5–7), Autism Spectrum Disorder (ASD; comparison score 3–4), and Sub-Threshold Symptoms; (STS; comparison score 1–2). Results: Overall, the largest part of children and toddlers diagnosed with autism spectrum disorder between 18 and 48 months continued to show autistic symptoms at one-year follow-up evaluation. Nevertheless, a significant percentage of children with higher ADOS severity scores exhibited a reduction of symptom severity and, therefore, moved towards a milder severity class one year later. Conversely, the number of subjects of the STS group meaningfully increased. Therefore, at one-year follow-up a statistically significant (χ2(2) = 181.46, p < 0.0001) percentage of subjects (25.2% of the total) who had received a categorical diagnosis of Autistic Disorder or Autism Spectrum Disorder in baseline no longer met the criteria for a categorical diagnosis. Furthermore, children who no longer met the criteria for autism spectrum disorder continue to show delays in one or more neurodevelopmental areas, possibly related to the emergence of other neurodevelopmental/neuropsychiatric disorders. Overall, the comprehensive results of the study account for a high sensibility but a moderate stability of ASD early diagnosis.

Multi-stage fault diagnosis framework for rolling bearing based on OHF Elman AdaBoost-Bagging algorithm

With the increasing complexity of industrial equipment, it is urgent to provide timely diagnosis and accurate evaluation to avoid failure. For rolling bearings, it is important to achieve the multi-stage (incipient, intermediate, late) fault diagnosis under random noise. Different from traditional methods, an Output Hidden Feedback Elman Adaptive Boosting-Bootstrap Aggregating algorithm is proposed under a comprehensive diagnosis framework. First, the original signal is decomposed, denoised and reconstructed by Ensemble Empirical Mode Decomposition. Then, OHF Elman neural network is designed by increasing a feedback from the output layer to the hidden layer based on Elman neural network. This improves the memory function for dynamic data of rolling bearings. Furthermore, for achieving diagnostic accuracy and algorithm stability, OHF Elman AdaBoost-Bagging algorithm is developed as a strong learner through the dual integration of AdaBoost algorithm and Bagging algorithm. Experimental results show that the proposed algorithm not only has a good diagnostic performance on different stages of rolling bearing faults, but also achieves higher generalization ability and stability. This multi-stage fault diagnosis framework provides a novel tool and an effective solution for rolling bearing fault diagnosis.

An initial examination of the psychometric properties of the Diagnostic Instrument for Social and Communication Disorders (DISCO-11) in a clinical sample of children with a diagnosis of Autism spectrum disorder.

The diagnostic interview for social and communication disorders (DISCO - 11; Wing 2006), is a semi-structured, interview-based instrument used in the diagnosis of children with autism spectrum disorder (ASD). This paper explores the psychometric properties of the DISCO-11 used in a specialist Paediatric clinical setting. Two key research questions were examined; (1) Does the factor structure of the DISCO-11 reflect the diagnostic and statistical manual 5th edition (DSM-5, American Psychiatric Association [APA], 2013) dyad of impairment in ASD? (2) Is there evidence of diagnostic stability over time using the DISCO? Review assessments of 65 children with ASD were carried out using standardised measures including the DISCO-11 and the autism diagnostic observation schedule. The results revealed two factors resembling the DSM-5 algorithms, as used in DISCO-11, which were named as social-communication, and restricted and repetitive behaviours. The reliability, for the overall DISCO score was good (Cronbach's alpha = 0.78). The social communication and social interaction subscale showed good reliability (Cronbach's Alpha = 0.77) as did the restricted and repetitive patterns of behaviour, interests or activities subscale (Cronbach's Alpha = 0.74). Acceptable internal reliability was found for the overall DISCO score and the subscales of social communication and social interaction and the restricted and repetitive patterns of behaviour, interests or activities. Test-retest showed good stability of diagnosis over time. This study supports that the DISCO-11 shows potential as a valid and reliable instrument that can be used both for clinical and research purposes.

Diagnostic stability and outcome after first episode psychosis

Background Individuals diagnosed with schizophrenia are often assigned other psychiatric diagnoses during their lives. The significance of changing diagnosis has not been widely studied. Aims Our aim was to examine the association between diagnostic change and later outcome. Methods Individuals’ diagnostic history, clinical and social outcomes were extracted from the AESOP-10 study, a 10-year follow-up of first episode psychosis cases. The association between outcome and different patterns of diagnosis over time were assessed using linear or logistic regression. Results Individuals always diagnosed with schizophrenia (n = 136) had worse clinical and social outcomes at follow-up than those never diagnosed with schizophrenia (n = 163), being more likely to be symptomatic, unemployed, single, and socially isolated. There was no difference in outcome between individuals always diagnosed with schizophrenia and those changing to a diagnosis of schizophrenia (n = 60), and no difference in outcome between individuals never diagnosed with schizophrenia, and those changing from a diagnosis of schizophrenia (n = 44). Conclusions Individuals always and never diagnosed with schizophrenia had different outcomes. In cases of diagnostic instability participants had similar outcomes to those always assigned the diagnosis they changed to irrespective of initial diagnosis.

A Cotton Disease Diagnosis Method Using a Combined Algorithm of Case-Based Reasoning and Fuzzy Logic

Abstract In this study, a cotton disease diagnosis method that uses a combined algorithm of case-based reasoning (CBR) and fuzzy logic was designed and implemented. It focuses on the prevention, diagnosis and control of diseases affecting cotton production in China. Conventional methods of disease diagnosis are primarily based on CBR with reference to user-provided symptoms; however, in most cases, user-provided symptoms do not fully meet the requirements of CBR. To address this problem, fuzzy logic is incorporated into CBR to allow for more flexible and accurate models. With the help of CBR and fuzzy reasoning, three diagnostic results can be obtained by the cotton disease diagnosis system (CDDS) constructed in this study: success, success but not exact and failure. To verify the reliability of the CDDS and its ability to diagnose cotton diseases, its diagnostic accuracy and stability were analyzed and compared with the results obtained by the traditional expert scoring method. The analysis results reveal that the CDDS can achieve a high diagnostic success rate (above 90%) and better diagnostic stability than the traditional expert scoring method when at least four disease symptoms are input. The CDDS provides an independent and objective source of information to assist farmers in the diagnosis and prevention of cotton diseases.

Bipolar disorder diagnostic stability: a Portuguese multicentric study

Bipolar disorder diagnostic stability: a Portuguese multicentric study

A Comparison of Diagnostic Stability of the ASIA Impairment Scale Versus Frankel Classification Systems for Traumatic Spinal Cord Injury

ObjectiveTo determine whether the “sacral sparing” definition for completeness of traumatic spinal cord injury (SCI) is a more stable definition than the previously used Frankel Classification. DesignRetrospective analysis of individuals enrolled in the Spinal Cord Injury Model Systems (SCIMS) database between 2011 and 2018. SettingSCIMS centers. ParticipantsIndividuals (N=804) with traumatic SCI who were at least 16 years old at time of injury, were admitted to rehabilitation within 30 days, had American Spinal Injury Association Impairment Scale (AIS) grades A-D at admission, and had complete neurologic data at the time of admission and 1 year. InterventionNot applicable. Main Outcome MeasuresFrankel and AIS scores were computed for a cohort of 804 eligible cases. Stability was compared between the 2 classification systems by calculating the proportions of cases in which regression (conversion to a more severe impairment level) was observed. ResultsA larger proportion of individuals classified with “incomplete” injuries (grades B-D) at the time of admission using the Frankel system regressed to complete status at 1 year compared with the AIS criteria (9.4% vs 2.0%). Those with grade B injuries regressed to grade A more often using the Frankel system compared with the AIS system (19.7% to 5.4%). A larger proportion of people diagnosed as Frankel grade C or D regressed to Frankel grade A compared with individuals diagnosed as AIS grade C or D who regressed to AIS grade A (5.0% to 1.1%). ConclusionsMore individuals diagnosed with neurologically incomplete SCI regressed to complete status at 1 year when using the Frankel system compared with AIS classification, which is based on sacral sparing. This reinforces the finding that the “sacral sparing” definition is a more stable classification in traumatic SCI.

Psychotic disorders in the diagnostic stability of a Portuguese ward - Diagnostic retrospective analysis

ObjectivesPsychiatric diagnosis is based on clinical manifestations, resulting from patients’ internal state, their life situation, the evolution of their condition and the response to our interventions. There are currently few objective data which help to establish the diagnosis which is why this is based on diagnostic criteria such as the Diagnostic and Statistical Manual of Mental Disorders (DSM).The DSM defines entities by their diagnostic stability, however there are several causes of variability as categorised by Spritzer et al. (1987): subjects variance (changing in patients), occasions variance (different episodes), information variance (new information) and observation variance (different interpretations).This paper aims to determine the diagnostic stability of patients with Psychotic Disorders among patients readmitted to our Psychiatric Unit. MethodsRetrospective analysis of the diagnoses of patients with Psychotic Disorders who had been readmitted to our unit. We analysed data from the last 12 years – 5422 admission episodes with 507 patients with a relevant diagnosis in this period. ResultsPsychiatric diagnosis does evolve over time, nevertheless some diagnostic groups show a relatively significant stability over time – Bipolar Disorder and Schizophrenia with 69% and 77% stability, respectively. Diagnosis such as Depressive Psychosis and Drug-induced psychosis show a significantly lower stability (8% and 21%, respectively). ConclusionsKnowing our own reality can make us aware that a cross-sectional view of patients can be insufficient and only time can determine a clear diagnosis. This study may help us to understand how psychotic disorders evolve.

MR enterocolonography in patients with Crohn's disease and healthy volunteers – Do we achieve diagnostic bowel distension?

PurposeThe aim of our prospective randomized study was to assess diagnostic quality and stability of bowel distension in patients with Crohn’s disease (CD) and healthy volunteers subjected to synchronous magnetic resonance enterography and colonography (MREC), as well as to test the role of water enema and intravenous spasmolytics. The influence of gastric content, age, gender, and body mass on bowel distension was also evaluated. MethodStudy groups included 164 CD patients and 53 healthy volunteers. After bowel preparation, randomized subgroups started ingestion ≥1000 mL of hyperosmolar solution within 30, 45, 60, 75, and 90 min before admission to MRI, respectively. Patients were examined in prone position and water enema was applied. Spasmolytics were administered prior to I.V. gadolinium. Distension of five bowel segments was independently assessed by two experienced radiologists. ResultsMREC yields diagnostic distension of the jejunum in 81.1 % and 79.2 % patients in the CD group and controls, respectively. For the terminal ileum it was >94 % in both groups. Good and excellent distension was achieved in other bowel segments. Distension was maintained up to 75 min from the start of oral ingestion. Water enema and spasmolytics significantly and independently improved distension of the small bowel. Distension of the cecum after spasmolytics was decreased. Gastric content, age, gender and body mass had no significant influence of bowel distension. ConclusionsMREC enables diagnostic distension of the colon and ileum (including terminal segment) in CD patients and healthy volunteers and diagnostically acceptable distension of the jejunum.