Development of a screening algorithm for borderline personality disorder using electronic health records.
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ABSTRACT:
SUBMITTER: Zang C
PROVIDER: S-EPMC9279396 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundBipolar disorder (BD) and borderline personality disorder (BPD) share overlapping phenomenology and are frequently misdiagnosed. This study investigated the diagnostic accuracy of the Mood Disorder Questionnaire (MDQ) and McLean Screening Instrument for Borderline Personality Disorder (MSI) in a clinical inpatient setting and whether individual screening items could differentiate BD from BPD.Methods757 sequential inpatients admitted to a Mood Disorder Unit completed both the MDQ and MSI. Screen positive for the MDQ was defined as ≥7/13 symptoms endorsed with concurrence and at least moderate impact. Screen positive for the MSI was defined as a score of ≥7. The clinical discharge summary diagnosis completed by a board-certified psychiatrist was used as the reference standard to identify concordance rates of a positive screen with clinical diagnosis. Individual items predicting one disorder and simultaneously predicting absence of other disorder by odds ratio (OR>and <1) were identified.ResultsBoth screening instruments were more specific than sensitive (MDQ 83.7%/ 67.8%, MSI 73.2% / 63.3%). MDQ individual items (elevated mood, grandiosity, increased energy, pressured speech, decreased need for sleep, hyperactivity) were significant predictors of BD diagnosis and non-predictors of BPD diagnosis. Whereas MSI subitem, self-harm behaviors/suicidal attempts predicted BPD in the absence of BD; distrust and irritability were additional predictors of BPD.ConclusionWhile this study is limited by the lack of structured diagnostic interview, these data provide differential symptoms to discriminate BD and BPD. Further work with larger datasets and more rigorous bioinformatics machine learning methodology is encouraged to continue to identify distinguishing features of these two disorders to guide diagnostic precision and subsequent treatment recommendations.
| S-EPMC8323027 | biostudies-literature
Project description:Borderline personality disorder is a chronic psychiatric disorder characterized by marked impulsivity, instability of mood and interpersonal relationships, and suicidal behaviour that can complicate medical care. Identifying this diagnosis is important for treatment planning. Although the cause of borderline personality disorder is uncertain, most patients improve with time. There is an evidence base for treatment using both psychotherapy and psychopharmacology. The clinical challenge centres on managing chronic suicidality.
| S-EPMC558173 | biostudies-literature
Project description: Not available
| S-EPMC3503902 | biostudies-literature
Project description:Purpose of Review:Variation in the monoamine oxidase A (MAO-A) gene and MAO-A enzyme levels have been linked to antisocial behavior and aggression in clinical and non-clinical populations. Here, we provide an overview of the genetic, epigenetic, and neuroimaging research that has examined MAO-A structure and function in antisocial personality disorder (ASPD) and borderline personality disorder (BPD). Recent Findings:The low-activity MAO-A variable nucleotide tandem repeat genetic polymorphism has shown a robust association with large samples of violent and seriously violent offenders, many of whom had ASPD. A recent positron emission tomography (PET) study of ASPD similarly revealed low MAO-A density in brain regions thought to contribute to the psychopathology of the condition. By contrast, PET has also demonstrated that brain MAO-A levels are increased in BPD and that they relate to symptoms of low mood and suicidality. Summary:Candidate gene studies have produced the most compelling evidence connecting MAO-A genetic variants to both ASPD and BPD. Still, conflicting results abound in the literature, making it highly unlikely that ASPD or BPD is related to a specific MAO-A genetic variant. Future research should strive to examine how MAO-A genotypes interact with broad-spectrum environmental influences to produce brain endophenotypes that may ultimately become tractable targets for novel treatment strategies.
| S-EPMC5846806 | biostudies-literature
Project description:Borderline personality disorder (BPD) is a complex psychiatric disease with an increased impact in the last years. While the diagnosis and therapy are well established, little is known on the pathogenesis of borderline personality disorder. Previously, a significant increase in DNA methylation of relevant neuropsychiatric genes in BPD patients has been reported. In our study we performed genome wide methylation analysis and revealed specific CpG sites that exhibited increased methylation in 26 BPD patients compared to 11 healthy controls. Bead chip technology and quantitative bisulfite pyrosequencing showed a significantly increased methylation at CpG sites of APBA2 (1.1 fold) and APBA3 (1.1 fold), KCNQ1 (1.6 fold), MCF2 (1.1 fold) and NINJ2 (1.2 fold) in BPD patients. For the CpG sites of GATA4 an increase in DNA methylation was observed, but was only significant in the bead chip assay. Moreover genome wide methylation levels of blood samples of BPD patients and control samples are similar. In summary, our results show a significant 1.26 fold average increase in methylation at the analyzed gene associated CpG sites in the blood of BPD patients compared to controls samples (p<0.001). This data may provide new insights into epigenetic mechanisms underlying the pathogenesis of BPD.
2014-02-01 | GSE52222 | GEO
Project description:BACKGROUND:The screening instrument for borderline personality disorder (SI-Bord) consists of a 5-item self-reported questionnaire on the key features of BPD from the DSM-5 using a 5-point Likert scale. This study investigated its validity and reliability in screening for BPD in university students. METHODS:A cross-sectional study was conducted on a sample of university students in Thailand between November and December 2019. An online assessment gathered demographic data and results from the SI-Bord, the Perceived Stress Scale-10 (PSS-10) and the Patient Health Questionnaire-9 (PHQ-9). Participants whose SI-Bord scores were???1 were randomly selected to be interviewed and assessed for a BPD diagnosis by four psychiatrists using the Structured Clinical Interview for DSM-IV Axis II Personality Disorders (SCID-II) as a reference point. An intraclass correlation coefficient (ICC) of 0.925 (95% CI, 0.805-0.979) ensured inter-rater reliability between the four psychiatrists. The diagnostic sensitivity and specificity of the SI-Bord, as compared to that of the SCID-II, were determined to indicate the cut-off score. The Receiver Operating Characteristics (ROC) was analyzed to evaluate its diagnostic accuracy. RESULTS:The study included 342 students aged 18-25?years (the mean age was 20.25?±?1.4?years), 80.4% of whom were female. Among the 68 participants selected for an online interview, 16 were diagnosed with BPD. The cut-off score of the SI-Bord was >?9, as suggested by the Youden index, yielding a sensitivity of 56.3% and a specificity of 92.3%. It had a positive predictive value of 69.2% and negative predictive value of 87.3%. The SI-Bord had adequate discriminative power between cases and non-cases of BPD, with the area under the ROC curve being 0.83. Cronbach's alpha for the SI-Bord was 0.76, indicating acceptable internal consistency. The SI-Bord score was positively correlated to PHQ-9 and PSS-10 scores (r?=?0.67 and r?=?0.69, p?<?0.001, respectively) and negatively correlated to MSPSS (r?=?-?0.50, p?<?0.001). The prevalence of BPD in the sample was 6.4%, according to the cut-off score?>?9. CONCLUSION:The SI-Bord demonstrated good reliability and validity for screening BPD in university students. However, a study in non-Thai and other population groups should be warranted.
| S-EPMC7526163 | biostudies-literature
Project description:BackgroundDrugs are widely used in borderline personality disorder (BPD) treatment, chosen because of properties known from other psychiatric disorders ("off-label use"), mostly targeting affective or impulsive symptom clusters.ObjectivesTo assess the effects of drug treatment in BPD patients.Search strategyWe searched bibliographic databases according to the Cochrane Developmental, Psychosocial and Learning Problems Group strategy up to September 2009, reference lists of articles, and contacted researchers in the field.Selection criteriaRandomised studies comparing drug versus placebo, or drug versus drug(s) in BPD patients. Outcomes included total BPD severity, distinct BPD symptom facets according to DSM-IV criteria, associated psychopathology not specific to BPD, attrition and adverse effects.Data collection and analysisTwo authors selected trials, assessed quality and extracted data, independently.Main resultsTwenty-eight trials involving a total of 1742 trial participants were included. First-generation antipsychotics (flupenthixol decanoate, haloperidol, thiothixene); second-generation antipsychotics (aripirazole, olanzapine, ziprasidone), mood stabilisers (carbamazepine, valproate semisodium, lamotrigine, topiramate), antidepressants (amitriptyline, fluoxetine, fluvoxamine, phenelzine sulfate, mianserin), and dietary supplementation (omega-3 fatty acid) were tested. First-generation antipsychotics were subject to older trials, whereas recent studies focussed on second-generation antipsychotics and mood stabilisers. Data were sparse for individual comparisons, indicating marginal effects for first-generation antipsychotics and antidepressants.The findings were suggestive in supporting the use of second-generation antipsychotics, mood stabilisers, and omega-3 fatty acids, but require replication, since most effect estimates were based on single studies. The long-term use of these drugs has not been assessed.Adverse event data were scarce, except for olanzapine. There was a possible increase in self-harming behaviour, significant weight gain, sedation and changes in haemogram parameters with olanzapine. A significant decrease in body weight was observed with topiramate treatment. All drugs were well tolerated in terms of attrition.Direct drug comparisons comprised two first-generation antipsychotics (loxapine versus chlorpromazine), first-generation antipsychotic against antidepressant (haloperidol versus amitriptyline; haloperidol versus phenelzine sulfate), and second-generation antipsychotic against antidepressant (olanzapine versus fluoxetine). Data indicated better outcomes for phenelzine sulfate but no significant differences in the other comparisons, except olanzapine which showed more weight gain and sedation than fluoxetine. The only trial testing single versus combined drug treatment (olanzapine versus olanzapine plus fluoxetine; fluoxetine versus fluoxetine plus olanzapine) yielded no significant differences in outcomes.Authors' conclusionsThe available evidence indicates some beneficial effects with second-generation antipsychotics, mood stabilisers, and dietary supplementation by omega-3 fatty acids. However, these are mostly based on single study effect estimates. Antidepressants are not widely supported for BPD treatment, but may be helpful in the presence of comorbid conditions. Total BPD severity was not significantly influenced by any drug. No promising results are available for the core BPD symptoms of chronic feelings of emptiness, identity disturbance and abandonment. Conclusions have to be drawn carefully in the light of several limitations of the RCT evidence that constrain applicability to everyday clinical settings (among others, patients' characteristics and duration of interventions and observation periods).
| S-EPMC4169794 | biostudies-literature
Project description:BackgroundChronic cough (CC) is difficult to identify in electronic health records (EHRs) due to the lack of specific diagnostic codes. We developed a natural language processing (NLP) model to identify cough in free-text provider notes in EHRs from multiple health care providers with the objective of using the model in a rules-based CC algorithm to identify individuals with CC from EHRs and to describe the demographic and clinical characteristics of individuals with CC.MethodsThis was a retrospective observational study of enrollees in Optum's Integrated Clinical + Claims Database. Participants were 18-85 years of age with medical and pharmacy health insurance coverage between January 2016 and March 2017. A labeled reference standard data set was constructed by manually annotating 1000 randomly selected provider notes from the EHRs of enrollees with ≥ 1 cough mention. An NLP model was developed to extract positive or negated cough contexts. NLP, cough diagnosis and medications identified cough encounters. Patients with ≥ 3 encounters spanning at least 56 days within 120 days were defined as having CC.ResultsThe positive predictive value and sensitivity of the NLP algorithm were 0.96 and 0.68, respectively, for positive cough contexts, and 0.96 and 0.84, respectively, for negated cough contexts. Among the 4818 individuals identified as having CC, 37% were identified using NLP-identified cough mentions in provider notes alone, 16% by diagnosis codes and/or written medication orders, and 47% through a combination of provider notes and diagnosis codes/medications. Chronic cough patients were, on average, 61.0 years and 67.0% were female. The most prevalent comorbidities were respiratory infections (75%) and other lower respiratory disease (82%).ConclusionsOur EHR-based algorithm integrating NLP methodology with structured fields was able to identify a CC population. Machine learning based approaches can therefore aid in patient selection for future CC research studies.
| S-EPMC9238070 | biostudies-literature
Project description:Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al. Am J Psychiatry 172:363-372, 2015). Here, we establish the genetic validity of these phenotypes by determining their genetic correlation with traditionally ascertained samples. Case and control algorithms were derived from structured and narrative text in the Partners Healthcare system comprising more than 4.6 million patients over 20 years. Genomewide genotype data for 3330 BD cases and 3952 controls of European ancestry were used to estimate SNP-based heritability (h2g) and genetic correlation (rg) between EHR-based phenotype definitions and traditionally ascertained BD cases in GWAS by the ICCBD and Psychiatric Genomics Consortium (PGC) using LD score regression. We evaluated BD cases identified using 4 EHR-based algorithms: an NLP-based algorithm (95-NLP) and three rule-based algorithms using codified EHR with decreasing levels of stringency-"coded-strict", "coded-broad", and "coded-broad based on a single clinical encounter" (coded-broad-SV). The analytic sample comprised 862 95-NLP, 1968 coded-strict, 2581 coded-broad, 408 coded-broad-SV BD cases, and 3 952 controls. The estimated h2g were 0.24 (p?=?0.015), 0.09 (p?=?0.064), 0.13 (p?=?0.003), 0.00 (p?=?0.591) for 95-NLP, coded-strict, coded-broad and coded-broad-SV BD, respectively. The h2g for all EHR-based cases combined except coded-broad-SV (excluded due to 0 h2g) was 0.12 (p?=?0.004). These h2g were lower or similar to the h2g observed by the ICCBD?+?PGCBD (0.23, p?=?3.17E-80, total N?=?33,181). However, the rg between ICCBD?+?PGCBD and the EHR-based cases were high for 95-NLP (0.66, p?=?3.69?×?10-5), coded-strict (1.00, p?=?2.40?×?10-4), and coded-broad (0.74, p?=?8.11?×?10-7). The rg between EHR-based BD definitions ranged from 0.90 to 0.98. These results provide the first genetic validation of automated EHR-based phenotyping for BD and suggest that this approach identifies cases that are highly genetically correlated with those ascertained through conventional methods. High throughput phenotyping using the large data resources available in EHRs represents a viable method for accelerating psychiatric genetic research.
| S-EPMC5904248 | biostudies-literature
Project description:Borderline personality disorder (BPD) patients, when in crisis, are frequent visitors of emergency departments (EDs). When these patients exhibit symptoms such as aggressiveness, impulsivity, intense anxiety, severe depression, self-harm, and suicidal attempts or gestures, diagnosis, and treatment of the BPD becomes challenging for ED doctors. This review will, therefore, outline advice to physicians and health-care providers who face this challenging patient population in the EDs. Crisis intervention should be the first objective of clinicians when dealing with BPD in the emergency. For the patients with agitation, symptom-specific pharmacotherapy is usually recommended, while for non-agitated patients, short but intensive psychotherapy especially dialectical behavior therapy (DBT) has a positive effect. Although various psychotherapies, either alone or integrated, are preferred modes of treatment for this group of patients, the effects of psychotherapies on BPD outcomes are small to medium. Proper risk management along with developing a positive attitude and empathy toward these patients will help them in normalizing in an emergency setting after which treatment course can be decided.
| S-EPMC5543278 | biostudies-other