Risk Factors for the Onset of Bipolar Disorder and Factors Influencing Recognition: Results from NEMESIS

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
E.J. Regeer ◽  
J. Spijker

Aims:Risk factors for the onset of bipolar disorder and factors influencing recognition were examined in a general population sample.Method:In the Netherlands Mental Health Survey and Incidence Study (NEMESIS) symptoms of depression, mania, psychosis and substance use were assessed among 7076 respondents with the Composite International Diagnostic Interview at baseline, after one and after three years. In a reappraisal study among 40 respondents with bipolar disorder confirmed by the Structured Clinical Interview for DSM-IV (SCID) data on illness and treatment history were collected.Results:Predictive values of subclinical depression and (hypo)mania for bipolar disorder ranged from 14.3% to 50%. Cannabis use at baseline increased the risk for manic symptoms during follow-up (OR 2.70, 95%CI:1.54-4.75) (Henquet et al., 2006). Comorbid subclinical psychosis in respondents with subclinical mania had predictive value for future diagnosis of bipolar disorder (positive predictive value of 3% versus 10% respectively) (Kaymaz et al., 2007). The majority of the respondents with a SCID diagnosis bipolar disorder consulted a health professional, only 12.5% received a diagnosis of bipolar disorder and agreed with the diagnosis. Only these respondents used a moodstabilizer and had contact with a psychiatrist. Type of bipolar disorder, number of mood episodes and age of onset did not influence recognition.Conclusion:Subclinical depression and (hypo)mania, and comorbity of subclinical psychosis and mania are predictive for future diagnosis of bipolar disorder. Cannabis use affects the expression of manic symptoms. Self-recognition of bipolar disorder is an important factor in treatment seeking and receiving adequate treatment.

CNS Spectrums ◽  
2021 ◽  
Vol 26 (2) ◽  
pp. 167-168
Author(s):  
C. Brendan Montano ◽  
Mehul Patel ◽  
Rakesh Jain ◽  
Prakash S. Masand ◽  
Amanda Harrington ◽  
...  

AbstractIntroductionApproximately 70% of patients with bipolar disorder (BPD) are initially misdiagnosed, resulting in significantly delayed diagnosis of 7–10 years on average. Misdiagnosis and diagnostic delay adversely affect health outcomes and lead to the use of inappropriate treatments. As depressive episodes and symptoms are the predominant symptom presentation in BPD, misdiagnosis as major depressive disorder (MDD) is common. Self-rated screening instruments for BPD exist but their length and reliance on past manic symptoms are barriers to implementation, especially in primary care settings where many of these patients initially present. We developed a brief, pragmatic bipolar I disorder (BPD-I) screening tool that not only screens for manic symptoms but also includes risk factors for BPD-I (eg, age of depression onset) to help clinicians reduce the misdiagnosis of BPD-I as MDD.MethodsExisting questionnaires and risk factors were identified through a targeted literature search; a multidisciplinary panel of experts participated in 2 modified Delphi panels to select concepts thought to differentiate BPD-I from MDD. Individuals with self-reported BPD-I or MDD participated in cognitive debriefing interviews (N=12) to test and refine item wording. A multisite, cross-sectional, observational study was conducted to evaluate the screening tool’s predictive validity. Participants with clinical interview-confirmed diagnoses of BPD-I or MDD completed a draft 10-item screening tool and additional questionnaires/questions. Different combinations of item sets with various item permutations (eg, number of depressive episodes, age of onset) were simultaneously tested. The final combination of items and thresholds was selected based on multiple considerations including clinical validity, optimization of sensitivity and specificity, and pragmatism.ResultsA total of 160 clinical interviews were conducted; 139 patients had clinical interview-confirmed BPD-I (n=67) or MDD (n=72). The screening tool was reduced from 10 to 6 items based on item-level analysis. When 4 items or more were endorsed (yes) in this analysis sample, the sensitivity of this tool for identifying patients with BPD-I was 0.88 and specificity was 0.80; positive and negative predictive values were 0.80 and 0.88, respectively. These properties represent an improvement over the Mood Disorder Questionnaire, while using >50% fewer items.ConclusionThis new 6-item BPD-I screening tool serves to differentiate BPD-I from MDD in patients with depressive symptoms. Use of this tool can provide real-world guidance to primary care practitioners on whether more comprehensive assessment for BPD-I is warranted. Use of a brief and valid tool provides an opportunity to reduce misdiagnosis, improve treatment selection, and enhance health outcomes in busy clinical practices.FundingAbbVie Inc.


2009 ◽  
Vol 15 (6) ◽  
pp. 665-670
Author(s):  
A. A. Dzizinskij ◽  
G. M. Sinkova ◽  
V. V. Sprach ◽  
A. V. Sinkov

Objective. To assess predictive value of total cardiovascular risk (CV) factors for prognosis of stroke and heart attack in hypertension. Design and methods. 841 hypertensive patients (197 men, 644 women) 19-95 years old were examined. Results. It was established that total CV risk factors have different predictive values. The majority of factors were more valuable for prognosis of heart attack, but not for stroke.


2020 ◽  
Author(s):  
Li Wang ◽  
Zhiqiang Zou ◽  
Kun Ding ◽  
Chunguo Hou ◽  
Song Qin

Abstract Background: Severe fever with thrombocytopenia syndrome (SFTS) is a severe systemic virus infectious disease usually having multi-organ dysfunction which resembles sepsis. Methods: Data of 321 patients with laboratory-confirmed SFTS from May 2013 to July 2017 were retrospectively analyzed. Demographic and clinical characteristics, calculated quick sequential organ failure assessment (qSOFA) score and systemic inflammatory response syndrome (SIRS) criteria for survivors and nonsurvivors were compared. Independent risk factors associated with in-hospital mortality were obtained using multivariable logistic regression analysis. Risk score models containing different risk factors for mortality in stratified patients were established whose predictive values were evaluated using the area under ROC curve (AUC). Results: Of 321 patients, 87 died (27.1%). Age ( p <0.001) and percentage numbers of patients with qSOFA≥2 and SIRS≥2 ( p <0.0001) were profoundly greater in nonsurvivors than in survivors. Age, qSOFA, SIRS score and aspartate aminotransferase (AST) were independent risk factors for mortality for all patients. And qSOFA score was the only common risk factor in all patients, those age≥60 years and those enrolled in the intensive care unit (ICU). A risk score model containing all these risk factors (Model1) has high predictive value for in-hospital mortality in these three groups with AUCs (95% CI): 0.919 (0.883-0.946), 0.929 (0.862-0.944) and 0.815 (0.710-0.894), respectively. A model only including age and qSOFA also has high predictive value for mortality in these groups with AUCs (95% CI): 0.872 (0.830-0.906), 0.885(0.801-0.900) and 0.865 (0.767-0.932), respectively. Conclusions: Risk models containing qSOFA have high predictive validity for SFTS mortality.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Giselle Sarganas ◽  
Angelika Schaffrath Rosario ◽  
Claudia Niessner ◽  
Alexander Woll ◽  
Hannelore K. Neuhauser

Blood pressure (BP) tracking from childhood to adulthood has two aspects: the ranking stability relative to others over time and the prediction of future values. This study investigates BP tracking in children and adolescents in Germany in the context of hypertension risk factors. BP was measured and analyzed in 2542 participants of the German Health Examination Survey for Children and Adolescents (t02003-2006; 3 to 17-year olds) and of a six year follow-up “Motorik Modul” (t12009-2012; 9 to 24-year olds). BP tracking coefficients were calculated from Spearman’s rank-order correlations. Predictive values and logistic regression models were used to forecast t1-BP above the hypertension threshold from t0-BP as well as from baseline and follow-up hypertension risk factors. BP tracking was moderate (0.33-0.50 for SBP and 0.19-0.39 for DBP) with no statistically significant differences between sex and age groups. Baseline hypertensive BP was the strongest independent predictor of hypertensive BP at follow-up (OR 4.3 and 3.4 for age groups 3-10 and 11-17 years) after adjusting for sex, BMI trajectories, birthweight, parental hypertension, and age-group dependent-sports/physical activity. However, the positive predictive value of baseline hypertensive BP for hypertensive BP at follow-up in 3- to 10-year olds was only 39% (34% in 11- to 17-year olds) and increased only moderately in the presence of additional risk factors. Our analysis with population-based data from Germany shows that BP in children and adolescents tracks only moderately over six years. BP in childhood is the strongest independent predictor of future BP but its predictive value is limited.


2020 ◽  
Author(s):  
Li Wang ◽  
Zhiqiang Zou ◽  
Kun Ding ◽  
Chunguo Hou

Abstract Background: Severe fever with thrombocytopenia syndrome (SFTS) is a severe systemic virus infectious disease usually having multi-organ dysfunction which resembles sepsis.Methods: Data of 321 patients with laboratory-confirmed SFTS from May 2013 to July 2017 were retrospectively analyzed. Demographic and clinical characteristics, calculated quick sequential organ failure assessment (qSOFA) score and systemic inflammatory response syndrome (SIRS) criteria for survivors and nonsurvivors were compared. Independent risk factors associated with in-hospital mortality were obtained using multivariable logistic regression analysis. Risk score models containing different risk factors for mortality in stratified patients were established whose predictive values were evaluated using the area under ROC curve (AUC).Results: Of 321 patients, 87 died (27.1%). Age (p<0.001) and percentage numbers of patients with qSOFA≥2 and SIRS≥2 (p<0.0001) were profoundly greater in nonsurvivors than in survivors. Age, qSOFA, SIRS score and aspartate aminotransferase (AST) were independent risk factors for mortality for all patients. And qSOFA score was the only common risk factor in all patients, those age≥60 years and those enrolled in the intensive care unit (ICU). A risk score model containing all these risk factors (Model1) has high predictive value for in-hospital mortality in these three groups with AUCs (95% CI): 0.919 (0.883-0.946), 0.929 (0.862-0.944) and 0.815 (0.710-0.894), respectively. A model only including age and qSOFA also has high predictive value for mortality in these groups with AUCs (95% CI): 0.872 (0.830-0.906), 0.885(0.801-0.900) and 0.865 (0.767-0.932), respectively.Conclusions: Risk models containing qSOFA have high predictive validity for SFTS mortality.


Author(s):  
Valerie C Gobao ◽  
Mostafa Alfishawy ◽  
Clair Smith ◽  
Karin E Byers ◽  
Mohamed Yassin ◽  
...  

Abstract Background Staphylococcus aureus is the most common cause of native septic arthritis. Few studies have characterized this disease during the U.S. opioid epidemic. The role of MRSA nasal screening in this disease has not been elucidated. We sought to identify risk factors and outcomes for S. aureus native septic arthritis and to evaluate MRSA screening in this disease. Methods A retrospective cohort study of native septic arthritis patients (2012-2016) was performed. Demographics, risk factors, and outcomes were compared between Staphylococcus aureus and other native septic arthritis infections. Sensitivity, specificity, and predictive values of MRSA screening were assessed. Results 215 cases of native septic arthritis were included. S. aureus was cultured in 64% (138/215). MRSA was cultured in 23% (50/215). S. aureus was associated with injection drug use (OR: 4.33, CI: 1.74 to 10.81, p=0.002) and switching antibiotics (OR: 3.92, CI: 1.01 to 21.38, p=0.032). For every ten-year increase in age, odds of S. aureus decreased (OR: 0.72, CI: 0.60 to 0.87, p=0.001). For one unit increases in CCMI, odds of S. aureus decreased (OR: 0.82 CI: 0.73 to 0.91, p=0.0004). MRSA screening during admission demonstrated sensitivity of 0.59, specificity of 0.96, positive predictive value of 0.85, and negative predictive value of 0.84 for MRSA native septic arthritis. Conclusions The opioid epidemic may be contributing to a demographic shift in native septic arthritis to younger, healthier individuals. S. aureus native septic arthritis has unique risks, including injection drug use. MRSA screening may be useful to rule in MRSA native septic arthritis.


Author(s):  
Ying Zhou ◽  
Zhen Yang ◽  
Yanan Guo ◽  
Shuang Geng ◽  
Shan Gao ◽  
...  

AbstractBackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) broke out in Wuhan, Hubei, China. This study sought to elucidate a novel predictor of disease severity in patients with coronavirus disease-19 (COVID-19) cased by SARS-CoV-2.MethodsPatients enrolled in this study were all hospitalized with COVID-19 in the Central Hospital of Wuhan, China. Clinical features, chronic comorbidities, demographic data, and laboratory and radiological data were reviewed. The outcomes of patients with severe pneumonia and those with non-severe pneumonia were compared using the Statistical Package for the Social Sciences (IBM Corp., Armonk, NY, USA) to explore clinical characteristics and risk factors. The receiver operating characteristic curve was used to screen optimal predictors from the risk factors and the predictive power was verified by internal validation.ResultsA total of 377 patients diagnosed with COVID-19 were enrolled in this study, including 117 with severe pneumonia and 260 with non-severe pneumonia. The independent risk factors for severe pneumonia were age [odds ratio (OR): 1.059, 95% confidence interval (CI): 1.036–1.082; p < 0.001], N/L (OR: 1.322, 95% CI: 1.180–1.481; p < 0.001), CRP (OR: 1.231, 95% CI: 1.129–1.341; p = 0.002), and D-dimer (OR: 1.059, 95% CI: 1.013–1.107; p = 0.011). We identified a product of N/L*CRP*D-dimer as having an important predictive value for the severity of COVID-19. The cutoff value was 5.32. The negative predictive value of less than 5.32 for the N/L*CRP*D-dimer was 93.75%, while the positive predictive value was 46.03% in the test sets. The sensitivity and specificity were 89.47% and 67.42%. In the training sets, the negative and positive predictive values were 93.80% and 41.32%, respectively, with a specificity of 70.76% and a sensitivity of 89.87%.ConclusionsA product of N/L*CRP*D-dimer may be an important predictor of disease severity in patients with COVID-19.


2020 ◽  
Author(s):  
Masayuki Hirose ◽  
Daisuke Kasugai ◽  
Kousuke Tajima ◽  
Hiroshi Takahashi ◽  
Shigeki Yamada ◽  
...  

Abstract Aim: Repeated suicide attempts through intentional overdose are not infrequent, but little is known about the risk factors for intentional overdose. We aimed to investigate risk factors for the recurrence of intentional overdose within 1 year of discharge and to develop an index that predicts recurrence.Methods: This retrospective observational study included 419 patients admitted to our hospital between 2011 and 2018 because of an intentional overdose. Of them, 43 (10.0%) repeated an overdose within 1 year of discharge. The risk factors with the highest odds ratios in multivariate logistic regression analysis were used to develop an index Recurrence of Overdose Suicide Attempt. The predictive value of this index for recurrence was compared with that of the existing SAD PERSONS scale.Results: The following variables were significantly associated with recurrence and were included in the index: anxiety and/or insomnia at discharge; use of five or more psychotropic drugs; a neurotic, stress-related, or somatoform disorder; and female sex (odds ratios: 4.24; 5.52; 2.41; and 3.41, respectively). The newly developed index was a significantly better predictor of recurrence than the SAD PERSONS scale (area under the receiver operating characteristics curve, 0.797 vs. 0.668; p = 0.007). Sensitivity, specificity, and positive and negative predictive values for Recurrence of Overdose Suicide Attempt > 4 points (out of 6) were 72.1%, 75.8%, 25.4%, and 96.0%, respectively.Conclusion: The novel index can predict the recurrence of intentional overdose with a good negative predictive value and may therefore be a useful screening tool for this high-risk population.


2019 ◽  
Author(s):  
Kai Xiang Lim ◽  
Frühling Rijsdijk ◽  
Saskia P. Hagenaars ◽  
Adam Socrates ◽  
Shing Wan Choi ◽  
...  

AbstractBackgroundMultiple individual vulnerabilities and traits are phenotypically associated with suicidal and non-suicidal self-harm. However, associations between these risk factors and self-harm are subject to confounding. We implemented genetically informed methods to better identify individual risk factors for self-harm.MethodsUsing genotype data and online Mental Health Questionnaire responses in the UK Biobank sample (N = 125,925), polygenic risk scores (PRS) were generated to index 24 plausible individual risk factors for self-harm in the following domains: mental health vulnerabilities, substance use phenotypes, cognitive traits, personality traits and physical traits. PRS were entered as predictors in binomial regression models to predict self-harm. Multinomial regressions were used to model suicidal and non-suicidal self-harm. To further probe the causal nature of these relationships, two-sample Mendelian Randomisation (MR) analyses were conducted for significant risk factors identified in PRS analyses.OutcomesSelf-harm was predicted by PRS indexing six individual risk factors, which are major depressive disorder (MDD), attention deficit/hyperactivity disorder (ADHD), bipolar disorder, schizophrenia, alcohol dependence disorder (ALC) and lifetime cannabis use. Effect sizes ranged from β = 0.044 (95% CI: 0.016 to 0.152) for PRS for lifetime cannabis use, to β = 0.179 (95% CI: 0.152 to 0.207) for PRS for MDD. No systematic distinctions emerged between suicidal and non-suicidal self-harm. In follow-up MR analyses, MDD, ADHD and schizophrenia emerged as plausible causal risk factors for self-harm.InterpretationAmong a range of potential risk factors leading to self-harm, core predictors were found among psychiatric disorders. In addition to MDD, liabilities for schizophrenia and ADHD increased the risk for self-harm. Detection and treatment of core symptoms of these conditions, such as psychotic or impulsivity symptoms, may benefit self-harming patients.FundingLim is funded by King’s International Postgraduate Research Scholarship. Dr Pingault is funded by grant MQ16IP16 from MQ: Transforming Mental Health. Dr Coleman is supported by the UK National Institute of Health Research Maudsley Biomedical Research Centre. MRC grant MR/N015746/1 to CML and PFO’R. Dr Hagenaars is funded by the Medical Research Council (MR/S0151132). Kylie P. Glanville is funded by the UK Medical Research Council (PhD studentship; grant MR/N015746/1). This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.Research in ContextEvidence before this studyA search was conducted on PubMed for literature from inception until 1st May 2019 using terms related to suicidal self-harm (SSH) and non-suicidal self-harm (NSSH), as well as polygenic risk scores (PRS), (“self-harm”[All Fields] OR “self-injurious”[All Fields] OR “self-mutilation”[All Fields] OR “suicide”[All Fields]) AND (“polygenic”[All Fields] OR “multifactorial inheritance”[All Fields]). Similar search was done for Mendelian Randomisation (MR), replacing “multifactorial inheritance” and “polygenic” with “Mendelian Randomisation/Randomization”. Evidence was included only if the study had used PRS or MR method to predict self-harm phenotypes using risk factors of self-harm. Ten papers for PRS and no paper for MR were identified.There were mixed results for PRS studies. PRS for MDD predicted SSH in two studies but not in another two studies. PRS for depressive symptoms predicted SSH but not NSSH. PRS for schizophrenia predicted SSH in one but not in another two studies. PRS for bipolar disorder predicted SSH in one study but did not predict SSH nor NSSH in another two studies.Added value of this studyBy using a large population-based sample, we systematically studied individual vulnerabilities and traits that can potentially lead to self-harm, including mental health vulnerabilities, substance use phenotypes, cognitive traits, personality traits and physical traits, summing up to 24 PRS as genetic proxies for 24 risk factors. We conducted MR to strengthen causal inference. We further distinguished non-suicidal self-harm (NSSH) and suicidal self-harm (SSH).Apart from PRS for schizophrenia, MDD and bipolar disorder, novel PRS were also identified to be associated with self-harm, which are PRS for attention-deficit hyperactivity disorder (ADHD), cannabis use and alcohol dependence. A larger sample size allowed us to confirm positive findings from the previously mixed literature regarding the associations between PRS for MDD, bipolar disorder, and schizophrenia with self-harm. Multivariate analyses and MR analyses strengthened the evidence implicating MDD, ADHD and schizophrenia as plausible causal risk factors for self-harm.Implications of all the available evidenceAmong the 24 risk factors considered, plausible causal risk factors for self-harm were identified among psychiatric conditions. Using PRS and MR methods and a number of complementary analyses provided higher confidence to infer causality and nuanced insights into the aetiology of self-harm. From a clinical perspective, detection and treatment of core symptoms of these conditions, such as psychotic or impulsivity symptoms, may prevent individuals from self-harming.


Author(s):  
Ying Zhou ◽  
Zhen Yang ◽  
Yanan Guo ◽  
Shuang Geng ◽  
Shan Gao ◽  
...  

Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) broke out in Wuhan, Hubei, China. This study sought to elucidate a novel predictor of disease severity in patients with coronavirus disease-19 (COVID-19) cased by SARS-CoV-2.Methods Patients enrolled in this study were all hospitalized with COVID-19 in the Central Hospital of Wuhan, China. Clinical features, chronic comorbidities, demographic data, and laboratory and radiological data were reviewed. The outcomes of patients with severe pneumonia and those with non-severe pneumonia were compared to explore risk factors. The receiver operating characteristic curve was used to screen optimal predictors from the risk factors and the predictive power was verified by internal validation.Results A total of 377 patients diagnosed with COVID-19 were enrolled in this study, including 117 with severe pneumonia and 260 with non-severe pneumonia. The independent risk factors for severe pneumonia were age, N/L, CRP and D-dimer. We identified a product of N/L*CRP*D-dimer as having an important predictive value for the severity of COVID-19. The cutoff value was 5.32. The negative predictive value of less than 5.32 for the N/L*CRP*D-dimer was 93.75%, while the positive predictive value was 46.03% in the test sets. In the training sets, the negative and positive predictive values were 93.80% and 41.32%.Conclusions A product of N/L*CRP*D-dimer may be an important predictor of disease severity in patients with COVID-19.


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