CODLEMONE/e8e10-12oh/CODLURE/9-Oxo-10,12-octadecadienoic acid/Feroflon SR-2/trans-8,trans-10-dodecadienol/10,12-Octadecadienoic acid, 9-oxo-, (10E,12E)-/(10E,12E)-9-Oxo-10,12-octadecadienoic acid/checkmatecm/trans-8,10-dodecadien-1,ol/9-KODE/codlelure/trans-8,10-dodecadienol/Feroflor SR-2/pheroconcm
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Background and aims
Compulsive sexual behavior disorder (CSBD) will be included in ICD-11 as an impulse-control disorder. CSBD also shares clinical features with obsessive-compulsive spectrum disorders (OCSDs) and behavioral addictions. There has been relatively little systematic investigation of CSBD in obsessive-compulsive disorder (OCD), the paradigmatic compulsive disorder. We aimed to determine prevalence of CSBD in OCD, and its associated sociodemographic and clinical features, including associated comorbidity, to learn more about the nature of CSBD.
Adult outpatients with current OCD (N = 539) participated in this study. The Structured Clinical Interview for OCSDs was used to diagnose OCSDs (Tourette’s syndrome, compulsive shopping, pathological gambling, kleptomania, pyromania, intermittent explosive disorder, self-injurious behavior, and CSBD). Prevalence rates of OCSDs in male versus female patients as well as comorbid disorders in OCD patients with and without CSBD were compared.
Lifetime prevalence of CSBD was 5.6% in patients with current OCD and significantly higher in men than women. OCD patients with and without CSBD were similar in terms of age, age of onset of OCD, present OCD illness severity, as well as educational background. Lifetime prevalence rates of several mood, obsessive-compulsive, and impulse-control disorders were considerably elevated in patients with lifetime CSBD.
Discussion and conclusions
A substantive number of OCD patients suffered from CSBD. CSBD in OCD was more likely comorbid with other mood, obsessive-compulsive, and impulse-control disorders, but not with disorders due to substance use or addictive behaviors. This finding supports conceptualization of CSBD as a compulsive-impulsive disorder.
hypersexuality, hypersexual disorder, behavioral addictions, compulsivity, impulsivity, compulsive sexual behavior disorder
Compulsive sexual behavior disorder in obsessive-compulsive disorder: Prevalence and associated comorbidity
Johannes Fuss,1,* Peer Briken,1 Dan J. Stein,2,3 and Christine Lochner2,3
This study aimed to analyze data from the Surveillance, Epidemiology, and End Results (SEER) program to identify patients with colorectal cancer (CRC) who had specific insurance details and the effects of stage at diagnosis, definitive treatment, and survival outcome with insurance status.
Between 2007 and 2009, SEER database analysis identified 54,232 patients with CRC. Logistic models examined the associations between insurance status and disease stage and definitive treatment. Kaplan-Meier analysis, the Cox model, and the Fine and Gray model were used to compare the tumor cause-specific survival (TCSS) for patients with different insurance status.
Insured patients were more likely to have earlier tumor stage at diagnosis when compared with patients receiving Medicaid (adjusted OR, 1.318; 95% CI, 1.249-1.391; P<0.001) and when compared with uninsured patients (adjusted OR, 1.479; 95% CI, 1.352-1.618; P<0.001). Insured patients were significantly more likely to undergo definitive treatment when compared with patients receiving Medicaid (adjusted OR, 0.591; 95% CI, 0.470-0.742; P<0.001) and compared with patients who were uninsured (adjusted OR, 0.404; 95% CI, 0.282-0.579; P<0.001). Insured patients had a significantly increased TCSS when compared with patients receiving Medicaid (HR, 1.298; 95% CI, 1.236-1.363; P<0.001) and compared with patients who were uninsured (HR 1.195, 95% CI, 1.100-1.297; P<0.001). Conclusions Insurance status was a significant factor that determined early diagnosis, definitive treatment, and clinical outcome and was an independent factor for TCSS in patients with CRC.
Colorectal Neoplasms, Insurance Coverage, Neoplasm Staging, Survival Rate, Treatment Outcome
Impact of Insurance Status on Stage, Treatment, and Survival in Patients with Colorectal Cancer: A Population-Based Analysis
Wei Sun,A,B,C,D,* Minghua Cheng,B,C,D,E,* Shaohui Zhuang,C,D,E and Zeting Qiucorresponding authorA,B,E,F
Introduction: Isoniazid (INH) is an essential drug for tuberculosis (TB) treatment. Resistance to INH may increase the likelihood of negative treatment outcome.
Aim: We aimed to determine the impact of INH mono-resistance on TB treatment outcome in the European Union/European Economic Area and to identify risk factors for unsuccessful outcome in cases with INH mono-resistant TB.
Methods: In this observational study, we retrospectively analysed TB cases that were diagnosed in 2002-14 and included in the European Surveillance System (TESSy). Multilevel logistic regression models were applied to identify risk factors and correct for clustering of cases within countries.
Results: A total of 187,370 susceptible and 7,578 INH mono-resistant TB cases from 24 countries were included in the outcome analysis. Treatment was successful in 74.0% of INH mono-resistant and 77.4% of susceptible TB cases. In the final model, treatment success was lower among INH mono-resistant cases (Odds ratio (OR): 0.7; 95% confidence interval (CI): 0.6-0.9; adjusted absolute difference in treatment success: 5.3%). Among INH mono-resistant TB cases, unsuccessful treatment outcome was associated with age above median (OR: 1.3; 95% CI: 1.2-1.5), male sex (OR: 1.3; 95% CI: 1.1-1.4), positive smear microscopy (OR: 1.3; 95% CI: 1.1-1.4), positive HIV status (OR: 3.3; 95% CI: 1.6-6.5) and a prior TB history (OR: 1.8; 95% CI: 1.5-2.2).
Conclusions: This study provides evidence for an association between INH mono-resistance and a lower likelihood of TB treatment success. Increased attention should be paid to timely detection and management of INH mono-resistant TB.
tuberculosis, TB, anti-tuberculous treatment, isoniazid mono-resistance, surveillance, epidemiology
Isoniazid (INH) mono-resistance and tuberculosis (TB) treatment success: analysis of European surveillance data, 2002 to 2014
Basel Karo,1,2,3,4 Anke Kohlenberg,4,5 Vahur Hollo,5 Raquel Duarte,6 Lena Fiebig,3,7 Sarah Jackson,8 Cathriona Kearns,9 Csaba Kodmon,5 Maria Korzeniewska-Kosela,10 Dimitrios Papaventsis,11 Ivan Solovic,12 Dick van Soolingen,13 and Marieke J. van der Werf5
2019 Mar 21;