The First Step in the Validation of a new Screen for Violence Risk in Acute Psychiatry: The Inpatient Context

2010 ◽  
Vol 26 (2) ◽  
pp. 92-99 ◽  
Author(s):  
P. Hartvig ◽  
J.O. Roaldset ◽  
T.A. Moger ◽  
B. Østberg ◽  
S. Bjørkly
Keyword(s):  
Risk Assessment ◽  
Area Under The Curve ◽  
Assessment Tools ◽  
Violence Risk ◽  
Operating Characteristics ◽  
Predictive Values ◽  
General Psychiatry ◽  
Psychiatric Units ◽  
One Year ◽  
Sensitivity Specificity

AbstractBackgroundInstruments for evaluating the risk of violence towards others have mostly been developed for assessment of risk for recidivism into violent crime in forensic psychiatry. In general psychiatry there is a considerable need for specialised, brief and structured assessment tools to inform risk decisions.MethodThe study aimed to validate a brief structured clinical risk assessment screen of inpatient violence (V-RISK-10), a 10-item structured clinical checklist with a good vignette-based interrater reliability (ICC=0.87). In this study it was used for risk assessment of a one-year sample of patients (N = 1.017) admitted to two acute psychiatric units. Risk assessments at admission were compared to prospective records of aggressive and violent acts during the hospital stay.ResultsResults showed a base rate for aggression of 9%. The predictive validity of the V-RISK-10 was estimated by Receiver Operating Characteristics (ROC). It yielded an area under the curve (AUC) of 0.83, with sensitivity/specificity of 0.81/0.73 and corresponding positive and negative predictive values (PPV/NPV) of 0.24/0.97. The screen was easy-to-use and showed a short completion time.ConclusionDespite promising results further validation studies are required before the V-RISK-10 is adopted into routine clinical practise.

scholarly journals Trabecular bone score improves fracture risk assessment in glucocorticoid-induced osteoporosis

Rheumatology ◽  
2019 ◽  
Vol 59 (7) ◽  
pp. 1574-1580 ◽  
Author(s):  
Helena Florez ◽  
José Hernández-Rodríguez ◽  
Africa Muxi ◽  
Josep Lluis Carrasco ◽  
Sergio Prieto-González ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Fracture Risk ◽  
Trabecular Bone ◽  
Fragility Fracture ◽  
Trabecular Bone Score ◽  
Area Under The Curve ◽  
Fracture Risk Assessment ◽  
Cross Sectional ◽  
Predictive Values ◽  
Sensitivity Specificity

Abstract Objective To analyse the clinical utility of trabecular bone score (TBS) evaluation for fracture risk assessment in glucocorticoid (GC)-treated patients compared with BMD assessment. Methods One hundred and twenty-seven patients on GC treatment were included [mean age 62 (18) years, 63% women] in this cross-sectional study. The medical history, anthropometric data, lumbar and femoral BMD (DXA) [considering osteoporosis (OP): T-score ⩽−2.5], TBS (considering degraded microarchitecture: <1.230) and dorsolumbar X-ray [to assess vertebral fractures (VF)] were evaluated. BMD and TBS sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were evaluated to determine the diagnostic accuracy of the two methods. Results All patients were receiving GC treatment for autoimmune diseases during 47.7 (68.9) months at a mean daily dose of 14.5 mg; 17% had VF, 28% any type of fragility fracture (VF + non-VF), 29% OP and 52% degraded microarchitecture. Degraded microarchitecture was significantly more frequent than densitometric OP in patients with VF (76% vs 38%) and with any fragility fracture (69% vs 36%). For VF, TBS and BMD sensitivity, specificity, PPV, and NPV were 0.76, 0.53, 0.25 and 0.92, and 0.38, 0.72, 0.22 and 0.85, respectively. Specificity increased to 0.89 for VF and 0.9 for any fragility fracture on combining BMD+TBS. TBS had better ability than BMD to discriminate between patients with fracture, especially VF (area under the curve = 0.73). Conclusion TBS seems to have greater discriminative power than BMD for fracture risk assessment in GC-treated patients, confirming the utility of this method as a complementary tool in the diagnosis of GC-induced OP.

Discriminating Malignancy in Thyroid Nodules: The Nomogram Versus the Kwak and ACR TI-RADS

2020 ◽  
Vol 163 (6) ◽  
pp. 1156-1165
Author(s):  
Juan Xiao ◽  
Qiang Xiao ◽  
Wei Cong ◽  
Ting Li ◽  
Shouluan Ding ◽  
...  
Keyword(s):  
Thyroid Nodules ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Study ◽  
Diagnostic Efficiency ◽  
Training Set ◽  
Multivariable Logistic Regression Model ◽  
Predictive Values ◽  
Validation Set ◽  
Sensitivity Specificity

Objective To develop an easy-to-use nomogram for discrimination of malignant thyroid nodules and to compare diagnostic efficiency with the Kwak and American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS). Study Design Retrospective diagnostic study. Setting The Second Hospital of Shandong University. Subjects and Methods From March 2017 to April 2019, 792 patients with 1940 thyroid nodules were included into the training set; from May 2019 to December 2019, 174 patients with 389 nodules were included into the validation set. Multivariable logistic regression model was used to develop a nomogram for discriminating malignant nodules. To compare the diagnostic performance of the nomogram with the Kwak and ACR TI-RADS, the area under the receiver operating characteristic curve, sensitivity, specificity, and positive and negative predictive values were calculated. Results The nomogram consisted of 7 factors: composition, orientation, echogenicity, border, margin, extrathyroidal extension, and calcification. In the training set, for all nodules, the area under the curve (AUC) for the nomogram was 0.844, which was higher than the Kwak TI-RADS (0.826, P = .008) and the ACR TI-RADS (0.810, P < .001). For the 822 nodules >1 cm, the AUC of the nomogram was 0.891, which was higher than the Kwak TI-RADS (0.852, P < .001) and the ACR TI-RADS (0.853, P < .001). In the validation set, the AUC of the nomogram was also higher than the Kwak and ACR TI-RADS ( P < .05), each in the whole series and separately for nodules >1 or ≤1 cm. Conclusions When compared with the Kwak and ACR TI-RADS, the nomogram had a better performance in discriminating malignant thyroid nodules.

scholarly journals New screening approach to detecting congenital syphilis in China: a retrospective cohort study

2020 ◽  
pp. archdischild-2020-320549
Author(s):  
Fang Hu ◽  
Shuai-Jun Guo ◽  
Jian-Jun Lu ◽  
Ning-Xuan Hua ◽  
Yan-Yan Song ◽  
...  
Keyword(s):  
Predictive Value ◽  
Congenital Syphilis ◽  
Area Under The Curve ◽  
Diagnostic Tools ◽  
Operating Characteristics ◽  
Loss To Follow Up ◽  
Sensitivity Specificity ◽  
Mother To Child ◽  
Rule Out

BackgroundDiagnosis of congenital syphilis (CS) is not straightforward and can be challenging. This study aimed to evaluate the validity of an algorithm using timing of maternal antisyphilis treatment and titres of non-treponemal antibody as predictors of CS.MethodsConfirmed CS cases and those where CS was excluded were obtained from the Guangzhou Prevention of Mother-to-Child Transmission of syphilis programme between 2011 and 2019. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using receiver operating characteristics (ROC) in two situations: (1) receiving antisyphilis treatment or no-treatment during pregnancy and (2) initiating treatment before 28 gestational weeks (GWs), initiating after 28 GWs or receiving no treatment for syphilis seropositive women.ResultsAmong 1558 syphilis-exposed children, 39 had confirmed CS. Area under the curve, sensitivity and specificity of maternal non-treponemal titres before treatment and treatment during pregnancy were 0.80, 76.9%, 78.7% and 0.79, 69.2%, 88.7%, respectively, for children with CS. For the algorithm, ROC results showed that PPV and NPV for predicting CS were 37.3% and 96.4% (non-treponemal titres cut-off value 1:8 and no antisyphilis treatment), 9.4% and 100% (non-treponemal titres cut-off value 1:16 and treatment after 28 GWs), 4.2% and 99.5% (non-treponemal titres cut-off value 1:32 and treatment before 28 GWs), respectively.ConclusionsAn algorithm using maternal non-treponemal titres and timing of treatment during pregnancy could be an effective strategy to diagnose or rule out CS, especially when the rate of loss to follow-up is high or there are no straightforward diagnostic tools.

scholarly journals Value and Diagnostic Efficacy of Fetal Morphology Assessment Using Ultrasound in A Poor-Resource Setting

Diagnostics ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 109 ◽  
Author(s):  
Ukweh ◽  
Ugbem ◽  
Okeke ◽  
Ekpo
Keyword(s):  
Predictive Value ◽  
Performance Metrics ◽  
Area Under The Curve ◽  
Youden Index ◽  
Likelihood Ratios ◽  
Diagnostic Efficacy ◽  
Predictive Values ◽  
Resource Setting ◽  
Post Test ◽  
Sensitivity Specificity

Background: Ultrasound is operator-dependent, and its value and efficacy in fetal morphology assessment in a low-resource setting is poorly understood. We assessed the value and efficacy of fetal morphology ultrasound assessment in a Nigerian setting. Materials and Methods: We surveyed fetal morphology ultrasound performed across five facilities and followed-up each fetus to ascertain the outcome. Fetuses were surveyed in the second trimester (18th–22nd weeks) using the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) guideline. Clinical and surgical reports were used as references to assess the diagnostic efficacy of ultrasound in livebirths, and autopsy reports to confirm anomalies in terminated pregnancies, spontaneous abortions, intrauterine fetal deaths, and still births. We calculated sensitivity, specificity, positive and negative predictive values, Area under the curve (AUC), Youden index, likelihood ratios, and post-test probabilities. Results: In total, 6520 fetuses of women aged 15–46 years (mean = 31.7 years) were surveyed. The overall sensitivity, specificity, and AUC were 77.1 (95% CI: 68–84.6), 99.5 (95% CI: 99.3–99.7), and 88.3 (95% CI: 83.7–92.2), respectively. Other performance metrics were: positive predictive value, 72.4 (95% CI: 64.7–79.0), negative predictive value, 99.6 (95% CI: 99.5–99.7), and Youden index (77.1%). Abnormality prevalence was 1.67% (95% CI: 1.37–2.01), and the positive and negative likelihood ratios were 254 (95% CI: 107.7–221.4) and 0.23 (95% CI: 0.16–0.33), respectively. The post-test probability for positive test was 72% (95% CI: 65–79). Conclusion: Fetal morphology assessment is valuable in a poor economics setting, however, the variation in the diagnostic efficacy across facilities and the limitations associated with the detection of circulatory system anomalies need to be addressed.

scholarly journals 006 Can seizure-related heart rate differentiate epileptic seizures from psychogenic non-epileptic seizures?

2019 ◽  
Vol 90 (e7) ◽  
pp. A2.3-A3
Author(s):  
Hue Mun Au Yong ◽  
Erica Minato ◽  
Eldho Paul ◽  
Udaya Seneviratne
Keyword(s):  
Heart Rate ◽  
Area Under The Curve ◽  
Epileptic Seizures ◽  
Roc Curve Analysis ◽  
Predictive Values ◽  
Minute Post ◽  
Poor Differentiation ◽  
Good Differentiation ◽  
Sensitivity Specificity ◽  
Video Eeg

IntroductionThis study aims to (i)evaluate the diagnostic sensitivity, specificity and predictive values of seizure-related heart rate (HR) in differentiating epileptic seizures(ES) from psychogenic non-epileptic seizures(PNES), (ii)define the most useful point of HR measurement: pre-ictal, ictal-onset, maximal-ictal or post-ictal, and (iii)define the HR cut-off points to differentiate ES from PNES.MethodsAll video EEG(VEEG) at Monash Health from May 2009 to November 2015 were retrospectively reviewed. Baseline(during wakefulness), one-minute pre-ictal, ictal-onset, maximal-ictal and one-minute post-ictal HR were measured for each ES and PNES event. Events less than ten seconds or with uninterpretable ECG due to artefacts were excluded. ROC curve analysis was performed to study the diagnostic accuracy reflected by area under the curve(AUC). The AUC was interpreted as follows; ≤0.5, differentiation of PNES from ES no better than chance; 0.80–0.89, good differentiation; and 0.9–1, excellent differentiation.ResultsVEEG of 341 ES and 265 PNES from 130 patients were analysed. The AUC for pre-ictal, ictal-onset, maximal-ictal and post-ictal HR were found to have poor differentiation between ES and PNES. Comparing PNES and bilateral tonic-clonic ES, AUC for absolute maximal-ictal HR was 0.84(CI 0.73–0.95) and for absolute post-ictal HR was 0.90(CI 0.81–1.00). Using Youden’s index, to diagnose tonic-clonic ES, the optimal cut-off point for absolute maximal-ictal HR was 114bpm (sensitivity 84%;specificity 82%;PPV 26.7%,NPV 98.5%) and for absolute post-ictal HR was 90bpm(sensitivity 91%;specificity 82%;PPV 30.3%;NPV 99.1%).ConclusionsThese findings suggest that seizure-related HR increase is useful in differentiating bilateral tonic-clonic ES from PNES. Based on the AUC, the best diagnostic measureme.

Factors Predicting Desistance From Reoffending: A Validation Study of the SAPROF in Sexual Offenders

2016 ◽  
Vol 62 (3) ◽  
pp. 697-716 ◽  
Author(s):  
Dahlnym Yoon ◽  
Daniel Turner ◽  
Verena Klein ◽  
Martin Rettenberger ◽  
Reinhard Eher ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Sexual Offenders ◽  
Interrater Reliability ◽  
Predictive Accuracy ◽  
Negative Relationship ◽  
Incremental Validity ◽  
Assessment Tools ◽  
Violence Risk ◽  
Limited Extent ◽  
Risk Assessment Tools

The present study aims at validating the German version of the Structured Assessment of PROtective Factors (SAPROF) for violence risk in a representative sample of incarcerated adult male sexual offenders. Sexual offenders ( n = 450) were rated retrospectively with the SAPROF using the database of the Federal Evaluation Centre for Violent and Sexual Offenders (FECVSO) in the Austrian Prison System. Interrater reliability and predictive validity of the SAPROF scores concerning desistance from recidivism were calculated. Concurrent and incremental validity were tested using the combination of the SAPROF and the Sexual Violence Risk–20 (SVR-20). Interrater reliability was moderate to excellent, and predictive accuracy for various types of recidivism was rather small to moderate. There was a clear negative relationship between the SAPROF and the SVR-20 risk factors. Whereas the SAPROF revealed itself as a significant predictor for various recidivism categories, it did not add any predictive value beyond the SVR-20. Although the SAPROF itself can predict desistance from recidivism, it seems to contribute to the risk assessment in convicted sexual offenders only to a limited extent, once customary risk assessment tools have been applied. Implications for clinical use and further studies are discussed.

scholarly journals Assessing Protective Factors for Adolescent Offending: A Conceptually Informed Examination of the SAVRY and YLS/CMI

Assessment ◽  
2018 ◽  
Vol 27 (5) ◽  
pp. 959-975 ◽  
Author(s):  
Jodi L. Viljoen ◽  
Aisha K. Bhanwer ◽  
Catherine S. Shaffer ◽  
Kevin S. Douglas
Keyword(s):  
Protective Factors ◽  
Area Under The Curve ◽  
Assessment Tools ◽  
Violence Risk ◽  
Protective Effects ◽  
Adolescent Risk ◽  
Risk Assessment Tools ◽  
Relevant Role ◽  
Research Assistants

Although the Structured Assessment of Violence Risk in Youth (SAVRY) and the Youth Level of Service/Case Management Inventory (YLS/CMI) are among the most widely used adolescent risk assessment tools, they conceptualize and measure strengths differently. As such, in this study, we compared the predictive validity of SAVRY Protective Total and YLS/CMI Strength Total, and tested conceptual models of how these measures operate (i.e., risk vs. protective effects, direct vs. buffering effects, causal models). Research assistants conducted 624 risk assessments with 156 youth on probation. They rated protective factors at baseline, and again at 3-, 6-, 9-, and 12-month follow-up periods. The SAVRY Protective Total and YLS/CMI Strength Total inversely predicted any charges in the subsequent 2 years (area under the curve scores = 0.61 and 0.60, respectively, p < .05). Furthermore, when adolescents’ protective total scores increased, their self-reported violence decreased, thus providing evidence that these factors might play a causally relevant role in reducing violence. However, protective factors did not provide incremental validity over risk factors. In addition, because these measures are brief and use a dichotomous rating system, they primarily captured deficits in protective factors (i.e., low scores). This suggests a need for more comprehensive measures.

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