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The incidence and prediction of self-injury among sentenced prisoners.

ABSTRACT: Prevention of self-injurious behaviour is an important priority in correctional settings given higher rates among inmates. Our study estimated the reported incidence of self-injury during the first 180 days in prison and tested potential risk and protective factors using official prison records.We conducted a retrospective cohort study using secondary data for 5154 admissions to the Correctional Service of Canada during 2011. Relative risks were estimated with Poisson regression. Recursive partitioning was used to create a parsimonious model of characteristics of offenders who engage in self-injury.Thirty-six of 5154 (0.7%) offenders engaged in 1 or more incidents of self-injury during their first 180 days of incarceration. Educational and occupational achievement, family history, demographic factors, mental health service use, and results of mental health screening at intake were predictive of self-injury. Recursive partitioning models identified about 23% of inmates who presented with multiple risk factors, and had increased incidence of self-injury. A comparison of a model using information at intake to a model also incorporating events in prison suggested that events in prison added little to the detection of self-injury.Given high rates of most risk factors, screening for self-injury during early incarceration will be overinclusive. However, it may identify a group of inmates with complex needs for whom interdisciplinary responses are needed to address wide-ranging social, family, behavioural, and mental health deficits.

SUBMITTER: Martin MS

PROVIDER: S-EPMC4079137 | biostudies-other | 2014 May

REPOSITORIES: biostudies-other

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The incidence and prediction of self-injury among sentenced prisoners.

Martin Michael S MS Dorken Shannon K SK Colman Ian I McKenzie Kwame K Simpson Alexander I F AI

Canadian journal of psychiatry. Revue canadienne de psychiatrie 20140501 5

<h4>Objective</h4>Prevention of self-injurious behaviour is an important priority in correctional settings given higher rates among inmates. Our study estimated the reported incidence of self-injury during the first 180 days in prison and tested potential risk and protective factors using official prison records.<h4>Methods</h4>We conducted a retrospective cohort study using secondary data for 5154 admissions to the Correctional Service of Canada during 2011. Relative risks were estimated with P ...[more]

PMID: 25007279

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Project description:ImportancePsychological distress is a key component of patient-centered cancer care. While a greater risk of suicide among patients with cancer has been reported, more frequent consequences of distress, including nonfatal self-injury (NFSI), remain unknown.ObjectiveTo examine the risk of NFSI after a cancer diagnosis.Design, setting, and participantsThis population-based retrospective cohort study used linked administrative databases to identify adults diagnosed with cancer between 2007 and 2019 in Ontario, Canada.ExposuresDemographic and clinical factors.Main outcomes and measuresCumulative incidence of NFSI, defined as emergency department presentation of self-injury, was computed, accounting for the competing risk of death from all causes. Factors associated with NFSI were assessed using multivariable Fine and Gray models.ResultsIn total, 806 910 patients met inclusion criteria. The mean (SD) age was 65.7 (14.3) years, and 405 161 patients (50.2%) were men. Overall, 2482 (0.3%) had NFSI and 182 (<0.1%) died by suicide. The 5-year cumulative incidence of NFSI was 0.27% (95% CI, 0.25%-0.28%). After adjusting for key confounders, prior severe psychiatric illness, whether requiring inpatient care (subdistribution hazard ratio [sHR], 12.6; 95% CI, 10.5-15.2) or outpatient care (sHR, 7.5; 95% CI, 6.5-8.8), and prior self-injury (sHR, 6.6; 95% CI, 5.5-8.0) were associated with increased risk of NFSI. Young adults (age 18-39 years) had the highest NFSI rates relative to individuals aged 70 years or older (sHR, 5.4; 95% CI, 4.5-6.5). The magnitude of association between prior inpatient psychiatric illness and NFSI was greatest for young adults (sHR, 17.6; 95% CI, 12.0-25.8). Certain cancer subsites were also associated with increased risk, including head and neck cancer (sHR, 1.5; 95% CI, 1.2-1.9).Conclusions and relevanceIn this study, patients with cancer had a higher incidence of NFSI than suicide after diagnosis. Younger age, history of severe psychiatric illness, and prior self-injury were independently associated with risk of NFSI. These exposures appeared to act synergistically, placing young adults with a prior mental health history at the greatest risk of NFSI. These factors should be used to identify at-risk patients.

Project description:INTRODUCTION: Cardiac surgery is frequently needed in patients with infective endocarditis (IE). Acute kidney injury (AKI) often complicates IE and is associated with poor outcomes. The purpose of the study was to determine the risk factors for post-operative AKI in patients operated on for IE. METHODS: A retrospective, non-interventional study of prospectively collected data (2000-2010) included patients with IE and cardiac surgery with cardio-pulmonary bypass. The primary outcome was post-operative AKI, defined as the development of AKI or progression of AKI based on the acute kidney injury network (AKIN) definition. We used ensemble machine learning ("Super Learning") to develop a predictor of AKI based on potential risk factors, and evaluated its performance using V-fold cross validation. We identified clinically important predictors among a set of risk factors using Targeted Maximum Likelihood Estimation. RESULTS: 202 patients were included, of which 120 (59%) experienced a post-operative AKI. 65 (32.2%) patients presented an AKI before surgery while 91 (45%) presented a progression of AKI in the post-operative period. 20 patients (9.9%) required a renal replacement therapy during the post-operative ICU stay and 30 (14.8%) died during their hospital stay. The following variables were found to be significantly associated with renal function impairment, after adjustment for other risk factors: multiple surgery (OR: 4.16, 95% CI: 2.98-5.80, p<0.001), pre-operative anemia (OR: 1.89, 95% CI: 1.34-2.66, p<0.001), transfusion requirement during surgery (OR: 2.38, 95% CI: 1.55-3.63, p<0.001), and the use of vancomycin (OR: 2.63, 95% CI: 2.07-3.34, p<0.001), aminoglycosides (OR: 1.44, 95% CI: 1.13-1.83, p=0.004) or contrast iodine (OR: 1.70, 95% CI: 1.37-2.12, p<0.001). Post-operative but not pre-operative AKI was associated with hospital mortality. CONCLUSIONS: Post-operative AKI following cardiopulmonary bypass for IE results from additive hits to the kidney. We identified several potentially modifiable risk factors such as treatment with vancomycin or aminoglycosides or pre-operative anemia.

Project description:BackgroundAcute kidney injury (AKI) is a prevalent complication following acute type A aortic dissection (ATAAD) surgery and is closely associated with unfavorable prognostic outcomes. Hence, the development of a robust and efficient diagnostic approach to identify high-risk patients is of paramount importance.MethodsWe conducted a prospective study involving 328 patients who underwent ATAAD surgery at our institution, comprising three distinct cohorts. In addition, 52 patients undergoing alternative cardiopulmonary surgeries and 37 healthy individuals were enrolled as control groups. Employing proteomic analysis, we initially identified plasma proteins potentially linked to AKI occurrence within the plasma proteomic cohort. Subsequent validation was performed in an independent cohort. Utilizing predictors derived from multivariate logistic regression analysis, a nomogram was meticulously formulated and its efficacy was validated in the model construction cohort.ResultsProteomics revealed significant elevation of plasma levels of S100A8/A9, pentraxin 3 (PTX3), and chitinase 3-like 1 (CHI3L1) immediately post-surgery in patients who developed ATAAD surgery-associated AKI (ASA-AKI). Receiver operating characteristic (ROC) curves demonstrated impressive predictive performance of S100A8/A9, PTX3, and CHI3L1 at 0 h post-surgery, yielding area under the curve (AUC) values of 0.823, 0.786, and 0.803, respectively, for ASA-AKI prediction. Furthermore, our findings exhibited positive correlations between plasma levels of S100A8/A9, PTX3, CHI3L1, and urinary neutrophil gelatinase-associated lipocalin (NGAL) at 0 h post-surgery, along with correlations between plasma S100A8/A9, CHI3L1 levels, and the Cleveland Clinic score. A logistic regression model incorporating plasma S100A8/A9, PTX3, CHI3L1 levels, urinary NGAL levels, and the Cleveland Clinic score facilitated the construction of a predictive nomogram for ASA-AKI. This nomogram demonstrated robust discriminative ability, achieving an AUC of 0.963 in the model construction cohort.ConclusionsOur study underscored the augmentation of plasma S100A8/A9, PTX3, and CHI3L1 levels immediately post-surgery in patients developing ASA-AKI. The incorporation of these three biomarkers, in conjunction with the Cleveland Clinic score and NGAL, into a nomogram demonstrated commendable predictive efficacy. This presents a practical tool for identifying patients at an elevated risk of AKI following ATAAD surgery.

Project description:BackgroundThere is growing interest in the design of digital interventions to improve conditions for young people who engage in high-risk behaviors, like nonsuicidal self-injury (NSSI). However, few studies have focused on how young people self-manage NSSI, or their existing, and historic, use of technologies to support their goals related to NSSI behavior change. Such an understanding has the potential to inform the design of digital interventions that meet this population's unique needs.ObjectivesThis study aims to (a) understand the self-management practices of young adults who engage in NSSI, (b) explore how they currently use technologies for self-injury self-management, and (c) identify the ways they can envision an app-based technology supporting their self-management.Methods and materialsTwenty young adults (aged 18-24) with lived experience of NSSI, and who were not currently enrolled in therapy, were recruited from online venues. Participants completed baseline measures to assess mental health and NSSI characteristics, followed by a virtual 1-h semi-structured interview where they were invited to share their experience of self-management, their goals, and their thoughts on supportive technology. Interview scripts were transcribed and analyzed via thematic analysis.ResultsThemes and sub-themes are organized under two broad domain areas: (1) How young adults self-manage NSSI thoughts and behaviors and (2) Opportunities and challenges for digital interventions to assist young adults in their recovery process. We found that young adults had varied experiences with, and goals related to, NSSI. Participants reported a lack of effective strategies to reduce NSSI urges and a desire for an app-based technology to track patterns and deliver personalized suggestions for self-management. Participants reported existing use of technologies as part of self-management, as well as early information and support seeking for NSSI online.ConclusionsThis study contributes a greater understanding of young people's experiences with self-injury, their self-management practices, and their desire to engage with technology. Our findings highlight the need for design flexibility in developing digital interventions that support individual goals, unique presentations of NSSI, and needs at different phases of recovery. Implications for the design of highly personalized and relevant digital interventions to address NSSI are discussed.

Project description:BackgroundThe use of internet search data has been demonstrated to be effective at predicting influenza incidence. This approach may be more successful for dengue which has large variation in annual incidence and a more distinctive clinical presentation and mode of transmission.MethodsWe gathered freely-available dengue incidence data from Singapore (weekly incidence, 2004-2011) and Bangkok (monthly incidence, 2004-2011). Internet search data for the same period were downloaded from Google Insights for Search. Search terms were chosen to reflect three categories of dengue-related search: nomenclature, signs/symptoms, and treatment. We compared three models to predict incidence: a step-down linear regression, generalized boosted regression, and negative binomial regression. Logistic regression and Support Vector Machine (SVM) models were used to predict a binary outcome defined by whether dengue incidence exceeded a chosen threshold. Incidence prediction models were assessed using r² and Pearson correlation between predicted and observed dengue incidence. Logistic and SVM model performance were assessed by the area under the receiver operating characteristic curve. Models were validated using multiple cross-validation techniques.ResultsThe linear model selected by AIC step-down was found to be superior to other models considered. In Bangkok, the model has an r² = 0.943, and a correlation of 0.869 between fitted and observed. In Singapore, the model has an r² = 0.948, and a correlation of 0.931. In both Singapore and Bangkok, SVM models outperformed logistic regression in predicting periods of high incidence. The AUC for the SVM models using the 75th percentile cutoff is 0.906 in Singapore and 0.960 in Bangkok.ConclusionsInternet search terms predict incidence and periods of large incidence of dengue with high accuracy and may prove useful in areas with underdeveloped surveillance systems. The methods presented here use freely available data and analysis tools and can be readily adapted to other settings.

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The incidence and prediction of self-injury among sentenced prisoners.

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The incidence and prediction of self-injury among sentenced prisoners.

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