Can repetition of deliberate self-harm be predicted? A prospective multicenter study validating clinical decision rules

Bilén, Katarina; Ponzer, Sari; Ottosson, Carin; Castrèn, Maaret; Owe‐Larsson, Björn; Ekdahl, Karin; Pettersson, Hans

doi:10.1016/j.jad.2013.01.037

Cited by 10 publications

(15 citation statements)

References 70 publications

(67 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This was relatively poor, underlining the potential utility of a decision support tool. A recent study documented the potential for clinical decision rules to augment clinical performance in risk stratification of patients who might be at risk of suicide [34]. The models studied had high sensitivity but low specificity, unlike those reported in our study which had lower sensitivity but high specificity.…”

Section: Discussioncontrasting

confidence: 73%

Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

et al. 2014

View full text Add to dashboard Cite

BackgroundTo date, our ability to accurately identify patients at high risk from suicidal behaviour, and thus to target interventions, has been fairly limited. This study examined a large pool of factors that are potentially associated with suicide risk from the comprehensive electronic medical record (EMR) and to derive a predictive model for 1–6 month risk.Methods7,399 patients undergoing suicide risk assessment were followed up for 180 days. The dataset was divided into a derivation and validation cohorts of 4,911 and 2,488 respectively. Clinicians used an 18-point checklist of known risk factors to divide patients into low, medium, or high risk. Their predictive ability was compared with a risk stratification model derived from the EMR data. The model was based on the continuation-ratio ordinal regression method coupled with lasso (which stands for least absolute shrinkage and selection operator).ResultsIn the year prior to suicide assessment, 66.8% of patients attended the emergency department (ED) and 41.8% had at least one hospital admission. Administrative and demographic data, along with information on prior self-harm episodes, as well as mental and physical health diagnoses were predictive of high-risk suicidal behaviour. Clinicians using the 18-point checklist were relatively poor in predicting patients at high-risk in 3 months (AUC 0.58, 95% CIs: 0.50 – 0.66). The model derived EMR was superior (AUC 0.79, 95% CIs: 0.72 – 0.84). At specificity of 0.72 (95% CIs: 0.70-0.73) the EMR model had sensitivity of 0.70 (95% CIs: 0.56-0.83).ConclusionPredictive models applied to data from the EMR could improve risk stratification of patients presenting with potential suicidal behaviour. The predictive factors include known risks for suicide, but also other information relating to general health and health service utilisation.

show abstract

Section: Discussioncontrasting

confidence: 73%

Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

et al. 2014

View full text Add to dashboard Cite

show abstract

“…The NICE evidence update 11 included one additional cohort study. 34 The search strategy from January 2012 to February 2015 resulted in an additional 60 papers of which three were relevant prospective cohort studies, 15 35 36 and one additional cohort study 14 was retrieved from related references (see figure 1 ). We also reran the searches for the earlier time periods.…”

Section: Resultsmentioning

confidence: 99%

Which are the most useful scales for predicting repeat self-harm? A systematic review evaluating risk scales using measures of diagnostic accuracy

et al. 2016

View full text Add to dashboard Cite

ObjectivesThe aims of this review were to calculate the diagnostic accuracy statistics of risk scales following self-harm and consider which might be the most useful scales in clinical practice.DesignSystematic review.MethodsWe based our search terms on those used in the systematic reviews carried out for the National Institute for Health and Care Excellence self-harm guidelines (2012) and evidence update (2013), and updated the searches through to February 2015 (CINAHL, EMBASE, MEDLINE, and PsychINFO). Methodological quality was assessed and three reviewers extracted data independently. We limited our analysis to cohort studies in adults using the outcome of repeat self-harm or attempted suicide. We calculated diagnostic accuracy statistics including measures of global accuracy. Statistical pooling was not possible due to heterogeneity.ResultsThe eight papers included in the final analysis varied widely according to methodological quality and the content of scales employed. Overall, sensitivity of scales ranged from 6% (95% CI 5% to 6%) to 97% (CI 95% 94% to 98%). The positive predictive value (PPV) ranged from 5% (95% CI 3% to 9%) to 84% (95% CI 80% to 87%). The diagnostic OR ranged from 1.01 (95% CI 0.434 to 2.5) to 16.3 (95%CI 12.5 to 21.4). Scales with high sensitivity tended to have low PPVs.ConclusionsIt is difficult to be certain which, if any, are the most useful scales for self-harm risk assessment. No scales perform sufficiently well so as to be recommended for routine clinical use. Further robust prospective studies are warranted to evaluate risk scales following an episode of self-harm. Diagnostic accuracy statistics should be considered in relation to the specific service needs, and scales should only be used as an adjunct to assessment.

show abstract

“…Our specific objectives were to: (a) estimate the predictive accuracy of the scales for repeat self-harm using published cut-offs; (b) plot receiver operating characteristic (ROC) curves and examine the area under the curve (AUC) for each of the scales; (c) estimate the predictive accuracy of the scales for repeat self-harm using data-determined optimal cut-offs that maximise sensitivity and specificity in this sample. We hypothesised that specific scales, which are often based on the most important epidemiological risk factors, 6,[13][14][15][16][17][18][19][20][21] would perform better than global measures of clinician-or patient-rated risk.…”

Section: Discussionmentioning

confidence: 99%

Predictive accuracy of risk scales following self-harm: Multicentre, prospective cohort study

et al. 2017

View full text Add to dashboard Cite

BackgroundScales are widely used in psychiatric assessments following self-harm. Robust evidence for their diagnostic use is lacking.AimsTo evaluate the performance of risk scales (Manchester Self-Harm Rule, ReACT Self-Harm Rule, SAD PERSONS scale, Modified SAD PERSONS scale, Barratt Impulsiveness Scale); and patient and clinician estimates of risk in identifying patients who repeat self-harm within 6 months.MethodA multisite prospective cohort study was conducted of adults aged 18 years and over referred to liaison psychiatry services following self-harm. Scale a priori cut-offs were evaluated using diagnostic accuracy statistics. The area under the curve (AUC) was used to determine optimal cut-offs and compare global accuracy.ResultsIn total, 483 episodes of self-harm were included in the study. The episode-based 6-month repetition rate was 30% (n = 145). Sensitivity ranged from 1% (95% CI 0–5) for the SAD PERSONS scale, to 97% (95% CI 93–99) for the Manchester Self-Harm Rule. Positive predictive values ranged from 13% (95% CI 2–47) for the Modified SAD PERSONS Scale to 47% (95% CI 41–53) for the clinician assessment of risk. The AUC ranged from 0.55 (95% CI 0.50–0.61) for the SAD PERSONS scale to 0.74 (95% CI 0.69–0.79) for the clinician global scale. The remaining scales performed significantly worse than clinician and patient estimates of risk (P<0.001).ConclusionsRisk scales following self-harm have limited clinical utility and may waste valuable resources. Most scales performed no better than clinician or patient ratings of risk. Some performed considerably worse. Positive predictive values were modest. In line with national guidelines, risk scales should not be used to determine patient management or predict self-harm.

show abstract

Can repetition of deliberate self-harm be predicted? A prospective multicenter study validating clinical decision rules

Cited by 10 publications

References 70 publications

Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

Which are the most useful scales for predicting repeat self-harm? A systematic review evaluating risk scales using measures of diagnostic accuracy

Predictive accuracy of risk scales following self-harm: Multicentre, prospective cohort study

Contact Info

Product

Resources

About