Clinical characteristics of unilateral myopic anisometropia in a juvenile optometric practice population

Purpose: A retrospective study of longitudinal case histories, undertaken to establish the clinical and statistical characteristics of unilateral myopic anisometropia (UMA) amongst the juvenile and adolescent population at an optometric practice, is reported. UMA was defined as that specific refractive state where an unequivocally myopic eye is paired with a 'piano' [spherical equivalent refraction, (SER) = ±0.25 Dioptres (D)] companion eye. Methods: The clinical records of all patients aged <19 years on file at an established independent optometric practice were categorised as 'myopic' (SER ≤-0.50 D), 'hypermetropie' (≥+0.75 D) or 'emmetropic' (≥-0.37≤+0.62 D). Subsequently all juvenile patients matching the UMA criterion, together with a case-matched group of bilaterally myopic individuals, were selected as the comparative study populations. Results: A total of 14.4% (n = 21 of 146) of the juvenile myopic case histories were identified as cases of UMA. More than half of these UMA cases emerged between the ages of 11.5 and 13.5 years. There was a marked female gender bias. The linear gradient of the age-related mean refractive trend in the myopic eye of the UMA population was not statistically significantly different (p > 0.1) to that fitted to the ametropic progression recorded in either eye of the case-matched population of young bilateral myopes; uniquely the slope associated with the companion eye of UMA cases was statistically significantly (p < 0.025) less steep. Compared with bilateral myopes fewer cases of UMA required a refractive correction to relieve visual or asthenopic symptoms, and this initial correction was dispensed on average 1 year later (at age 12.7 years) in UMA patients. Conclusions: Individuals identified as demonstrating clinically-defined UMA can be considered as distinct but functionally normal cases on the continuum of human refractive error. However, any unilaterally-acting determining factor(s) underlying the genesis of the condition remain obscure. © 2004 The College of Optometrists.

The role of suicide risk in the decision for psychiatric hospitalization after a suicide attempt

BACKGROUND: Suicide prevention can be improved by knowing which variables physicians take into account when considering hospitalization or discharge of patients who have attempted suicide. AIMS: To test whether suicide risk is an adequate explanatory variable for predicting admission to a psychiatric unit after a suicide attempt. METHODS: Analyses of 840 clinical records of patients who had attempted suicide (66.3% women) at four public general hospitals in Madrid (Spain). RESULTS: 180 (21.4%) patients were admitted to psychiatric units. Logistic regression analyses showed that explanatory variables predicting admission were: male gender; previous psychiatric hospitalization; psychiatric disorder; not having a substance-related disorder; use of a lethal method; delay until discovery of more than one hour; previous attempts; suicidal ideation; high suicidal planning; and lack of verbalization of adequate criticism of the attempt. CONCLUSIONS: Suicide risk appears to be an adequate explanatory variable for predicting the decision to admit a patient to a psychiatric ward after a suicide attempt, although the introduction of other variables improves the model. These results provide additional information regarding factors involved in everyday medical practice in emergency settings.

Quality of the written information about suicide attempters

INTRODUCTION: The aim of the study was to assess the quality of the clinical records of the patients who are seen in public hospitals in Madrid after a suicide attempt in a blind observation. METHODS: Observational, descriptive cross-sectional study conducted at four general public hospitals in Madrid (Spain). Analyses of the presence of seven indicators of information quality (previous psychiatric treatment, recent suicidal ideation, recent suicide planning behaviour, medical lethality of suicide attempt, previous suicide attempts, attitude towards the attempt, and social or family support) in 993 clinical records of 907 patients (64.5% women), ages ranging from 6 to 92 years (mean 37.1±15), admitted to hospital after a suicide attempt or who committed an attempt whilst in hospital. RESULTS: Of patients who attempted suicide, 94.9% received a psychosocial assessment. All seven indicators were documented in 22.5% of the records, whilst 23.6% recorded four or less than four indicators. Previous suicide attempts and medical lethality of current attempt were the indicators most often missed in the records. The study found no difference between the records of men and women (z=0.296; p=0.767, two tailed Mann-Whitney U test), although clinical records of patients discharged after an emergency unit intervention were more incomplete than the ones from hospitalised patients (z=2.731; p=0.006), and clinical records of repeaters were also more incomplete than the ones from non-repeaters (z=3.511; p<0.001). CONCLUSIONS: Clinical records of patients who have attempted suicide are not complete. The use of semi-structured screening instruments may improve the evaluation of patients who have self- harmed.

Using secondary knowledge to support decision tree classification of retrospective clinical data

Retrospective clinical data presents many challenges for data mining and machine learning. The transcription of patient records from paper charts and subsequent manipulation of data often results in high volumes of noise as well as a loss of other important information. In addition, such datasets often fail to represent expert medical knowledge and reasoning in any explicit manner. In this research we describe applying data mining methods to retrospective clinical data to build a prediction model for asthma exacerbation severity for pediatric patients in the emergency department. Difficulties in building such a model forced us to investigate alternative strategies for analyzing and processing retrospective data. This paper describes this process together with an approach to mining retrospective clinical data by incorporating formalized external expert knowledge (secondary knowledge sources) into the classification task. This knowledge is used to partition the data into a number of coherent sets, where each set is explicitly described in terms of the secondary knowledge source. Instances from each set are then classified in a manner appropriate for the characteristics of the particular set. We present our methodology and outline a set of experiential results that demonstrate some advantages and some limitations of our approach. © 2008 Springer-Verlag Berlin Heidelberg.