[The Dutch version of the Radner Reading Chart for assessing vision function]. / De Nederlandse versie van de Radner-leeskaart voor het beoordelen van de functionele visus.

A chart for measuring visual acuity is a better functional test than the routine distance visual acuity testing with single optotypes. The characteristics of a good reading chart are: logarithmically diminishing print size, simultaneous measurement of reading acuity and reading speed, and the calculation of one score for reading acuity corrected for the number of reading errors. The original German-language Radner Reading Chart meets all these requirements, and above all emphasizes the principle of 'sentence optotypes' i.e. highly standardized sentences, because sentence complexity also influences reading performance. Sentence optotypes were created in the Dutch language and tested according to Radner's strict principles. The most equally matched sentence optotypes in terms of reading speed and number of reading errors were selected for the introduction and printing of the first Dutch version of the Radner Reading Chart. The Dutch Radner Reading Chart is precise and practical and therefore useful for research and daily practice.

Impact of the introduction of a guideline on the targeted detection of hereditary haemochromatosis.

BACKGROUND: In 1998 a clinical guideline for the targeted, accurate and early detection and treatment of HFE-related hereditary haemochromatosis (HH), which comprises a test for the causative HFE-gene mutations, was introduced in our outpatient department. METHODS: The impact of this guideline was evaluated retrospectively. Data were acquired from medical records of patients with discharge diagnosis codes suggestive of HH (n=878 patients), obtained from a period before (n=422) and after guideline introduction (n=456). RESULTS: Combined measurements of serum transferrin saturation and serum ferritin rose from 12.2% (n=53) to 29.5% (n=138, p<0.001), leaving 70% of the patients eligible for HH not tested for iron parameters. The HFE-gene mutation detection test was correctly used in II (40.7%) of 27 tested patients and improperly interpreted in six (22.2%) of these 27 patients. Five new HH patients were diagnosed before and 13 after introduction. Seven of these 13 patients appeared to be incorrectly diagnosed, due to misinterpretation of laboratory results. Diagnostic costs of case detection for each accurately diagnosed patient were euro 2380 before and euro 2600 after introduction of the guideline. CONCLUSION: Evaluation of the introduction of a practical guideline for targeted HH detection reveals a low compliance with the guideline, resulting in both a small percentage of patients tested for HH and overdiagnosis of HH. Therefore, the introduction of the guideline should be combined with a more appropriate implementation strategy which includes education on its most critical points, i.e. the indication and interpretation of the iron parameters and the HFE genotype.

Impact factors on intraocular pressure measurements in healthy subjects.

AIM: To evaluate whether intraocular pressure (IOP) calculation by applanation tonometry is determined more essentially by the subject's neck position or by neck constriction. METHODS: 23 right eyes of 23 healthy subjects (12 male, 11 female) were included. IOP was measured by applanation tonometry with the TonoPen on sitting participants under four different conditions: with open collar upright (A) or with the head in the headrest of a slit lamp (B), with a tight necktie upright (C) or in slit lamp position (D). All measurements with neck constriction were performed 3 minutes after placing the necktie. RESULTS: Mean IOP was 16.9 (SD 2.3) mm Hg (range 11-21 mm Hg) (A), 18.1 (SD 2.2) mm Hg (range 14-22 mm Hg) (B), 17.9 (SD 2.9) mm Hg (range 12-25 mm Hg) (C) and 18.7 (SD 2.7) mm Hg (range 13-24 mm Hg) (D). Mean IOP increased by 1.3 (SD 2.6) mm Hg (p = 0.028, paired t test, range +0.2 to +2.4 mm Hg) if subjects changed position from A to B. There was no statistically significant difference between measurements with or without neck constriction. CONCLUSION: Applanation tonometry may be inaccurate if performed in slit lamp position. In contrast, tight neckties do not significantly affect IOP evaluation in healthy subjects.

Predicting the need for hospital admission in patients with intentional drug overdose.

BACKGROUND: Self-poisoned patients are often admitted to a medical unit. However, often no treatment is given. We have developed a model to predict those patients who will not be treated and how long patients should be observed before this prediction can be safely made. METHODS: In this retrospective study a model to predict treatment was developed based on cases of self-poisoning in 1996 and validated on cases between 1997 and 1999. In a teaching hospital in The Netherlands 299 adults performing 353 episodes of self-poisoning were studied. The main outcome measures were predicted versus initiated medical treatment, time to prediction and time to initiation of treatment. RESULTS: The model predicted that in 51% (156/307) of all autointoxications no treatment would be given. In 2% (6/307) of all cases, treatment was incorrectly not predicted. All but one of these were preventive treatments based on the ingested compound. 4.5 hours after admission no additional patients fulfilled the criteria for prediction of treatment and all treatments were started within 4.5 hours. CONCLUSIONS: In 51% of patients that present with an autointoxication the model accurately predicts that no treatment will be initiated. This decision can be made in the first 4.5 hours after presentation. This model can be used for a first screening of patients. It can also be used as a basis for a further prospective study to establish rational guidelines in the management of these patients.

Comparison of estimates and calculations of risk of coronary heart disease by doctors and nurses using different calculation tools in general practice: cross sectional study.

OBJECTIVE: To assess the effect of using different risk calculation tools on how general practitioners and practice nurses evaluate the risk of coronary heart disease with clinical data routinely available in patients' records. DESIGN: Subjective estimates of the risk of coronary heart disease and results of four different methods of calculation of risk were compared with each other and a reference standard that had been calculated with the Framingham equation; calculations were based on a sample of patients' records, randomly selected from groups at risk of coronary heart disease. SETTING: General practices in central England. PARTICIPANTS: 18 general practitioners and 18 practice nurses. MAIN OUTCOME MEASURES: Agreement of results of risk estimation and risk calculation with reference calculation; agreement of general practitioners with practice nurses; sensitivity and specificity of the different methods of risk calculation to detect patients at high or low risk of coronary heart disease. RESULTS: Only a minority of patients' records contained all of the risk factors required for the formal calculation of the risk of coronary heart disease (concentrations of high density lipoprotein (HDL) cholesterol were present in only 21%). Agreement of risk calculations with the reference standard was moderate (kappa=0.33-0.65 for practice nurses and 0.33 to 0.65 for general practitioners, depending on calculation tool), showing a trend for underestimation of risk. Moderate agreement was seen between the risks calculated by general practitioners and practice nurses for the same patients (kappa=0.47 to 0.58). The British charts gave the most sensitive results for risk of coronary heart disease (practice nurses 79%, general practitioners 80%), and it also gave the most specific results for practice nurses (100%), whereas the Sheffield table was the most specific method for general practitioners (89%). CONCLUSIONS: Routine calculation of the risk of coronary heart disease in primary care is hampered by poor availability of data on risk factors. General practitioners and practice nurses are able to evaluate the risk of coronary heart disease with only moderate accuracy. Data about risk factors need to be collected systematically, to allow the use of the most appropriate calculation tools.