Whispered voice test for screening for hearing impairment in adults and children: systematic review

Objective To determine the accuracy of the whispered voice test in detecting hearing impairment in adults and children. Design Systematic review of studies of test accuracy. Data sources Medline, Embase, Science Citation Index, unpublished theses, manual searching of bibliographies of known primary and review articles, and contact with authors. Study selection Two reviewers independently selected and extracted data on study characteristics, quality, and accuracy of studies. Studies were included if they had cross sectional designs, at least one of the index tests was the whispered voice test, and the reference test (audiometry) was performed on at least 80% of the participants. Data extraction Data were used to form 2x2 contingency tables with hearing impairment by audiometry as the reference standard. Data synthesis The eight studies that were found used six different techniques. The sensitivity in the four adult studies was 90% or 100% and the specificity was 70% to 87%. The sensitivity in the four childhood studies ranged from 80% to 96% and specificity ranged from 90% to 98%. Conclusion The whispered voice test is a simple and accurate test for detecting hearing impairment. There is some concern regarding the lower sensitivity in children and the overall reproducibility of the test, particularly in primary care settings. Further studies should be conducted in primary care settings to explore the influence of components of the testing procedure to optimise test sensitivity and to promote standardisation of the testing procedure.

Detecting sugarcane 'orange rust' disease using EO-1 Hyperion hyperspectral imagery

This Letter evaluates several narrow-band indices from EO-1 Hyperion imagery in discriminating sugarcane areas affected by 'orange rust' ( Puccinia kuehnii ) disease. Forty spectral vegetation indices (SVIs), focusing on bands related to leaf pigments, leaf internal structure, and leaf water content, were generated from an image acquired over Mackay, Queensland, Australia. Discriminant function analysis was used to select an optimum set of indices based on their correlations with the discriminant function. The predictive ability of each index was also assessed based on the accuracy of classification. Results demonstrated that Hyperion imagery can be used to detect orange rust disease in sugarcane crops. While some indices that only used visible near-infrared (VNIR) bands (e.g. SIPI and R800/R680) offer separability, the combination of VNIR bands with the moisture-sensitive band (1660 nm) yielded increased separability of rust-affected areas. The newly formulated 'Disease-Water Stress Indices' (DWSI-1=R800/R1660; DSWI-2=R1660/R550; DWSI-5=(R800+R550)/(R1660+R680)) produced the largest correlations, indicating their superior ability to discriminate sugarcane areas affected by orange rust disease.

Auditory lexical decisions in children with specific language impairment

This study examined spoken-word recognition in children with specific language impairment (SLI) and normally developing children matched separately for age and receptive language ability. Accuracy and reaction times on an auditory lexical decision task were compared. Children with SLI were less accurate than both control groups. Two subgroups of children with SLI, distinguished by performance accuracy only, were identified. One group performed within normal limits, while a second group was significantly less accurate. Children with SLI were not slower than the age-matched controls or language-matched controls. Further, the time taken to detect an auditory signal, make a decision, or initiate a verbal response did not account for the differences between the groups. The findings are interpreted as evidence for language-appropriate processing skills acting upon imprecise or underspecified stored representations.

Application of a species-specific PCR-RFLP to identify Ancylostoma eggs directly from canine faeces

Apart from their veterinary importance, the hookworms Ancylostoma caninum, Ancylostoma braziliense and Ancylostoma caninum are also capable of causing zoonotic disease in humans. A highly sensitive and species-specific PCR-RFLP technique was utilised to detect and differentiate the various canine Ancylostoma spp directly from eggs in faeces. This technique was utilised to screen 101 canine faecal samples from parasite endemic tea growing communities in Assam, India, as part as an ongoing epidemiological investigation into canine parasitic zoonoses. The prevalence of hookworms in dogs was found to be 98% using a combination of PCR and conventional microscopy. Overall, 36% of dogs were found positive for single hookworm infections with A. caninum, 24% positive for single infections with A. braziliense and 38% had mixed infections with both A. caninum and A. braziliense. No dogs were found positive for A. ceylanicum in the community under study. The high prevalence of A. caninum and A. braziliense in dogs in this community may account for the high incidence of cutaneous larva migrans (CLM) observed among the human population residing at the tea estates. The PCR-RFLP technique described herein allows epidemiological screening of canine hookworms to be conducted rapidly, with ease and accuracy, and has the potential to be applied to a number of different clinical, pharmacological and epidemiological situations. (C) 2004 Elsevier B.V. All rights reserved.

Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.