The reliability of a newborn foot length measurement tool used by community volunteers to identify low birth weight or premature babies born at home in southern Tanzania
Tanya MarchantSuzanne PenfoldElibariki MkumboDonat ShambaJennie JaribuFatuma ManziJoanna Schellenberg
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Abstract:
Low birthweight babies need extra care, and families need to know whether their newborn is low birthweight in settings where many births are at home and weighing scales are largely absent. In the context of a trial to improve newborn health in southern Tanzania, a counselling card was developed that incorporated a newborn foot length measurement tool to screen newborns for low birth weight and prematurity. This was used by community volunteers at home visits and shows a scale picture of a newborn foot with markers for a 'short foot' (<8 cm). The tool built on previous hospital based research that found newborn foot length <8 cm to have sensitivity and specificity to identify low birthweight (<2500 g) of 87% and 60% respectively. Reliability of the tool used by community volunteers to identify newborns with short feet was tested. Between July-December 2010 a researcher accompanied volunteers to the homes of babies younger than seven days and conducted paired measures of newborn foot length using the counselling card tool and using a plastic ruler. Intra-method reliability of foot length measures was assessed using kappa scores, and differences between measurers were analysed using Bland and Altman plots. 142 paired measures were conducted. The kappa statistic for the foot length tool to classify newborns as having small feet indicated that it was moderately reliable when applied by volunteers, with a kappa score of 0.53 (95% confidence interval 0.40 – 0.66) . Examination of differences revealed that community volunteers systematically underestimated the length of newborn feet compared to the researcher (mean difference −0.26 cm (95% confidence interval −0.31—0.22), thus overestimating the number of newborns needing extra care. The newborn foot length tool used by community volunteers to identify small babies born at home was moderately reliable in southern Tanzania where a large number of births occur at home and scales are not available. Newborn foot length is not the best anthropometric proxy for birthweight but was simple to implement at home in the first days of life when the risk of newborn death is highest.Keywords:
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Sample size requirements that achieve a prespecified expected lower limit for a confidence interval about the intraclass kappa statistic are supplied for the case of multiple raters and a binary outcome variable. The expected lower confidence limit achievable for a given number of subjects and raters is also presented. These results should be useful in the planning stages of an interobserver agreement study in which the focus is on interval estimation rather than hypothesis-testing.
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The command kapci calculates 100(1 –α)% confidence intervals for the kappa statistic using an analytical method in the case of dichotomous variables or bootstrap for more complex situations. For instance, kapci allows estimating CI for polychotomous variables using weighted kappa or for cases in which there are more than 2 raters/replications.
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Summary. Model‐based inference procedures for the kappa statistic have developed rapidly over the last decade. However, no method has yet been developed for constructing a confidence interval about a difference between independent kappa statistics that is valid in samples of small to moderate size. In this article, we propose and evaluate two such methods based on an idea proposed by Newcombe (1998, Statistics in Medicine , 17 , 873–890) for constructing a confidence interval for a difference between independent proportions. The methods are shown to provide very satisfactory results in sample sizes as small as 25 subjects per group. Sample size requirements that achieve a prespecified expected width for a confidence interval about a difference of kappa statistic are also presented.
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kappci and kappaci compute confidence intervals for the kappa-statistic with two unique raters and with two or more (non-unique) raters and a binary outcome. kapssi computes sample size for estimating kappa with a given standard error (or standard error for given sample size) in the same situation of two or more raters and a binary outcome.
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OBJECTIVE: To estimate the inter-rater agreement on the assessment of cervical photographs after acetic acid wash, using visual inspection with acetic acid categories. METHODS: Three raters individually assessed 144 photographs as negative, positive, or suspicious for cancer. The inter-rater agreement was analyzed using the unweighted and weighted κ coefficient. To explore the reasons for concordancy and discordancy, photographs were compared on histologic evidence of cervical intraepithelial neoplasia and on testing for oncogenic types of human papillomavirus. RESULTS: Overall raw agreement among the three raters was 66.7% (96 of 144) with a κ of 0.57 (95% confidence interval 0.48, 0.66). Pair-wise agreement using unweighted and weighted κ was moderate to substantial: 0.54–0.60 and 0.56–0.63, respectively. There was concordance on negative in 25.7% (37 of 144) and on positive or suspicious for cancer in 41.0% (59 of 144). Cervical intraepithelial neoplasia II or III was not present on biopsy if photographs were concordant-negative, and the human papillomavirus test was less likely to be positive (relative risk 0.3; 95% confidence interval 0.2, 0.6) in concordant-negatives compared with concordant-positives, including suspicious for cancer. Cervical intraepithelial neoplasia II or III was more common in photographs that were concordant-positive, including suspicious for cancer, compared with discordants (relative risk 3.4, 95% confidence interval 1.5, 7.6). CONCLUSION: Based on photographs of the cervix taken after acetic acid wash, the level of agreement among raters using visual inspection with acetic acid categories was moderate to substantial, consistent with other commonly used tests.
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Abstract: Objective: To identify desirable characteristics, including different sample sizes and dental caries prevalences, in virtual samples that allow, at the same time, higher values of general agreement percentage (GPA) and Kappa coefficient (κ), under a low confidence interval (CI), in reproducibility studies. Method: A total of 384 statistical simulations of inter-examiner calibration, varying sample size (12, 15, 20, 60, 200 and 500 individuals), caries prevalence (30, 50, 60 and 90%) and percentages of positive (PA) and negative (NA) agreement (30, 50, 60 and 90%) were undertaken. GPA and κ were used to measure reproducibility and define deviation between them. Results: The sample of 60 individuals, under caries prevalence of 50%, PA and NA of 90%, presented a GPA and Kappa values of 90 and 80%, respectively, a relative small confidence interval (95%CI 0.65 - 0.95) and a GPA/Kappa deviation of 10.00. Conclusion: A virtual sample of 60 individuals, under caries prevalence of 50%, seems feasible to produce a satisfactory interexaminer agreement at epidemiological conditions. However, epidemiological studies to corroborate or refute this assertion are necessary.
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To investigate whether and to what extent central serous chorioretinopathy (CSC) depicted on color fundus photographs can be assessed using deep learning technology.We collected a total of 2,504 fundus images acquired on different subjects. We verified the CSC status of these images using their corresponding optical coherence tomography images. A total of 1,329 images depicted CSC. These images were preprocessed and normalized. This resulting data set was randomly split into three parts in the ratio of 8:1:1, respectively, for training, validation, and testing purposes. We used the deep learning architecture termed Inception-V3 to train the classifier. We performed nonparametric receiver operating characteristic analyses to assess the capability of the developed algorithm to identify CSC. To study the inter-reader variability and compare the performance of the computerized scheme and human experts, we asked two ophthalmologists (i.e., Rater #1 and #2) to independently review the same testing data set in a blind manner. We assessed the performance difference between the computer algorithms and the two experts using the receiver operating characteristic curves and computed their pair-wise agreements using Cohen's Kappa coefficients.The areas under the receiver operating characteristic curve for the computer, Rater #1, and Rater #2 were 0.934 (95% confidence interval = 0.905-0.963), 0.859 (95% confidence interval = 0.809-0.908), and 0.725 (95% confidence interval = 0.662-0.788). The Kappa coefficient between the two raters was 0.48 (P < 0.001), while the Kappa coefficients between the computer and the two raters were 0.59 (P < 0.001) and 0.33 (P < 0.05).Our experiments showed that the computer algorithm based on deep learning can assess CSC depicted on color fundus photographs in a relatively reliable and consistent way.
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Abstract Background Maculopapular cutaneous mastocytosis (MPCM) in children is classified in two variants: (i) monomorphic variant, presenting with the small macules or papules typically seen in adult patients; and (ii) polymorphic variant with larger lesions of variable size and shape, typically seen in children. The definition of polymorphic and monomorphic variants is mostly intuitive, and a validation of this classification has not been done. Objective To study interobserver variability in the classification of MPCM in two groups of observers: mastocytosis experts and general dermatologists. Materials and methods Nineteen cases of childhood MPCM were shown blindly, for classification as monomorphic or polymorphic type, to 10 independent observers (eight dermatologists, one allergist and one haematologist) from Europe and North America with a vast experience in the management of paediatric mastocytosis. Also, the same cases were shown on a screen to 129 general dermatologists attending a meeting; their votes were registered by remote controls. The interobserver variability kappa coefficient (with 95% confidence interval) was calculated to measure the reliability of the correlation. Results The value of kappa interobserver variability coefficient for the group of 10 experts (95% confidence interval) was 0.39 (0.18–0.63), which is considered as ‘fair’. The value of kappa interobserver variability coefficient for the group of 129 general dermatologists (95% confidence interval) was 0.17 (0.06–0.39), which is considered as ‘slight’. A complete agreement of all 10 experts was achieved in only four of 19 cases (21.1%) The most voted choice was concordant between the two groups in only 11 of the 19 cases. Conclusions We failed to validate the classification system of childhood MPCM in monomorphic and polymorphic types. While the rate of agreement was low for mastocytosis experts, it was nearly the agreement expected by chance in general dermatologists.
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kappci and kappaci compute confidence intervals for the kappa-statistic with two unique raters and with two or more (non-unique) raters and a binary outcome. kapssi computes sample size for estimating kappa with a given standard error (or standard error for given sample size) in the same situation of two or more raters and a binary outcome.
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