The importance of power and sample size estimation for study design and analysis.

Diffuse white matter abnormalities and post-hemorrhagic ventricular dilation are common at term and seem to correlate with reduced developmental quotients. Early lesions, except for cerebellar hemorrhage and major destructive lesions, do not show clear relationships with outcomes.

This study provides objective evidence that DEHSI represents diffuse white matter abnormality.

Objectives: To produce an easily understood and accessible tool for use by researchers in diagnostic studies. Diagnostic studies should have sample size calculations performed, but in practice, they are performed infrequently. This may be due to a reluctance on the part of researchers to use mathematical formulae. Methods: Using a spreadsheet, we derived nomograms for calculating the number of patients required to determine the precision of a test's sensitivity or specificity. Results: The nomograms could be easily used to determine the sensitivity and specificity of a test. Conclusions: In addition to being easy to use, the nomogram allows deduction of a missing parameter (number of patients, confidence intervals, prevalence, or sensitivity/specificity) if the other three are known. The nomogram can also be used retrospectively by the reader of published research as a rough estimating tool for sample size calculations. I n a previous paper, 1 we described a method of calculating sample size in diagnostic tests by determining the precision of the expected sensitivity and specificity. However, our experience suggests that many colleagues are reluctant to use the mathematical formula we described. Nomograms have been used in trials of therapy to aid calculation and understanding. The nomogram designed by Gore 2 for trials of therapy is an example of an easily understood and accessible tool that can be used by reader and researcher alike.Sample size estimation in diagnostic tests may take two forms. 4 Firstly, the number of subjects needed to test the hypothesis that a particular parameter will exceed a predetermined level can be estimated (that is, is the sensitivity of the new test within 10% of the reference test?). This formal statistical approach is used when the researcher needs to specify equivalence or the difference between two tests.Secondly, the number of subjects needed to define an expected level of sensitivity and specificity together with the precision of that estimate (that is, the confidence intervals) can be calculated. The mathematical approach differs depending upon whether the researcher is estimating precision (the second method) or testing a hypothesis (the first method). The methods described here are taken from the work by Buderer and are based on the researcher estimating the number of patients required to determine the precision of the result. 3 We sought to develop a similar nomogram to estimate sample size in diagnostic trials based upon determination of sample size precision. We present nomograms for the prospective calculation of sample size in studies evaluating single diagnostic tests. METHODS Derivation of the nomogramThe calculations by Buderer 3 were used to plot the nomogram. These calculations were described in detail in our

BackgroundAn early clinical score predicting an abnormal amplitude-integrated electroencephalogram (aEEG) or moderate-severe hypoxic ischemic encephalopathy (HIE) may allow rapid triage of infants for therapeutic hypothermia. We aimed to determine if early clinical examination could predict either an abnormal aEEG at age 6 hours or moderate-severe HIE presenting within 72 hours of birth.MethodsSixty infants ≥ 36 weeks gestational age were prospectively enrolled following suspected intrapartum hypoxia and signs of encephalopathy. Infants who were moribund, had congenital conditions that could contribute to the encephalopathy or had severe cardio-respiratory instability were excluded. Predictive values of the Thompson HIE score, modified Sarnat encephalopathy grade (MSEG) and specific individual signs at age 3–5 hours were calculated.ResultsAll of the 60 infants recruited had at least one abnormal primitive reflex. Visible seizures and hypotonia at 3–5 hours were strongly associated with an abnormal 6-hour aEEG (specificity 88% and 92%, respectively), but both had a low sensitivity (47% and 33%, respectively). Overall, 52% of the infants without hypotonia at 3–5 hours had an abnormal 6-hour aEEG. Twelve of the 29 infants (41%) without decreased level of consciousness at 3–5 hours had an abnormal 6-hour aEEG (sensitivity 67%; specificity 71%). A Thompson score ≥ 7 and moderate-severe MSEG at 3–5 hours, both predicted an abnormal 6-hour aEEG (sensitivity 100 vs. 97% and specificity 67 vs. 71% respectively). Both assessments predicted moderate-severe encephalopathy within 72 hours after birth (sensitivity 90%, vs. 88%, specificity 92% vs. 100%). The 6-hour aEEG predicted moderate-severe encephalopathy within 72 hours (sensitivity 75%, specificity 100%) but with lower sensitivity (p = 0.0156) than the Thompson score (sensitivity 90%, specificity 92%). However, all infants with a normal 3- and 6-hour aEEG with moderate-severe encephalopathy within 72 hours who were not cooled had a normal 24-hour aEEG.ConclusionsThe encephalopathy assessment described by the Thompson score at age 3–5 hours is a sensitive predictor of either an abnormal 6-hour aEEG or moderate-severe encephalopathy presenting within 72 hours after birth. An early Thompson score may be useful to assist with triage and selection of infants for therapeutic hypothermia.