In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

[EX Q]: Context: Interobserver and intraobserver reliability study of improved method to evaluate radiographs of patients with scoliosis.', 'To determine the reliability of a computer-assisted measurement protocol for evaluating Cobb angle and King et al classification.', 'Evaluation of scoliosis radiographs is inherently unreliable because of technical and human judgmental errors. Objective, computer-assisted evaluation tools may improve reliability.', 'Posteroanterior preoperative radiographic images of 27 patients with adolescent idiopathic scoliosis were each displayed on a computer screen. They were marked 3 times in random sequence by each of 5 evaluators (observers) who marked 70 standardized points on the vertebrae and sacrum in each radiograph. A computer program (Spine 2002;27:2801-5) that identified curves, calculated Cobb angles, and generated the King et al classification automatically analyzed coordinates of these points. The interobserver and intraobserver variability of the Cobb angle and King et al classification evaluations were quantified and compared with values obtained by unassisted observers.', 'Average Cobb angle intraobserver standard deviation was 2.0 degrees for both the thoracic and lumbar curves (range 0.1 to 8.3 degrees for different curves). Interobserver reliability was 2.5 degrees for thoracic curves and 2.6 degrees for lumbar curves. Among the 5 observers, there was an inverse relationship between repeatability and time spent marking images, and no correlation with image quality or curve magnitude. Kappa values for the variability of the King et al classification averaged 0.85 (intraobserver).\Question: Do computer-assisted algorithms improve reliability of King classification and Cobb angle measurement of scoliosis?
[EX A]: Variability of Cobb measurements compares favorably with previously published series. The classification was more reliable than achieved by unassisted observers evaluating the same radiographs. The same principles may be applicable to other radiographic measurement and evaluation procedures.

[EX Q]: Context: To assess how different imputation methods used to account for missing variance data in primary studies influence tests of heterogeneity and pooled results from a meta-analysis with continuous outcomes.', 'Point and variance estimates for changes in serum creatinine, glomerular filtration rate, systolic blood pressure, and diastolic blood pressure were variably reported among 48 primary longitudinal studies of living kidney donors (71%-78% of point estimates were reported, 8%-13% of variance data were reported). We compared the results of meta-analysis, which either were restricted to available data or used four methods to impute missing variance data. These methods used reported P-values, reported nonparametric summaries, results from other similar studies using multiple imputation, or results from estimated correlation coefficients.', 'Significant heterogeneity was present in all four outcomes regardless of the imputation methods applied. The random effects point estimates and 95% confidence intervals varied little across imputation methods, and the differences were not clinically significant.\Question: Do imputing variance estimates alter the conclusions of a meta-analysis with continuous outcomes : a case study of changes in renal function after living kidney donation?
[EX A]: Different methods to impute the variance data in the primary studies did not alter the conclusions from this meta-analysis of continuous outcomes. Such reproducibility increases confidence in the results. However, as with most meta-analyses, there was no gold standard of truth, and results must be interpreted judiciously. The generalization of these findings to other meta-analyses, which differ in outcomes, missing data, or between-study heterogeneity, requires further consideration.

[EX Q]: Context: As next-generation sequencing (NGS) becomes a major sequencing platform in clinical diagnostic laboratories, it is critical to identify artifacts that constitute baseline noise and may interfere with detection of low-level gene mutations. This is especially critical for applications requiring ultrasensitive detection, such as molecular relapse of solid tumors and early detection of cancer. We recently observed a ~10-fold higher frequency of C:G\xa0>\xa0T:A mutations than the background noise level in both wild-type peripheral blood and formalin-fixed paraffin-embedded samples. We hypothesized that these might represent cytosine deamination events, which have been seen using other platforms.', 'To test this hypothesis, we pretreated samples with uracil N-glycosylase (UNG). Additionally, to test whether some of the cytosine deamination might be a laboratory artifact, we simulated the heat associated with polymerase chain reaction thermocycling by subjecting samples to thermocycling in the absence of polymerase. To test the safety of universal UNG pretreatment, we tested known positive samples treated with UNG.', 'UNG pretreatment significantly reduced the frequencies of these mutations, consistent with a biologic source of cytosine deamination. The simulated thermocycling-heated samples demonstrated significantly increased frequencies of C:G\xa0>\xa0T:A mutations without other baseline base substitutions being affected. Samples with known mutations demonstrated no decrease in our ability to detect these after treatment with UNG.\Question: Is cytosine deamination a major cause of baseline noise in next-generation sequencing?
[EX A]:
Baseline noise during NGS is mostly due to cytosine deamination, the source of which is likely to be both biologic and an artifact of thermocycling, and it can be reduced by UNG pretreatment.