Sample bias and overinference: two sources of error in interpreting case report data.
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Hematofluorometers manufactured by two different companies (Aviv Biomedical and Environmental Science Associates) performed satisfactorily for protoporphyrin determinations with proficiency test samples but showed about a 30% low bias with actual clinical blood specimens.
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Various technical methods were investigated with the aim of developing a multiplex system to amplify five Y-chromosome STR loci in the same PCR reaction: DYS393, DYS19, DYS390, DYS389 I and DYS389 II. A sequenced allelic ladder was constructed with previously sequenced alleles including the most common ones. A number of reamplification conditions of the allelic ladders were tested. The pentaplex was evaluated for typing using two different platforms (ABI and ALF) with promising results. However, in degraded samples non-specific artifacts were observed in the DYS393 system in the same range of sizes as the real alleles. This system can also be typed in females under relatively low stringency conditions in the PCR amplification, making this system prone to errors in critical samples. This lack of specificity can be reduced by increasing the stringency of the PCR conditions. The DYS19 ladder cannot be reamplified as stutters appear after a few reamplifications. These stutters are probably due to a 2 bp slippage induced by the presence of a TA repeat stretch in the PCR amplified fragments. Non-specific products were also noted in the DYS389 I and DYS389 II amplification, although out of the range of other alleles in this pentaplex. This newly constructed pentaplex has proved to be very useful in population genetic studies because all five Y STR markers can be loaded in the same lane of a gel with other Y STR singleplex or multiplexes. The usefulness of Y-chromosome STRs in criminal casework is especially evident in analyzing azoospermic individuals.
The findings from 30 research investigations examining the effectiveness of occupational therapy interventions were reviewed and analyzed. The statistical conclusion validity was determined by computing post hoc power coefficients for the statistical hypothesis tests included in the examined studies. Data analysis revealed the median power values to detect small, medium, and large effect sizes were .09, .33, and .66, respectively. These results suggest a high probability of Type II errors in the sample of occupational therapy intervention research examined. In practical terms, this means the intervention produced a potentially useful treatment effect, but the effect was not detected as significant. Examples are provided that illustrate how low statistical power contributes to increases in Type II errors and inhibits the development of consensus through replication in the research literature. The presence of low-power studies with high rates of false negative findings prevents the establishment of guidelines for evidence-based practice and impedes the scientific progress of rehabilitation professions such as occupational therapy.
Five chimpanzee bacterial artificial chromosome (BAC) sequences (described in GenBank) have been compared with the best matching regions of the human genome sequence to assay the amount and kind of DNA divergence. The conclusion is the old saw that we share 98.5% of our DNA sequence with chimpanzee is probably in error. For this sample, a better estimate would be that 95% of the base pairs are exactly shared between chimpanzee and human DNA. In this sample of 779 kb, the divergence due to base substitution is 1.4%, and there is an additional 3.4% difference due to the presence of indels. The gaps in alignment are present in about equal amounts in the chimp and human sequences. They occur equally in repeated and nonrepeated sequences, as detected by REPEATMASKER (http://ftp.genome.washington.edu/RM/RepeatMasker.html).
OBJECTIVES: To describe the proportion and types of medical errors that are stated to be reported via incident report systems by physicians and nurses who care for pediatric patients and to determine attitudes about potential interventions for increasing error reports. METHODS: A survey on use of incident reports to document medical errors was sent to a random sample of 200 physicians and nurses at a large children's hospital. Items on the survey included proportion of medical errors that were reported, reasons for underreporting medical errors, and attitudes about potential interventions for increasing error reports. In addition, the survey contained scenarios about hypothetical medical errors; the physicians and nurses were asked how likely they were to report each of the events described. Differences in use of incident reports for documenting medical errors between nurses and physicians were assessed with chi(2) tests. Logistic regression was used to determine the association between health care profession type and likelihood of reporting medical errors. RESULTS: A total of 140 surveys were returned, including 74 from physicians and 66 by nurses. Overall, 34.8% of respondents indicated that they had reported <20% of their perceived medical errors in the previous 12 months, and 32.6% had reported <40% of perceived errors committed by colleagues. After controlling for potentially confounding variables, nurses were significantly more likely to report >or=80% of their own medical errors than physicians (odds ratio: 2.8; 95% confidence interval: 1.3-6.0). Commonly listed reasons for underreporting included lack of certainty about what is considered an error (indicated by 40.7% of respondents) and concerns about implicating others (37%). Potential interventions that would lead to increased reporting included education about which errors should be reported (listed by 65.4% of respondents), feedback on a regular basis about the errors reported (63.8%) and about individual events (51.2%), evidence of system changes because of reports of errors (55.4%), and an electronic format for reports (44.9%). Although virtually all respondents would likely report a 10-fold overdose of morphine leading to respiratory depression in a child, only 31.7% would report an event in which a supply of breast milk is inadvertently connected to a venous catheter but is discovered before any breast milk goes into the catheter. CONCLUSIONS: Medical errors in pediatric patients are significantly underreported in incident report systems, particularly by physicians. Some types of errors are less likely to be reported than others. Information in incident reports is not a representative sample of errors committed in a children's hospital. Specific changes in the incident report system could lead to more reporting by physicians and nurses who care for pediatric patients.
We present a model for the bias of free-energy differences when determined using the nonequilibrium work (NEW) formalism due to Jarzynski. Input to the model is the distribution of work values underlying the NEW calculation, and the bias is estimated by assuming that all of the inaccuracy is incurred by failure to sample work values beyond a specific point in the tail of the distribution. The model is formulated considering both small- and large-sample NEW calculations. It is then applied to the study of bias for cases in which the work distribution is Gaussian. The model is shown to give an excellent description of the bias in situations where the bias is a more significant source of error than the sample variance. A scaling law is presented and it is shown that the bias as a function of sampling can be reduced to a single universal curve, approximately valid for all Gaussian work distributions. This result is used to formulate a simple criterion that can be applied to test if a NEW calculation is effectively free of bias. The criterion is shown to be effective even though it uses the measured (and perhaps biased) free energy as an input.
We developed a computer model to study the use of patients' specimens to assess compliance of cholesterol measurement performance with the 1992 goals of the Laboratory Standardization Panel of the National Cholesterol Education Program. The model uses Monte Carlo techniques to simulate cholesterol measurements that are subject to both systematic and random error. Split-sample measurements by a clinical laboratory and by a reference laboratory are compared by using linear regression to estimate clinical laboratory bias and imprecision; subsequently, according to specified decision limits, the performance of the clinical laboratory is classified as acceptable or deficient. We have quantified the influence of the bias and imprecision of the clinical laboratory, the imprecision of the reference laboratory, the number of split samples compared, and the decision limits on the accuracy of the classification of clinical laboratory performance. Unless the decision limits are carefully selected and a sufficient number of split samples are used, clinical laboratory performance will be frequently misclassified.
DNA profiling has been automated by the fluorescent tagging of amplified variable number tandem repeat (VNTR) loci. This was achieved by the use of fluorescently labeled primers in the amplification of 10 ng of genomic DNA, coupled with laser detection of the products during electrophoresis. The PCR products are sized by co-electrophoresing a standard size ladder mixed with every sample, thereby eliminating errors in size estimation caused by lane-to-lane differences in migration rate. This increases the precision of VNTR characterization and enables alleles that differ by a single 15-bp repeat to be resolved. The system is capable of high throughput: Twenty-four samples are electrophoresed and analyzed within 6 hr. Also, because four different dyes are available, three different loci can be simultaneously characterized with the fourth dye used for the internal standard. Approximately 100 unrelated British caucasians were analyzed at the loci D1S80, D17S5, and ApoB. The probabilities of two unrelated individuals matching by chance (pM) at these three loci were determined to be 0.065, 0.040, and 0.069, respectively, with a combined pM of 1.8 x 10(-4).
This research was performed to test the hypothesis that acoustic-resonance spectrometry (ARS) is able to rapidly and accurately differentiate tablets of similar size and shape. The US Food and Drug Administration frequently orders recalls of tablets because of labeling problems (eg, the wrong tablet appears in a bottle). A high-throughput, nondestructive method of online analysis and label comparison before shipping could obviate the need for recall or disposal of a batch of mislabeled drugs, thus saving a company considerable expense and preventing a major safety risk. ARS is accurate and precise as well as inexpensive and nondestructive, and the sensor is constructed from readily available parts, suggesting utility as a process analytical technology (PAT). To test the classification ability of ARS, 5 common household tablets of similar size and shape were chosen for analysis (aspirin, ibuprofen, acetaminophen, vitamin C, and vitamin B12). The measures of successful tablet identification were intertablet distances in nonparametric multidimensional standard deviations (MSDs) greater than 3 and intratablet MSDs less than 3, as calculated from an extended bootstrap error-adjusted single sample technique. The average intertablet MSD was 65.64, while the average intratablet MSD from cross-validation was 1.91. Tablet mass (r (2) = 0.977), thickness (r (2) = 0.977), and density (r (2) = 0.900) were measured very accurately from the AR spectra, each with less than 10% error. Tablets were identified correctly with only 250 ms data collection time. These results demonstrate that ARS effectively identified and characterized the 5 types of tablets and could potentially serve as a rapid high-throughput online pharmaceutical sensor.
The important assumption of independent errors should be evaluated routinely in the application of interrupted time-series regression models. The two most frequently recommended tests of this assumption [Mood's runs test and the Durbin-Watson (D-W) bounds test] have several weaknesses. The former has poor small sample Type I error performance and the latter has the bothersome property that results are often declared to be "inconclusive." The test proposed in this article is simple to compute (special software is not required), there is no inconclusive region, an exact p-value is provided, and it has good Type I error and power properties relative to competing procedures. It is shown that these desirable properties hold when design matrices of a specified form are used to model the response variable. A Monte Carlo evaluation of the method, including comparisons with other tests (viz., runs, D-W bounds, and D-W beta), and examples of application are provided.
A corpus of phonological errors produced in narrative speech by a Wernicke's aphasic speaker (R.W.B.) was tested for context effects using two new methods for establishing chance baselines. A reliable anticipatory effect was found using the second method, which estimated chance from the distance between phoneme repeats in the speech sample containing the errors. Relative to this baseline, error-source distances were shorter than expected for anticipations, but not perseverations. R.W.B.'s anticipation/perseveration ratio measured intermediate between a nonaphasic error corpus and that of a more severe aphasic speaker (both reported in Schwartz et al., 1994), supporting the view that the anticipatory bias correlates to severity. Finally, R.W.B's anticipations favored word-initial segments, although errors and sources did not consistently share word or syllable position.
In order to evaluate the accuracy, precision and image plane uniformity a phantom study was undertaken on a 1.5 T whole-body MR imaging system (Philips Gyroscan S15 HP). The manufacturers algorithm for obtaining relaxation time images was used. This method uses Ratios and Least Squares (RLSQ-algorithm) on data obtained from a combination of a multi-echo (CPMG) and an inversion recovery pulse sequence, yielding a calculated T1-, T2- and a proton density image simultaneously. T1 and T2 accuracy was measured in phantoms consisting of CuSO4 and MnCl2 in aqueous solution in different concentrations. The results were compared to a reference T1 and T2 obtained by spectroscopy. The accuracy error over the entire relaxation time range was expressed as the root mean square of the modulus of the difference between the reference and the image measurement and was 2.3% for T1 and 4.1% for T2. Precision or reproducibility was measured by 11 double estimations on 11 samples. The precision error was 0.35% for both T1 and T2. Image plane uniformity, i.e., the homogeneity of pixel values throughout the image plane, was measured by 3 consecutive image readings from a phantom of 19 cm in diam. in 8 directions 45 degrees apart and 1, 3, 5, 7, 9 cm from the center. Errors in the imaging plane were expressed as the deviation from the center value. For both T1 and T2 the maximum deviation was less than 5% over the entire image in the transverse plane. It is concluded that when the pulse sequence timings are carefully optimized, the mixed imaging sequence in combination with the RLSQ algorithm used in this MRI system is a reliable and precise means of obtaining relaxation time data.