Volume 158 Number 6, Part 1

trol and spontaneous abortion in insulin-dependent dia­betic women. Obstet Gynecol 1986;68:366.

4. Mimouni F, Miodovnik M, Tsang RC, et al. Decreased maternal serum magnesium concentrations and adverse fetal outcome in insulin-dependent diabetic women. Obstet Gynecol 1987;70:85.

Reply To the Editors:

The central issue addressed in our '}rticle is whether the clinical event of spontaneous abortion, recognized as such by the pregnant woman, occurred with greater frequency if diabetes mellitus were also present. Our data concur with those of Miodovnik et al. 1 in suggest­ing that the risk is approximately doubled for women with diabetes. We would also agree with the point they make in their letter that a prospective approach is more likely to be accurate than a retrospective one.

However, the substantial differences in the abortion rates between the studies can not be accounted for sim­ply in terms of the superiority of the prospective ap­proach. In our article we admit the difficulties relating to abortions very early in pregnancy, and for that rea­son we include an analysis of abortions occurring after the ninth completed week of gestation. Additionally, the criterion used for the upper limit of spontaneous abortion was the then (and now) current British stan­dard of 28 completed weeks. Clearly, our studies ought to be comparable over the period between 10 and 20 completed weeks of gestation. Three of the sponta­neous abortions in our study occurred after the nine­teenth completed week of gestation, giving an abortion rate of 221161 = 13.66% between 10 and 20 weeks. Although not completely clear from their article, this would compare with a rate of 33/129 = 25.58% over the same gestational ages reported by Miodovnik et al. 1

If the abortion rate in Aberdeen had been similar to that reported from Cincinnati, it would mean that 24 pregnancies of~ 10 weeks' gestation that ended in abor­tion in insulin-dependent diabetic women who were attending the Aberdeen Diabetic Clinic would have been unrecorded (i.e., 46/182 = rate 25.27%). If the authors believed that such a situation were possible, they would not have troubled the JouRNAL with their paper.

Apart from the acknowledged superiority of the prospective design, it is also possible that the women studied in Aberdeen differed from those studied by Miodovnik et al. In particular, we note that the study reported in 1984 1 was part of a long-term study of patients with juvenile-onset diabetes. In the two later studies cited,2

• 3 the age at onset of the disease among

those women with spontaneous abortions appears markedly lower than those who did not have an abor­tion. Our study was not restricted to those with juvenile­onset of the disease.

The relatively "low" abortion rates of our "control" population are, of course, readily explained by the "about 8% of human pregnancies ... lost at such an

Correspondence 14 73

early stage of development that the patients are un­aware that conception has occurred" reported by Whit­taker et al. 4

Whereas it is possible that differences in either the age at onset or the duration of the disease (the two are obviously related) account for the differences in the abortion rates between the two studies, we suspect that the more likely explanation lies in the degree of met­abolic control present at the time of conception. Al­though dietary and exercise regulation was used in both centers, in Cincinnati it appears that glycemic control "for most patients" resulted from "once daily injections of intermediate acting insulin"' to be compared with "twice daily long- and short-acting insulin" for every patient in Aberdeen (probably similar to the therapeu­tic regimen introduced in pregnancy in Cincinnati3

).

Even in centers such as Aberdeen, operating in a free-of-charge National Health Service where an in­tensive educational program and specialized prepreg­nancy clinic for diabetic women have been in existence for nearly a decade, the attendance rate for insulin­dependent diabetic women is still as low as 40% to 50% before conception.

Perhaps the inference to be drawn from this Cincin­nati Aberdeen dialogue is that if the spontaneous abor­tion rate is to be reduced, twice-daily injections of short­and long-acting insulins should be recommended for all women with insulin-dependent diabetes at risk of pregnancy, rather than wait to improve metabolic con­trol when pregnancy has occurred.

Hamish W. Sutherland, MB, ChB Colin Pritchard, PhD

Department of Obstetrics and Gynaecology University of Aberdeen Aberdeen AB9 2ZE, Scotland

REFERENCES

1. Miodovnik M, Lavin JP, Knowles HC, et al. Spontaneous abortion among insulin-dependent diabetic women. AM J 0BSTET GYNECOL 1984;150:372.

2. Miodovnik M, Skillman CA, Holroyde JC, et al. Elevated maternal glycohemoglobin in early pregnancy and sponta­neous abortion among insulin-dependent diabetic women. AMJ 0BSTET GYNECOL 1985;153:439.

3. Miodovnik M, Mimouni F, Tsang RC, et al. Glycemic con­trol and spontaneous abortion in insulin-dependent dia­betic women. Obstet Gynecol 1986;68:366.

4. Whittaker PG, Taylor A, LindT, et al. Unsuspected preg­nancy loss in healthy women. Lancet 1983; l: 1126-7.

Controls in maternal serum a-fetoprotein screening

To the Editors: In their recent article on maternal serum u-fetopro­

tein testing (AM j 0BSTET GYNECOL 1987; 156:533-5), Macri et al. invoke the central limit theorem to com­pute the probability of failing to detect assay drifts ranging from 5% to 20%. They should have completed their Tables lA and IB to show that with small test

14 7 4 Correspondence

runs, 5% to 10% drift is more likely to be accepted than rejected. Instead, the authors erroneously conclude that "assay drift falls within acceptable limits." Granted, in each instance designated by a dash in their tables the shift in the population mean would fall within 95% confidence limits; nevertheless, the degree of drift in­dicated in the table has occurred. Individual runs with such degrees of drift may result in mean values outside the confidence limits, and the central limit theorem allows calculation of the probability of this occurring. For example, 5% drift in a 100-patient test run will be undetected two out of three times.

The article implies that quality control methods in current use may be deficient in detecting systematic error caused by assay drift. The serum-based reference samples used in clinical laboratories are designed to detect both random and systematic error. In studying the ability of a quality control system to detect error, one must examine several factors including the preci­sion of the assay, the number of controls, the allowed range for the controls, and the acceptable frequency of falsely rejecting an accurate run.' Only after consid­ering all of these factors can the probability of falsely accepting assay drift be established. Westgard's multi­rule method is effective in this regard; several controls combine to improve error detection while reducing the false rejection rate to I% (instead of 5% the authors describe).

The use of patient data as an adjunct to serum-based quality control has been investigated extensively in the laboratory medicine literature. 2

·3 The power of the "av­

erage of normals" method to detect assay drift depends not only on the factors cited above but also on the size and standard deviation of the patient population; of particular importance is the ratio of the population standard deviation to that of the analytic technique. Without these parameters we readers of the article have no way of comparing the authors' approach to our own quality control techniques.

Macri et a!. imply that test runs as large as 1000 patients will improve laboratory performance. Batches of such magnitude make within-assay error diffficult to control and are unusual even in the largest labora­tories, because they necessitate rerunning large num­bers of patient samples when control limits are violated. The increased assay size advocated by the authors may, in fact, cause unacceptable, and possibly undetectable, within-assay error while providing little, if any, addi­tional power in detecting drift.

Evan M. Cadoff, MD Department of Pathology University of Pittsburgh School of Medicine Clinical Chemistry Laboratory 3705 Fifth Ave. at DeSoto St. Room 5845 Main Tower Pittsburgh, PA 15213-2583

Department of Pathology State University of New York Basic Health Science, T9-140 Stony Brook, NY 11794-8691

M. Desmond Burke, MD

REFERENCES

June 1988 Am J Obstet Gynecol

l. Westgard JO, Klee GG. Quality assurance. In: Tietz NW, ed. Textbook of clinical chemistry. Philadelphia: WB Saun­ders, 1986:424.

2. Czembrowski GS, Chandler EP, Westgard JO. Assessment of "average of normals" quality control procedures and guidelines for implementation. Am J Clin Pathol 1984; 81:492-9.

3. Bergtrup H, Leroy S, Thyregod P, Walloe-Hansen P. "Av­erage of normals" used as control of accuracy, and a com­parison with other controls. Scand J Clin Lab Invest 1971;27:247-53.

Reply

To the Editors: It is clear that the writers of the above letter mis­

understand our article. By reading only the tabular information from our article, one can misinterpret the phrase "assay drift falls within acceptable limits." The text makes clear that in monitoring patient data for assay drift in an assay of 30 patients, for example, the probability of accepting an assay with I7.5% positive drift exceeds the probability of rejecting an assay with such a significant drift. The writers do not err in agree­ing with our position; as they state," ... with small test runs, 5% to IO% drift is more likely to be accepted than rejected."

The writers seek data from our laboratory to com­pare our approach with other quality control tech­niques. Once again, they overlook the fact that data from a qualified laboratory can be used in conjunction with the method we present to improve intralaboratory quality control.

The writers advocate the use of serum-based refer­ence samples and Westgard's multirule method as a means of: (I) detecting both systematic and random assay errors and (2) reducing false rejection of assays. Westgard's advice in discussing quality control utilizing patient data, however, is consistent with our position, not the writers'. Westgard states: (1) test results from large numbers of patients are useful for detecting sys­tematic errors (shifts and drifts), (2) many of the control problems detected with these techniques may not be evident with conventional quality control systems, and (3) quality control mechanisms based on patient data can provide addjtional information useful in monitor­ing the quality of laboratory analyses. 1

According to the writers, our article implies that quality control methods in current use (multilevel, serum-based quality control samples) may be deficient. Indeed, this is the very focus of our article: that labo­ratories performing small assays demonstrating ac­ceptable serum-based quality control sample results may actually be experiencing significant drift that goes unrecognized. Furthermore, we contend that any qual­ity control system that can evaluate the accuracy of test results only after such results have been reported rep­resents quality control in retrospect. This would mean that patient data reported to physicians would be rec­ognized as erroneous only after the physician and pa­tient have received the data and acted on the infor-