Abstract
Analogous to medication dosage errors, inaccuracies in measurement units for analyte test results in clinical laboratories can lead to adverse clinical consequences. We report a case of a 35-years-old pregnant woman at 38 weeks of gestation with a history of gestational hypertension. During routine follow-up, she presented with elevated blood pressure, abnormal qualitative urinary protein findings, and an elevated random urinary protein concentration, prompting a request for 24-hour urinary total protein quantification (UTP). The laboratory reported her 24-hour urine total protein excretion as 547.87 g/24 h, which the attending physician identified as inconsistent with the patient's clinical manifestations. Unfortunately, the medical laboratory professional failed to identify the cause of the discrepancy following receipt of the feedback and only reported the issue to the laboratory quality supervisor 1 week later. In the detection system, both the direct and 1:2 auto-diluted measurements triggered an "F" alarm code, indicating the analyte concentration exceeded the analytical measurement range. When the alarm code in the data flag column and the analyte measurement result were simultaneously transmitted to the Laboratory Information System (LIS), precluding accurate data recognition and extraction by the LIS. This led to the appearance of the alarm code in the LIS result field and disrupted the automatic unit conversion process. According to relevant requirements (such as those in the detection system operation manual or the laboratory-developed standard operating procedure), if the alarm code appears in the data flag column of the measurement result, it is necessary to further increase the dilution ratio and conduct a re-measurement. Regrettably, the alarm code was mishandled in the laboratory: it was manually suppressed in the LIS. This resulted in the failure of the automatic unit conversion, leading to a 100-fold overestimation as the results were erroneously reported in "g/L" instead of mg/dL." This case highlights critical quality management considerations for other clinical laboratories, emphasizing the importance of unit consistency across diverse detection platforms and information systems, and the quality risks associated with falsely decreased results when analyzing high-concentration samples.