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In this task, you are given an abstract of article. Your task is to generate label "True" if abstract is structured, otherwise generate "False". A structured abstract is composed of a topic sentence (or key sentence), relevant supporting sentences, and a closing (or transition) sentence. This structure is key to keeping your abstract focused on the main idea and creating a clear and concise image.

as compared with 103 (8.2 percent) in the control group; the Kaplan-Meier estimates of the likelihood of freedom from deep-vein thrombosis or pulmonary embolism at 90 days were 94.1 percent (95 percent confidence interval, 92.5 to 95.4 percent) and 90.6 percent (95 percent confidence interval, 88.7 to 92.2 percent), respectively (P 0.001). The computer alert reduced the risk of deep-vein thrombosis or pulmonary embolism at 90 days by 41 percent (hazard ratio, 0.59; 95 percent confidence interval, 0.43 to 0.81; P 0.001).
CONCLUSIONS The institution of a computer-alert program increased physicians' use of prophylaxis and markedly reduced the rates of deep-vein thrombosis and pulmonary embolism among hospitalized patients at risk. Editorial Comment: Most hospitals have adopted electronic systems to alert physicians of drug interactions or possible substitutions, as well as other measures designed to improve the quality of care and decrease expenses. This approach was taken one step further by these authors, who evaluated whether notifying physicians that their patients were at increased risk for venous thromboembolism would decrease the incidence of deep vein thrombosis or pulmonary embolism. The premise was that simply notifying the physician would increase the use of appropriate prophylactic measures. Major surgery (defined as anything requiring general anesthesia), cancer and age greater than 75 years were included among the risk factors, each of which frequently applies to a urology population. In fact, more than 13% of the patients in the intervention group had a known diagnosis of a genitourinary cancer. The computer alert decreased the risk of deep vein thrombosis or pulmonary embolism by 41%. There are 2 lessons urologists can learn from this study. First, many urology patients are at increased risk for venous thromboembolism and appropriate prophylaxis should be used. In addition, although computer alert systems may seem intrusive at times, clinicians can expect to see more and more of them if there is further documentation that they improve the quality of care.
Output:
True