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The COVID-19 pandemic generated a great impact on health systems. We compared evolution, polypharmacy, and potential drug-drug interactions (P-DDIs) in COVID-19 and non-COVID-19 hospitalizations during first wave of pandemic. Prescriptions for hospitalized patients ≥ 18 years (COVID-19 and non-COVID-19 rooms) between April and September 2020 were included. The computerized medical decision support system SIMDA and the physician order entry system Hdc.DrApp.la were used. Patients in COVID-19 rooms were divided into detectable and non-detectable, according to real-time reverse transcription polymerase chain reaction (RT-PCR). Number of drugs, prescribed on day 1, after day 1, and total; polypharmacy, excessive polypharmacy, and P-DDIs were compared. 1,623 admissions were evaluated: 881 COVID-19, 538 detectable and 343 non-detectable, and 742 non-COVID-19. Mortality was 15% in COVID-19 and 13% in non-COVID-19 (RR [non-COVID-19 vs. COVID-19]: 0.84 [95% CI] [0.66-1.07]). In COVID-19, mortality was 19% in detectable and 9% in non-detectable (RR: 2.07 [1.42-3.00]). Average number of drugs was 4.54/patient (SD ± 3.06) in COVID-19 and 5.92/patient (±3.24) in non-COVID-19 (p<0.001) on day 1 and 5.57/patient (±3.93) in COVID-19 and 9.17/patient (±5.27) in non-COVID-19 (p<0.001) throughout the hospitalization. 45% received polypharmacy in COVID-19 and 62% in non-COVID-19 (RR: 1.38 [1.25-1.51]) and excessive polypharmacy 7% in COVID-19 and 14% in non-COVID-19 (RR: 2.09 [1.54-2.83]). The frequency of total P-DDIs was 0.31/patient (±0.67) in COVID-19 and 0.40/patient (±0.94) in non-COVID-19 (p=0.022). Hospitalizations in the COVID-19 setting are associated with less use of drugs, less polypharmacy and less P-DDIs. Detectable patients had higher mortality.

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OBJECTIVES: We evaluated polypharmacy and possible drug-drug interactions (p-DDIs) in hospitalized patients before and after using the SIMDA Computerized Medical Decision Support System (CMDSS). MATERIALS AND METHODS: We included the prescriptions of ≥ 18 years hospitalized patients in the internal medicine department. We developed and implemented the Hdc.DrApp Physician Order Entry System and the CMDSS SIMDA, which detects p-DDIs and signals dosage adjustment based on renal function. To evaluate the impact of the CMDSS, we made a comparison Before (Survey) / After (Intervention): Survey between Oct/22/2019, and Mar/21/2020, and Intervention between Apr/4/2020 and Sep/3/2020. We analyze prescriptions from the first day and after the first day. We compared the number of drugs, polypharmacy (≥ 5 drugs), excessive polypharmacy (≥ 10 drugs), and p-DDIs. We evaluated differences with the X2 test, Yates correction, Fisher's exact test, ANOVA, and post hoc tests according to their characteristics. RESULTS: We evaluated 2,834 admissions: Survey 1,211 and Intervention 1,623. The number of drugs per patient was 6.02 (± 3.20) in Survey and 5.17 (± 3.22) in Intervention (p < 0.001) on the first day and 9.68 (± 5.60) in Survey and 7.22 (± 4.93) in Intervention (p < 0.001) throughout the hospitalization. Polypharmacy was present in 64% of the Survey and 53% of Interventions (RR: 0.83 (0.78-0.88); and excessive polypharmacy in 14% of the Survey and 10% of Intervention (RR: 0.73, 0.60-0.90). The frequency of total p-DDIs was 1.91/patient (± 4.11) in Survey and 0.35 (± 0.81) in the Intervention (p < 0.001). CONCLUSIONS: We developed and implemented the Hdc.DrApp and SIMDA systems that were easy to use and allowed us to quantify and reduce polypharmacy and p-DDIs.

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It is known that high levels of parathyroid hormone-related protein (PTHrP) correlate with a bad prognostic in malignancies. Here we present a patient with advanced penile cancer (PC) without antecedents of human papillomavirus infections and bone metastases but with severe hypercalcemia. By quantitative polymerase chain reaction, we observed high levels of PTHrP messenger RNA in metastatic cutaneous tissue. This is the first reported case in Argentina of hypercalcemia induced by PTHrP in human PC. Furthermore, the association of PTHrP and this disease through quantitative polymerase chain reaction allows us to consider this molecular technique as a novel tool for diagnosis in patients with PC.