Optimizing pain management following kidney stone surgery: can we avoid narcotics?

INTRODUCTION: Opioids are often used to manage postoperative pain. Non-narcotic alternatives have increasingly been used to reduce opioid usage. We conducted an open-label randomized non-inferiority clinical trial to compare non-opioid to opioid therapy for pain management after nephrolithiasis surgery. METHODS: Patients undergoing elective ureteroscopy or percutaneous nephrolithotomy between July 2018 and May 2021 were randomized to receive ketorolac (non-opioid) or oxycodone-acetaminophen (opioid). Each patient was surveyed one week postoperatively to assess pain outcomes. Patient demographics, surgical variables, number of pills used, constipation, and adverse events were also assessed. We evaluated whether non-opioid analgesia was non-inferior to opioid analgesia for postoperative pain, assuming a non-inferiority margin of 1.3 in pain score between groups. RESULTS: Analyses were based on 90 patients with postoperative pain data: 44 in the ketorolac group and 46 in the oxycodone-acetaminophen group. The groups were similar regarding demographics, type of surgery, ureteral stent placement, and stone burden. Non-inferiority of non-opioids compared to opioids was demonstrated for all outcomes. At follow-up, the average pain scores were 3.20 ± 1.94 (SD) in the non-opioid group and 4.17 ± 1.84 in the opioid group (difference = - 0.96; 95% CI: - 1.76, - 0.17, p = 0.018). The mean proportions of unused pills were similar between groups (p = 0.47) as were rates of constipation (p = 0.32). CONCLUSIONS: Non-opioid analgesia was non-inferior to opioid analgesia in pain management after kidney stone surgery. This trial contributes to the evidence that non-opioid analgesics should be considered an effective option for pain management following non-invasive urologic procedures.

Assessing and managing the risk of Aedes mosquito introductions via the global maritime trade network.

The global shipping network (GSN) has been suggested as a pathway for the establishment and reintroduction of Aedes aegypti and Aedes albopictus primarily via the tire trade. We used historical maritime movement data in combination with an agent-based model to understand invasion risk in the United States Gulf Coast and how the risk of these invasions could be reduced. We found a strong correlation between the total number of cargo ship arrivals at each port and likelihood of arrival by both Ae. aegypti and Ae. albopictus. Additionally, in 2012, 99.2% of the arrivals into target ports had most recently visited ports likely occupied by both Ae. aegypti and Ae. albopictus, increasing risk of Aedes invasion. Our model results indicated that detection and removal of mosquitoes from containers when they are unloaded effectively reduced the probability of mosquito populations establishment even when the connectivity of ports increased. To reduce the risk of invasion and reintroduction of Ae. aegypti and Ae. albopictus, surveillance and control efforts should be employed when containers leave high risk locations and when they arrive in ports at high risk of establishment.

Modeling marine cargo traffic to identify countries in Africa with greatest risk of invasion by Anopheles stephensi.

Anopheles stephensi, an invasive malaria vector native to South Asia and the Arabian Peninsula, was detected in Djibouti's seaport, followed by Ethiopia, Sudan, Somalia, and Nigeria. If An. stephensi introduction is facilitated through seatrade, similar to other invasive mosquitoes, the identification of at-risk countries are needed to increase surveillance and response efforts. Bilateral maritime trade data is used to (1) identify coastal African countries which were highly connected to select An. stephensi endemic countries, (2) develop a prioritization list of countries based on the likelihood of An. stephensi introduction through maritime trade index (LASIMTI), and (3) use network analysis of intracontinental maritime trade to determine likely introduction pathways. Sudan and Djibouti were ranked as the top two countries with LASIMTI in 2011, which were the first two coastal African countries where An. stephensi was detected. With Djibouti and Sudan included as source populations, 2020 data identify Egypt, Kenya, Mauritius, Tanzania, and Morocco as the top countries with LASIMTI. Network analysis highlight South Africa, Mauritius, Ghana, and Togo. These tools can prioritize efforts for An. stephensi surveillance and control in Africa. Surveillance in seaports of identified countries may limit further expansion of An. stephensi by serving as an early warning system.