Journal of Patan Academy of Health Sciences
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    Comparative study of ultrasonography and computed tomography for detecting stones in case of renal colic

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    Introduction: Nephrolithiasis is most common cause of renal colic encountered. Computed Tomography of kidneys, ureters and bladder (CT-KUB) was found to be extremely sensitive and specific for ureteric calculi. This study aimed to compare the diagnostic performance of ultrasonography ( USG) and CT-KUB in patients presenting with renal colic based on previous studies by Sharad Kondekar, Iqbal Minne & Doaa N Anas, Khaled Elshafey et.al. Method: This is a retrospective study. The USG and CT-KUB findings of 2574 patients were retrospectively analyzed over four years. The data was compiled using XLSX Spreadsheet. Sensitivity, specificity, diagnostic accuracy, positive predictive value and negative predictive values of USG were calculated taking CT-KUB as the gold standard. Result: In 2574 sets of data, the majority of patients were ≤ 30 years old with males predominating. In 2269 cases, renal calculi were detected in both USG and CT-KUB and CT-KUB alone detected renal calculi in 2554 cases. USG detected maximum 1435 cases with 5-10mm sized renal calculi and CT-KUB too detected maximum of 5-10 mm calculi in 1430 cases. The sensitivity, specificity, diagnostic accuracy, positive predictive value and negative predictive values of USG taking CT-KUB as the gold standard, were 88.21%, 17.6%. 87.75%, 99.38% and 0.98% respectively. Conclusion: Although CT-KUB exposes patients to ionizing radiation, it remains the gold standard due to its higher diagnostic accuracy. USG, while less specific, may serve as an initial, no-invasive screening tool

    Interview with Professor Dr. Rajesh Nath Gongal

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    Professor Dr. Rajesh Nath Gongal is an academic and healthcare leader whose career blends surgical expertise with visionary institutional management. As a Professor of Surgery at the Patan Academy of Health Sciences (PAHS), Dr. Gongal has played a pivotal role in shaping medical education in Nepal. He is deeply committed to developing innovative curricula that produce socially responsible health care professionals. His academic contributions extend to research, including studies on empathy development among medical students and palliative care awareness, reflecting his commitment to both clinical excellence and humanistic medicine. Dr. Gongal has held several key managerial positions: he served as Medical Director of Patan Hospital, later became founding Dean, Rector and Vice-Chancellor of the Academy. He is the Founding President of Hospice Nepal, the country’s first palliative care center, and the Founding President of Nepal Ambulance Service, which introduced Emergency Medical Technician (EMT)-based emergency response through a three-digit number system. By initiating programs like Primary Trauma Care (PTC) training in Nepal, he has strengthened emergency medical preparedness across the nation. His academic leadership and managerial innovations have profoundly advanced Nepal’s medical education, healthcare delivery, and emergency response systems. The Journal of Patan Academy of Health Sciences extends its sincere gratitude to Professor Dr. Gongal for his generous and thoughtful engagement in answering the written questions prepared for this interview

    Data set: Partnership Job Board job postings

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    This dataset includes information on all jobs posted on the Partnership Job Board (https://partnershipjobs.ca/)

    How intergroup relation moderates the group bias in Third-Party Punishment

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    data and analysis script

    Can interest groups really influence a national-wide topic, when it comes out of the blind spot?

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    Drawing on a field experiment in Brazil, in which receipt of printed and WhatsApp messages from a pro-reform business organization by legislators and their aides was randomized, the paper tests if when an interest group emphasizes a blend of economic and coalitional power, legislators are more likely to vote in favor of the group’s positio

    Government Religious Preference 2.0 (GRP 2.0), Composite

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