BackgroundGenitourinary tuberculosis (GUTB) is known to cause high rates of structural organ damage, however, literature on its biochemical manifestations is limited. Additionally, local studies in the Philippine setting, where cases are rampant, are few and dated. This study aimed to determine the serologic and urinary profile of patients with GUTB admitted at a tertiary hospital within January 2009 to March 2020 and their association with short-term outcomes.MethodsThis retrospective study included 112 patients with laboratory-confirmed GUTB (i.e., positivity in acid-fast smear, polymerase chain reaction, culture, or histology). Demographic data, clinical characteristics, laboratory and radiologic findings, histopathology reports, treatment, and short-term outcomes were recorded.ResultsBladder (54.5%) and kidney (36.4%) were the most affected organs. The male:female ratio was 1:1.15, and the mean age was 35.79 ± 18.29 years. Weakness (14.29%) was the most common chief complaint. A majority presented with anemia (83.04%), while several had leukocytosis (41.96%) and thrombocytosis (26.79%). Hypoalbuminemia (58.10%), impairment of renal function (36.94%), and electrolyte abnormalities such as hyponatremia (50.93%), hypercalcemia (20.19%), and hypokalemia (21.82%) were common. Proteinuria (67.96%) and pyuria (67.96%) were the most frequent abnormal findings, followed by hematuria (51.46%), acidic urine (45.63%) and low specific gravity (31.07%). Age, leukocytosis, and the need for pressors were all significantly associated with mortality (p values of <0.001, 0.010, and <0.001, respectively).ConclusionsThe young age at presentation with severe clinical and laboratory manifestations may reflect local epidemiology as TB continues to be widespread in the country. Apart from the more commonly cited abnormalities in literature, multiple electrolyte imbalances and urinary concentration defects were also observed in many cases, possibly indicating tubulointerstitial involvement—a complication increasingly mentioned in case reports. As several patient characteristics were found to be associated with the high mortality rates observed in the study, further research is recommended to explore predictive modeling.