Lange, Dirk

Abstract Purpose We compared perioperative morbidity after repeat transurethral resection (re-TURP) versus primary TURP, focusing on transfusion and broader bleeding-related complications relevant to counseling and risk stratification. Methods We analyzed the American College of Surgeons National Surgical Quality Improvement Program (2013–2023) to identify men undergoing primary TURP (Current Procedural Terminology [CPT] 52601) or re-TURP (CPT 52630). The primary outcome was 30-day red blood cell transfusion. Secondary outcomes included a prespecified postoperative hematuria endpoint based on ICD-10 codes. Multivariable logistic regression evaluated associations with bleeding endpoints and downstream complications. Results Among 83,539 TURP procedures, 76,983 (92.2%) were primary and 6,556 (7.8%) were repeat. Re-TURP patients were older, had higher ASA class, and more often underwent urgent surgery. Transfusion occurred in 1.9% after re-TURP versus 1.5% after primary TURP; hematuria-coded events occurred in 3.5% versus 1.3%, respectively. After adjustment, re-TURP was associated with postoperative hematuria (adjusted odds ratio [aOR] 2.42, 95% CI 2.03–2.88) but not with transfusion (aOR 1.09, 95% CI 0.87–1.36). Older age, urgent/emergent status, bleeding disorder, and lower hematocrit predicted both bleeding endpoints. Re-TURP was associated with slightly lower odds of readmission (aOR 0.87; 95% CI 0.76–0.99) and was not associated with return to the operating room. Transfusion strongly predicted return to the operating room (aOR 7.21) and readmission (aOR 2.05), whereas hematuria predicted return to the operating room only (aOR 1.50). Conclusions Compared with primary TURP, re-TURP was associated with more hematuria-coded events but not higher adjusted transfusion risk, suggesting a relative shift toward lower-severity bleeding morbidity.

Background: Residual fragments (RFs) after percutaneous nephrolithotomy (PCNL) have a significant impact on patients' quality of life and clinical course. There is a paucity of studies that evaluate the natural history of RFs after PCNL. The objective of this study is to compare rates of reintervention, complications, stone growth, and passage in patients with RFs >4, ≤4, and ≤2 mm after PCNL. Methods: Sites from the Endourologic Disease Group for Excellence (EDGE) research consortium examined data of PCNL patients from 2015 to 2019 with at least 1-year follow-up. RF passage, regrowth, reintervention, and complications were recorded and RFs were stratified into >4 and ≤4 mm groups, as well as >2 and ≤2 mm groups. Potential predictors for stone-related events after PCNL were determined using multivariable logistic regression analysis. It was hypothesized that larger RF thresholds would result in lower passage rates, faster regrowth, and greater clinically significant events (complications and reinterventions) than smaller RF thresholds. Results: A total of 439 patients with RFs >1 mm on CT postoperative day 1 were included in this study. For RFs >4 mm, rates of reintervention were found to be significantly higher and Kaplan–Meier curve analysis showed significantly higher rates of stone-related events. Passage and RF regrowth were not found to be significantly different compared with RFs ≤4 mm. However, RFs ≤2 mm had significantly higher rates of passage, and significantly lower rates of fragment regrowth (>1 mm), complications, and reintervention compared with RFs >2 mm. On multivariable analysis, older age, body mass index, and RF size were found to be predictive of stone-related events. Conclusions: With the largest cohort to date, this study by the EDGE research consortium further confirms that clinically insignificant residual fragment is problematic for patients after PCNL, particularly in older more obese patients with larger RFs. Our study underscores the importance of complete stone clearance post-PCNL and challenges the use of Clinically insignificant residual fragment (CIFR).

Background Human kidney stones form via repeated events of mineral precipitation, partial dissolution, and reprecipitation, which are directly analogous to similar processes in other natural and manmade environments, where resident microbiomes strongly influence biomineralization. High-resolution microscopy and high-fidelity metagenomic (microscopy-to-omics) analyses, applicable to all forms of biomineralization, have been applied to assemble definitive evidence of in vivo microbiome entombment during urolithiasis. Methods Stone fragments were collected from a randomly chosen cohort of 20 patients using standard percutaneous nephrolithotomy (PCNL). Fourier transform infrared (FTIR) spectroscopy indicated that 18 of these patients were calcium oxalate (CaOx) stone formers, whereas one patient formed each formed brushite and struvite stones. This apportionment is consistent with global stone mineralogy distributions. Stone fragments from seven of these 20 patients (five CaOx, one brushite, and one struvite) were thin sectioned and analyzed using brightfield (BF), polarization (POL), confocal, super-resolution autofluorescence (SRAF), and Raman techniques. DNA from remaining fragments, grouped according to each of the 20 patients, were analyzed with amplicon sequencing of 16S rRNA gene sequences (V1–V3, V3–V5) and internal transcribed spacer (ITS1, ITS2) regions. Results Bulk-entombed DNA was sequenced from stone fragments in 11 of the 18 patients who formed CaOx stones, and the patients who formed brushite and struvite stones. These analyses confirmed the presence of an entombed low-diversity community of bacteria and fungi, including Actinobacteria, Bacteroidetes, Firmicutes , Proteobacteria , and Aspergillus niger . Bacterial cells approximately 1 μm in diameter were also optically observed to be entombed and well preserved in amorphous hydroxyapatite spherules and fans of needle-like crystals of brushite and struvite. Conclusions These results indicate a microbiome is entombed during in vivo CaOx stone formation. Similar processes are implied for brushite and struvite stones. This evidence lays the groundwork for future in vitro and in vivo experimentation to determine how the microbiome may actively and/or passively influence kidney stone biomineralization.