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In March 2020, the Italian Government introduced measures to reduce the spread of COVID-19 infection. Between 8th April and 2nd May 2020 we investigated levels and correlates of sexual activity and depression during COVID-19 lockdown in a sample of hospital workers and their acquaintances by an online survey on SurveyMonkey. Socio-demographic data, International Index of Erectile Function, Female Sexual Function Index, and Beck Depression Inventory were recorded. Multivariable logistic regression analysis (MLRA) was used to test predictors of depressive symptoms and low sexual desire and satisfaction. A statistically significant difference in age, change in working habit, sexual satisfaction, sexual desire, and depressive symptoms was found between males and females. A statistically significant higher proportion of health care workers had low sexual desire (65.3% vs 56.8%, p = 0.042). At MLRA, age, being female, being a health care worker, having children at home, living with the partner, and having low sexual satisfaction were predictors of low level of sexual desire. To our knowledge, this is one of the few studies using validated questionnaires for both males and females to assess sexual well-being and psychometric alterations during COVID quarantine.

BackgroundAim of this study was to evaluate and compare perioperative outcomes of transperitoneal (TP) and retroperitoneal (TR) approaches in a multi-institutional cohort of minimally invasive partial nephrectomy (MI-PN).Material and methodsAll consecutive patients undergone MI-PN for clinical T1 renal tumors at 26 Italian centers (RECORd2 project) between 01/2013 and 12/2016 were evaluated, collecting the pre-, intra-, and postoperative data. The patients were then stratified according to the surgical approach, TP or RP. A 1:1 propensity score (PS) matching was performed to obtain homogeneous cohorts, considering the age, gender, baseline eGFR, surgical indication, clinical diameter, and PADUA score.Results1669 patients treated with MI-PN were included in the study, 1256 and 413 undergoing TP and RP, respectively. After 1:1 PS matching according to the surgical access, 413 patients were selected from TP group to be compared with the 413 RP patients. Concerning intraoperative variables, no differences were found between the two groups in terms of surgical approach (lap/robot), extirpative technique (enucleation vs standard PN), hilar clamping, and ischemia time. Conversely, the TP group recorded a shorter median operative time in comparison with the RP group (115 vs 150 min), with a higher occurrence of intraoperative overall, 21 (5.0%) vs 9 (2.1%); p = 0.03, and surgical complications, 18 (4.3%) vs 7 (1.7%); p = 0.04. Concerning postoperative variables, the two groups resulted comparable in terms of complications, positive surgical margins and renal function, even if the RP group recorded a shorter median drainage duration and hospital length of stay (3 vs 2 for both variables), p < 0.0001.ConclusionsThe results of this study suggest that both TP and RP are feasible approaches when performing MI-PN, irrespectively from tumor location or surgical complexity. Notwithstanding longer operative times, RP seems to have a slighter intraoperative complication rate with earlier postoperative recovery when compared with TP.

Background: We investigated the predictive role of prostatic morphology on preoperative multiparametric magnetic resonance imaging for post-prostatectomy urinary incontinence. Methods: Patients who underwent robot-assisted radical prostatectomy between February 2018 and October 2021 and who were not previously incontinent, did not undergo radiotherapy, hormone therapy, or transurethral resection of the prostate, and who had a follow-up longer than 12 months were selected. For each patient, a radiology physician evaluated the preoperative magnetic resonance imaging, measuring prostatic and membranous urethral length, classifying prostatic apex according to the Lee Type, and estimating the presence of the median lobe and its intravesical protrusion. Multivariate logistic regression models evaluated the influence of anatomic features measured in magnetic resonance imaging on urinary continence recovery, defined as daily pad usage less than or equal to one, considering age, body mass index, prostate volume, International Prostatic Symptoms Score, the usage of a nerve sparing technique, and the International Society of Urological Pathology classification. Results: A total of 95 patients who underwent robot-assisted radical prostatectomy were enrolled. Median age, median body mass index, and median PSA density were respectively 66 years (62, 70), 26.12 kg/m2 (23.88, 28.09), and 0.16 ng/mL/cc (0.10, 0.26). Patients with urinary continence ranged from 32 (33.7%) at baseline to 93 (97.8%) after one year from surgery. At preoperative magnetic resonance, Lee Type was almost equally distributed, but Type C was less represented (18 patients, 18.9%) and Type D was more frequent (31 patients, 32.2%). Median prostatic urethral length, median membranous urethral length, and median intravesical prostatic protrusion were respectively 36 mm (31, 42), 15 mm (13, 16), and 0 mm (0, 0). Multivariate logistic regression models showed no statistical significance, except for Lee Type C and A comparison at vesical catheter removal after surgery (OR 0.17; 95% CI 0.04–0.71; p-value 0.01). Conclusions: The results of this study showed that patients who had Lee Type C might have higher probability of early urinary continence recovery, but no further statistically significant correlations were found.

3D models have been introduced as tools to improve surgeon's precision during Robotic-Assisted Partial Nephrectomy (RAPN). They showed to provide accurate anatomical details, improve operative time and patient safety by reducing complications. Over the last years, several useful models have been developed and proposed. However, literature is still scant regarding if and how the experience of the operator, and the learning curve, may impact the accuracy and precision of the model. In this light, the aim of the study is to evaluate the accuracy, the interpersonal variability of the precision and the learning curve for the segmentation of RAPN 3D preoperative models starting from CT images. This study will identify the influence of operator experience and learning curves on the accuracy of 3D preoperative models in RAPN, optimizing workflows for broader clinical adoption.

Background Positron Emission Tomography (PET) imaging with Prostate-Specific Membrane Antigen (PSMA) and Fluorodeoxyglucose (FDG) represent promising biomarkers for risk-stratification of Prostate Cancer (PCa). We verified whether the expression of genes encoding for PSMA and enzymes regulating FDG cellular uptake are independent and additive prognosticators in PCa. Methods mRNA expression of genes involved in glucose metabolism and PSMA regulation obtained from primary PCa specimens were retrieved from open-source databases and analyzed using an integrative bioinformatics approach. Machine Learning (ML) techniques were used to create predictive Progression-Free Survival (PFS) models. Cellular models of primary PCa with different aggressiveness were used to compare [18F]F-PSMA-1007 and [18F]F-FDG uptake kinetics in vitro. Confocal microscopy, immunofluorescence staining, and quantification analyses were performed to assess the intracellular and cellular membrane PSMA expression. Results ML analyses identified a predictive functional network involving four glucose metabolism-related genes: ALDOB, CTH, PARP2, and SLC2A4. By contrast, FOLH1 expression (encoding for PSMA) did not provide any additive predictive value to the model. At a cellular level, the increase in proliferation rate and migratory potential by primary PCa cells was associated with enhanced FDG uptake and decreased PSMA retention (paralleled by the preferential intracellular localization). Conclusions The overexpression of a functional network involving four glucose metabolism-related genes identifies a higher risk of disease progression since the earliest phases of PCa, in agreement with the acknowledged prognostic value of FDG PET imaging. By contrast, the prognostic value of PSMA PET imaging is independent of the expression of its encoding gene FOLH1. Instead, it is influenced by the protein docking to the cell membrane, regulating its accessibility to tracer binding.

To test for rates of inpatient palliative care (IPC) in metastatic testicular cancer patients receiving critical care therapy (CCT). Within the Nationwide Inpatient Sample (NIS) database (2008–2019), we tabulated IPC rates in metastatic testicular cancer patients receiving CCT, namely invasive mechanical ventilation (IMV), percutaneous endoscopic gastrostomy tube (PEG), dialysis for acute kidney failure (AKF), total parenteral nutrition (TPN) or tracheostomy. Univariable and multivariable logistic regression models addressing IPC were fitted. Of 420 metastatic testicular cancer patients undergoing CCT, 70 (17%) received IPC. Between 2008 and 2019, the rates of IPC among metastatic testicular cancer patients undergoing CCT increased from 5 to 19%, with the highest rate of 30% in 2018 (EAPC: + 9.5%; 95% CI + 4.7 to + 15.2%; p = 0.005). IPC patients were older (35 vs. 31 years, p = 0.01), more frequently had do not resuscitate (DNR) status (34 vs. 4%, p < 0.001), more frequently exhibited brain metastases (29 vs. 17%, p = 0.03), were more frequently treated with IMV (76 vs. 53%, p < 0.001) and exhibited higher rate of inpatient mortality (74 vs. 29%, p < 0.001). In multivariable analyses, DNR status (OR 10.23, p < 0.001) and African American race/ethnicity (OR 4.69, p = 0.003) were identified as independent predictors of higher IPC use. We observed a significant increase in rates of IPC use in metastatic testicular cancer patients receiving CCT, rising from 5 to 19% between 2008 and 2019. However, this rates remain lower compared to metastatic lung cancer patients, indicating the need for further awareness among clinicians treating metastatic testicular cancer. The increase in IPC rates for metastatic testicular cancer patients receiving CCT indicates a need for ongoing education and awareness among healthcare providers. This could enhance the integration of IPC in the treatment of advanced cancer, potentially improving quality of life and care outcomes for survivors.

PurposeTo externally validate the Palacios’ equation estimating the new baseline glomerular filtration rate (NB-GFR) after partial or radical-nephrectomy (PN, RN) for Renal cancer carcinoma (RCC).Materials and methodsOur research group recently published two studies that investigated the association between renal function and cancer-specific survival in RCC. The first one included 3457 patients undergone RN or PN for a cT1-2 RCC coming from five high-volume centers; the second one considered 1767 patients undergone RN or PN for a cT1-4 RCC in a single high-volume center. From such datasets, available complete patients’ data were used to calculate the predicted NB-GFR through the Palacios’ equation: predicted NB-GFR = 35.03 + 0.65 ∙ preoperative GFR – 18.19 ∙ (if radical nephrectomy) – 0.25 ∙ age + 2.83 ∙ (if tumor size > 7 cm) – 2.09 ∙ (if diabetes). The observed NB-GFR was calculated by the CKD-EPI equation on serum creatinine at 3–12 months after surgery. Concordance between observed and predicted NB-GFR was evaluated by Lin’s concordance correlation coefficient and Bland-Altman analysis.Results2419 patients were included (1210, cohort #1; 1219, cohort #2). The median observed NB-GFR value in cohorts #1 and #2 was 73.0 ml/min/1.73 m2 (IQR 56.1–90.1) and 64.2 ml/min/1.73 m2 (IQR 49.6–83); the median predicted NB-GFR was 71.1 ml/min/1.73 m2 (IQR 58–81.5) and 62.6 ml/min/1.73m2 (IQR 47.9–75.9). The concordance line showed a slope of 0.80 and 0.86, and an intercept at 11.02 and 5.41 ml/min/1.73 m2 in the cohort#1 and #2, respectively. The Palacio’s equation moderately over-estimated and under-estimated NB-GFR, for values below and above the cut-off of 50 ml/min/1.73 m2 and 35 ml/min/1.73m2 in cohort#1 and #2. The Lin’s concordance correlation coefficient was 0.79 (95% CI 0.77–0.81) and 0.83 (95% CI 0.82–0.85).ConclusionsWe confirm the predictive performances of Palacios’ equation, supporting its utilization in clinical practice.

The contact surface area (CSA) quantifies the interface between a tumor and an organ and is a key predictor of perioperative outcomes in kidney cancer. However, existing CSA computation methods rely on shape assumptions and manual annotation. We propose a novel approach using 3D reconstructions from computed tomography (CT) scans to provide an accurate CSA estimate. Our method includes a segmentation protocol and an algorithm that processes reconstructed meshes. We also provide an open-source implementation with a graphical user interface. Tested on synthetic data, the algorithm showed minimal error and was evaluated on data from 82 patients. We computed the CSA using both our approach and Hsieh’s method, which relies on subjective CT scan measurements, in a double-blind study with two radiologists of different experience levels. We assessed the correlation between our approach and the expert radiologist’s measurements, as well as the deviation of both our method and the less experienced radiologist from the expert’s values. While the mean and variance of the differences between the less experienced radiologist and the expert were lower, our method exhibited a slight deviation from the expert’s, demonstrating its reliability and consistency. These findings are further supported by the results obtained from synthetic data testing.