In-Season Cotton Yield Prediction with Scale-Aware Convolutional Neural Network Models and Unmanned Aerial Vehicle RGB Imagery.

In the pursuit of sustainable agriculture, efficient water management remains crucial, with growers relying on advanced techniques for informed decision-making. Cotton yield prediction, a critical aspect of agricultural planning, benefits from cutting-edge technologies. However, traditional methods often struggle to capture the nuanced complexities of crop health and growth. This study introduces a novel approach to cotton yield prediction, leveraging the synergy between Unmanned Aerial Vehicles (UAVs) and scale-aware convolutional neural networks (CNNs). The proposed model seeks to harness the spatiotemporal dynamics inherent in high-resolution UAV imagery to improve the accuracy of the cotton yield prediction. The CNN component adeptly extracts spatial features from UAV-derived imagery, capturing intricate details related to crop health and growth, modeling temporal dependencies, and facilitating the recognition of trends and patterns over time. Research experiments were carried out in a cotton field at the USDA-ARS Cropping Systems Research Laboratory (CSRL) in Lubbock, Texas, with three replications evaluating four irrigation treatments (rainfed, full irrigation, percent deficit of full irrigation, and time delay of full irrigation) on cotton yield. The prediction revealed that the proposed CNN regression models outperformed conventional CNN models, such as AlexNet, CNN-3D, CNN-LSTM, ResNet. The proposed CNN model showed state-of-art performance at different image scales, with the R2 exceeding 0.9. At the cotton row level, the mean absolute error (MAE) and mean absolute percentage error (MAPE) were 3.08 pounds per row and 7.76%, respectively. At the cotton grid level, the MAE and MAPE were 0.05 pounds and 10%, respectively. This shows the proposed model's adaptability to the dynamic interplay between spatial and temporal factors that affect cotton yield. The authors conclude that integrating UAV-derived imagery and CNN regression models is a potent strategy for advancing precision agriculture, providing growers with a powerful tool to optimize cultivation practices and enhance overall cotton productivity.

Emergence of artificial generative intelligence and its potential impact on urology.

INTRODUCTION: Artificial generative intelligence (AGI) and large language models (LLMs) have gained significant attention in healthcare and hold enormous promise for transforming every aspect of our life and urology is no exception. MATERIALS AND METHODS: We conducted a comprehensive literature search of electronic databases and included articles discussing AGI and LLMs in healthcare. Additionally, we have incorporated our experiences interacting with the ChatGPT and GPT-4 in different situations with real case reports and case constructs. RESULTS: Our review highlights the potential applications and likely impact of these technologies in urology, for differential diagnosis, prioritizing treatment options, and facilitating research, surgeon, and patient education. At their current developmental stage, we have recognized the need for concurrent validation and continuous human interaction necessary to induce inverse reinforced learning with human feedback to mature them to authenticity. We need to consciously adjust to the hallucinations and guard patients' confidentiality before their extensive implementations in clinical practice. We propose possible remedies for these shortcomings and emphasize the critical role of human interaction in their evolution. CONCLUSION: The integration of these tools has the potential to revolutionize urology, but it also presents several challenges needing attention. To harness the full potential of these models, urologists must consistently engage in training these tools with their clinical sense and experience. We urge the urology community to actively participate in AGI and LLM development to address potential challenges. These models could help us in unleashing our full potential and help us achieve a better work-life balance.

Comparison of outcomes after open versus robotic kidney transplantation: A systematic review and meta-analysis.

Introduction: This meta-analysis compares the clinical outcomes of robot-assisted kidney transplant (RAKT) to open kidney transplant (OKT). Methods: A systematic search of Scopus and MEDLINE databases was carried out using a combination of keywords to identify studies comparing RAKT to OKT. Baseline characteristics and preoperative and postoperative data were collected along with data on the short- and long-term outcomes. The study was registered in PROSPERO and Assessing the Methodological Quality of Systematic Reviews and Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines were followed. Results: A total of 16 studies were included with a total of 2555 patients, of which 677 underwent RAKT and 1878 underwent OKT. This meta-analysis shows a significant benefit of RAKT over OKT in terms of less intra-operative blood loss, smaller incision length, less postoperative pain scores at 24 and 48 hours, and a lower incidence of surgical site infections (SSIs), especially in obese patients. In addition, the incidence of postoperative lymphoceles was lower in the RAKT group compared to the OKT group, although not statistically significant. There was no difference between the two groups in terms of short-term graft functional outcomes and overall survival. The number of deceased donor recipients undergoing RAKT was very small. At the time of reporting this meta-analysis, no randomized controlled trials (RCTs) had been published. Conclusion: This meta-analysis showed that RAKT is a safe and feasible alternative to OKT, especially in obese individuals. Further trials are needed to confirm the safety, efficacy, and cost-effectiveness of RAKT.

Trifecta and pentafecta outcomes following robot-assisted partial nephrectomy in a multi-institutional cohort of Indian patients.

Introduction: The literature on studies reporting trifecta or pentafecta outcomes following robot-assisted partial nephrectomy (RAPN) in Indian patients is limited. The primary aim of this study was to report and evaluate the factors predicting trifecta and pentafecta outcomes following RAPN in Indian patients using the multicentric Vattikuti collective quality initiative (VCQI) database. Methods: From the VCQI database for patients who underwent RAPN, data for Indian patients were extracted and analyzed for factors predicting the achievement of trifecta and pentafecta following RAPN. Trifecta was defined as the absence of complications, negative surgical margins, and warm ischemia period shorter than 25 min or zero ischemia. Pentafecta covers all the trifecta criteria as well as >90% preservation of estimated glomerular filtration rate (eGFR) and no stage upgrade of chronic kidney disease at 12 months. Results: In this study, among 614 patients, the trifecta was achieved in 374 patients (60.9%) and pentafecta was achieved in 24.2% of the patients. Patients who achieved trifecta had significantly higher mean age (54.1 vs. 51.0 years, P = 0.005), body mass index (BMI) (26.7 vs. 26.03 kg/m2, P = 0.022), and smaller tumor size (38.6 vs. 41.4 mm, P = 0.028). The preoperative eGFR (84.2 vs. 91.9 ml/min, P = 0.012) and renal nephrometry score (RNS) (6.96 vs. 7.87, P ≤ 0.0001) were significantly lower in the trifecta group. Comparing patients who achieved pentafecta to those who did not, we noted a statistically significant difference between the two groups for tumor size (36.1 vs. 41.5 mm, P = 0.017) and RNS (6.6 vs. 7.7, P = 0.0001). On multivariate analysis, BMI and RNS were associated with trifecta outcomes. Similarly, only RNS was identified as an independent predictor of pentafecta. Conclusions: RNS and BMI were independent predictors of the trifecta. At the same time, RNS was identified as an independent predictor of pentafecta following RAPN.

Comparison of perioperative outcomes following transperitoneal versus retroperitoneal robot-assisted partial nephrectomy: a propensity-matched analysis of VCQI database.

OBJECTIVE: To compare perioperative outcomes following retroperitoneal robot-assisted partial nephrectomy (RPRAPN) and transperitoneal robot-assisted partial nephrectomy (TPRAPN). METHODS: With this Vattikuti Collective Quality Initiative (VCQI) database, study propensity scores were calculated according to the surgical access (TPRAPN and RPRAPN) for the following independent variables, i.e., age, sex, side of the surgery, RENAL nephrometry scores (RNS), estimated glomerular filtration rate (eGFR) and serum creatinine. The study's primary outcome was the comparison of trifecta between the two groups. RESULTS: In this study, 309 patients who underwent RPRAPN were matched with 309 patients who underwent TPRAPN. The two groups matched well for age, sex, tumor side, polar location of the tumor, RNS, preoperative creatinine and eGFR. Operative time and warm ischemia time were significantly shorter with RPRAPN. Intraoperative blood loss and need for blood transfusion were lower with RPRAPN. There was a significantly higher number of intraoperative complications with RPRAPN. However, there was no difference in the two groups for postoperative complications. Trifecta outcomes were better with RPRAPN (70.2% vs. 53%, p < 0.0001) compared to TPRAPN. We noted no significant change in overall results when controlled for tumor location (anteriorly or posteriorly). The surgical approach, tumor size and RNS were identified as independent predictors of trifecta on multivariate analysis. CONCLUSION: RPRAPN is associated with superior perioperative outcomes in well-selected patients compared to TPRAPN. However, the data for the retroperitoneal approach were contributed by a few centers with greater experience with this technique, thus limiting the generalizability of the results of this study.

Perioperative outcomes following robot-assisted partial nephrectomy in elderly patients.

OBJECTIVE: To compare perioperative outcomes following robot-assisted partial nephrectomy (RAPN) in patients with age ≥ 70 years to age < 70 years. METHODS: Using Vattikuti Collective quality initiative (VCQI) database for RAPN we compared perioperative outcomes following RAPN between the two age groups. Primary outcome of the study was to compare trifecta outcomes between the two groups. Propensity matching using nearest neighbourhood method was performed with trifecta as primary outcome for sex, body mass index (BMI), solitary kidney, tumor size and Renal nephrometery score (RNS). RESULTS: Group A (age ≥ 70 years) included 461 patients whereas group B included 1932 patients. Before matching the two groups were statistically different for RNS and solitary kidney rates. After propensity matching, the two groups were comparable for baselines characteristics such as BMI, tumor size, clinical symptoms, tumor side, face of tumor, solitary kidney and tumor complexity. Among the perioperative outcome parameters there was no difference between two groups for operative time, blood loss, intraoperative transfusion, intraoperative complications, need for radical nephrectomy, positive margins and trifecta rates. Warm ischemia time was significantly longer in the younger age group (18.1 min vs. 16.3 min, p = 0.003). Perioperative complications were significantly higher in the older age group (11.8% vs. 7.7%, p = 0.041). However, there was no difference between the two groups for major complications. CONCLUSION: RAPN in well-selected elderly patients is associated with comparable trifecta outcomes with acceptable perioperative morbidity.

Perioperative outcomes following robot-assisted partial nephrectomy for complex renal masses: A Vattikuti Collective Quality Initiative database study.

Introduction: Outcomes of robot-assisted partial nephrectomy (RAPN) depend on tumor complexity, surgeon experience and patient profile among other variables. We aimed to study the perioperative outcomes of RAPN for patients with complex renal masses using the Vattikuti Collective Quality Initiative (VCQI) database that allowed evaluation of multinational data. Methods: From the VCQI, we extracted data for all the patients who underwent RAPN with preoperative aspects and dimensions used for an anatomical (PADUA) score of ≥10. Multivariate logistic regression was conducted to ascertain predictors of trifecta (absence of complications, negative surgical margins, and warm ischemia times [WIT] <25 min or zero ischemia) outcomes. Results: Of 3,801 patients, 514 with PADUA scores ≥10 were included. The median operative time, WIT, and blood loss were 173 (range 45-546) min, 21 (range 0-55) min, and 150 (range 50-3500) ml, respectively. Intraoperative complications and blood transfusions were reported in 2.1% and 6%, respectively. In 8.8% of the patients, postoperative complications were noted, and surgical margins were positive in 10.3% of the patients. Trifecta could be achieved in 60.7% of patients. Clinical tumor size, duration of surgery, WIT, and complication rates were significantly higher in the group with a high (12 or 13) PADUA score while the trifecta was significantly lower in this group (48.4%). On multivariate analysis, surgical approach (retroperitoneal vs. transperitoneal) and high PADUA score (12/13) were identified as predictors of the trifecta outcomes. Conclusion: RAPN may be a reasonable surgical option for patients with complex renal masses with acceptable perioperative outcomes.

Robotic Kidney Transplantation with Regional Hypothermia versus Open Kidney Transplantation for Patients with End Stage Renal Disease: An Ideal Stage 2B Study.

PURPOSE: We report on comparative effectiveness of minimally invasive versus traditional open kidney transplantation. MATERIALS AND METHODS: We undertook a prospective cohort study of 654 patients who underwent open or robotic kidney transplantation at a single tertiary care hospital between January 2013 and December 2015. Primary outcome was delayed graft function, defined as the need for dialysis within 1 week of surgery. Secondary outcomes included postoperative complications, pain, graft rejection, and graft and patient survival. Nonparsimonious propensity score and Ding-VanderWeele analytical methods were used to account for confounding bias. RESULTS: Within the 1:3 matched cohort (robotic 126, open 378; well matched with standardized mean difference ∼10%), the robotic approach was associated with lower rates of wound infections (0% vs 4%, p=0.023) and symptomatic lymphoceles (0% vs 7% at 36 months, p=0.003), as well as reduced postoperative pain, requirement for narcotic analgesia and blood loss. There were no differences between the 2 groups, robotic versus open, with respect to graft function (delayed graft function 0% vs 2.4%, p=0.081), hospital stay (median 8 days for both, p=0.647), graft rejection (16.2% vs 18.6% at 36 months, p=0.643), and graft (95.2% vs 96.3% at 36 months, p=0.266) and overall survival (94.5% vs 98.1% at 36 months, p=0.307). Ding-VanderWeele analysis suggested minimal influence of unknown confounders on study findings. CONCLUSIONS: Robotic kidney transplantation with regional hypothermia was associated with a lower rate of postoperative complications and improved patient comfort in comparison to open kidney transplantation. Graft function, and graft and overall survival were comparable between the 2 techniques.

Outcomes in robot-assisted partial nephrectomy for imperative vs elective indications.

OBJECTIVES: To assess and compare peri-operative outcomes of patients undergoing robot-assisted partial nephrectomy (RAPN) for imperative vs elective indications. PATIENT AND METHODS: We retrospectively reviewed a multinational database of 3802 adults who underwent RAPN for elective and imperative indications. Laparoscopic or open partial nephrectomy (PN) were excluded. Baseline data for age, gender, body mass index, American Society of Anaesthesiologists score and PADUA score were examined. Patients undergoing RAPN for an imperative indication were matched to those having surgery for an elective indication using propensity scores in a 1:3 ratio. Primary outcomes included organ ischaemic time, operating time, estimated blood loss (EBL), rate of blood transfusions, Clavien-Dindo complications, conversion to radical nephrectomy (RN) and positive surgical margin (PSM) status. RESULTS: After propensity-score matching for baseline variables, a total of 304 patients (76 imperative vs 228 elective indications) were included in the final analysis. No significant differences were found between groups for ischaemia time (19.9 vs 19.8 min; P = 0.94), operating time (186 vs 180 min; P = 0.55), EBL (217 vs 190 mL; P = 0.43), rate of blood transfusions (2.7% vs 3.7%; P = 0.51), or Clavien-Dindo complications (P = 0.31). A 38.6% (SD 47.9) decrease in Day-1 postoperative estimated glomerular filtration rate was observed in the imperative indication group and an 11.3% (SD 45.1) decrease was observed in the elective indication group (P < 0.005). There were no recorded cases of permanent or temporary dialysis. There were no conversions to RN in the imperative group, and seven conversions (5.6%) in the elective group (P = 0.69). PSMs were seen in 1.4% (1/76) of the imperative group and in 3.3% of the elective group (7/228; P = 0.69). CONCLUSION: We conclude that RAPN is feasible and safe for imperative indications and demonstrates similar outcomes to those achieved for elective indications.

Predicting intra-operative and postoperative consequential events using machine-learning techniques in patients undergoing robot-assisted partial nephrectomy: a Vattikuti Collective Quality Initiative database study.

OBJECTIVE: To predict intra-operative (IOEs) and postoperative events (POEs) consequential to the derailment of the ideal clinical course of patient recovery. MATERIALS AND METHODS: The Vattikuti Collective Quality Initiative is a multi-institutional dataset of patients who underwent robot-assisted partial nephectomy for kidney tumours. Machine-learning (ML) models were constructed to predict IOEs and POEs using logistic regression, random forest and neural networks. The models to predict IOEs used patient demographics and preoperative data. In addition to these, intra-operative data were used to predict POEs. Performance on the test dataset was assessed using area under the receiver-operating characteristic curve (AUC-ROC) and area under the precision-recall curve (PR-AUC). RESULTS: The rates of IOEs and POEs were 5.62% and 20.98%, respectively. Models for predicting IOEs were constructed using data from 1690 patients and 38 variables; the best model had an AUC-ROC of 0.858 (95% confidence interval [CI] 0.762, 0.936) and a PR-AUC of 0.590 (95% CI 0.400, 0.759). Models for predicting POEs were trained using data from 1406 patients and 59 variables; the best model had an AUC-ROC of 0.875 (95% CI 0.834, 0.913) and a PR-AUC 0.706 (95% CI, 0.610, 0.790). CONCLUSIONS: The performance of the ML models in the present study was encouraging. Further validation in a multi-institutional clinical setting with larger datasets would be necessary to establish their clinical value. ML models can be used to predict significant events during and after surgery with good accuracy, paving the way for application in clinical practice to predict and intervene at an opportune time to avert complications and improve patient outcomes.

Artificial intelligence and robotic surgery: current perspective and future directions.

PURPOSE OF REVIEW: This review aims to draw a road-map to the use of artificial intelligence in an era of robotic surgery and highlight the challenges inherent to this process. RECENT FINDINGS: Conventional mechanical robots function by transmitting actions of the surgeon's hands to the surgical target through the tremor-filtered movements of surgical instruments. Similarly, the next iteration of surgical robots conform human-initiated actions to a personalized surgical plan leveraging 3D digital segmentation generated prior to surgery. The advancements in cloud computing, big data analytics, and artificial intelligence have led to increased research and development of intelligent robots in all walks of human life. Inspired by the successful application of deep learning, several surgical companies are joining hands with tech giants to develop intelligent surgical robots. We, hereby, highlight key steps in the handling and analysis of big data to build, define, and deploy deep-learning models for building autonomous robots. SUMMARY: Despite tremendous growth of autonomous robotics, their entry into the operating room remains elusive. It is time that surgeons actively collaborate for the development of the next generation of intelligent robotic surgery.

Urological implications of SARS CoV-19.

INTRODUCTION: The novel coronavirus disease 2019 (COVID-19), pandemic has afflicted > 3.3 million people around the world since December 2019. Though, more than 1000 publications have appeared in scientific journals addressing a plethora of questions, there is a considerable hiatus in understanding of the behavior and natural history of the virus and its impact on urology. Also, a modified approach is the need of hour in taking care of patients as urologists should safeguard their teams, families, and patients. MATERIAL AND METHODS: The authors have used guidelines from USA, Canada, UK, Europe and India for making recommendations to help urologist define their own policies that may have to be fine-tuned on the basis of continued and evolving challenges they would encounter and the local resources at their disposal. RESULTS: COVID-19 do effect genitourinary system from kidney to testis. The authors provide scientific basis to urologists to help identify patients by remote consultation who are likely to be harmed by coming to the hospital, and not to miss those who need hospitalization for diagnostic or therapeutic interventions. There is uncompromised need of specific precautions during surgery to safe guard the surgeon and his team along with the patient. CONCLUSIONS: Urological operations during COVID-19 pandemic should be limited to emergency cases during the acute phase with an exit strategy planned in a staggered manner, based on the scientific risk stratification. Telemedicine (e-clinics or virtual clinics) would help achieve the goal of risk stratification.

'Trifecta' outcomes of robot-assisted partial nephrectomy in solitary kidney: a Vattikuti Collective Quality Initiative (VCQI) database analysis.

OBJECTIVES: To analyse the outcomes of robot-assisted partial nephrectomy (RAPN) in patients with a solitary kidney in a large multi-institutional database. PATIENTS AND METHODS: In all, 2755 patients in the Vattikuti Collective Quality Initiative database underwent RAPN by 22 surgeons at 14 centres in nine countries. Of these patients, 74 underwent RAPN with a solitary kidney between 2007 and 2016. We retrospectively analysed the functional and oncological outcomes of these 74 patients. A 'trifecta' of outcomes was assessed, with trifecta defined as a warm ischaemia time (WIT) of <20 min, negative surgical margins, and no complications intraoperatively or within 3 months of RAPN. RESULTS: All 74 patients underwent RAPN successfully with one conversion to radical nephrectomy. The median (interquartile range [IQR]) operative time was 180 (142-230) min. Early unclamping was used in 11 (14.9%) patients and zero ischaemia was used in 12 (16.2%). Trifecta outcomes were achieved in 38 of 66 patients (57.6%). The median (IQR) WIT was 15.5 (8.75-20.0) min for the entire cohort. The overall complication rate was 24.1% and the rate of Clavien-Dindo grade ≤II complications was 16.3%. Positive surgical margins were present in four cases (5.4%). The median (IQR) follow-up was 10.5 (2.12-24.0) months. The median drop in estimated glomerular filtration rate at 3 months was 7.0 mL/min/1.72 m2 (11.01%). CONCLUSION: Our findings suggest that RAPN is a safe and effective treatment option for select renal tumours in solitary kidneys in terms of a trifecta of negative surgical margins, WIT of <20 min, and low operative and perioperative morbidity.

Robot-assisted partial nephrectomy in cystic tumours: analysis of the Vattikuti Global Quality Initiative in Robotic Urologic Surgery (GQI-RUS) database.

OBJECTIVE: To evaluate the outcomes of robot-assisted partial nephrectomy (RAPN) in cystic tumours, analysing a large, multi-institutional, retrospective series of RAPN, as limited data are available about the outcome of RAPN in cystic tumours. PATIENTS AND METHODS: We evaluated 465 patients who received RAPN for either cystic or solid tumours from 2010 to 2013 and included in the multi-institutional, retrospective Vattikuti Global Quality Initiative in Robotic Urologic Surgery (GQI-RUS) database. Univariable and multivariable linear and logistic regression models addressed the association of cystic tumours with perioperative outcomes. RESULTS: In all, 54 (12%) tumours were cystic. Cystic tumours were associated with significantly lower operative time (t -3.9; P < 0.001), once adjusted for the effect of covariates, whereas blood loss and warm ischaemia time were similar. Postoperative any grade complications were recorded in 66 solid (16%) and nine cystic (17%) tumours (P = 0.08). In multivariable analysis, cystic tumours were not associated with a significantly lower risk of any grade postoperative complications [odds ratio (OR) 0.9; P = 0.8]. Similarly, presence of tumours with cystic features was not associated with a significantly different risk of high-grade postoperative complications (OR 2.2; P = 0.1). Prevalence of cancer histology and positive surgical margin rates were similar in cystic and solid tumours. Cystic tumours were not associated with significantly different postoperative estimated glomerular filtration rate (t 0.4; P = 0.7), once adjusted for the effect of covariates. CONCLUSIONS: RAPN can be performed in cystic renal tumours with perioperative, pathological, and functional outcomes similar to those achievable in solid tumours.

Robot-assisted hepatic mobilization and control of suprahepatic infradiaphragmatic inferior vena cava for level 3 vena caval thrombectomy: An IDEAL stage 0 study.

Robot-assisted level 1/2 inferior vena caval (IVC) thrombectomy techniques have been recently described for clinical use. Following the IDEAL recommendations on safe surgical innovation, we here describe a robotic approach for level 3 IVC thrombectomy in fresh frozen cadavers (IDEAL stage 0). In all cadavers (n = 3), hepatic mobilization with control of short hepatic veins, contralateral renal vein, infrarenal IVC and suprahepatic-infradiaphragmatic IVC could be achieved successfully, without converting to open surgery. Clinical feasibility of our technique remains to be tested.

Minimally invasive renal autotransplantation.

Minimally invasive renal allotransplantation techniques have been recently described; reported benefits include reduced morbidity/complications. These benefits have been successfully adapted for minimally invasive renal autotransplantation, however, in a non-oncological setting. We, here, describe a novel alternative robot-assisted renal autotransplantation technique, utilizing GelPOINT, which by permitting ex vivo graft examination and surgery might allow further broadening of indications for minimally-invasive renal autotransplantation, to include complex oncological renal/ureteral lesions. Future studies are needed to evaluate the utility of these techniques.

Robotic renal transplantation: Current status.

INTRODUCTION: Kidney transplantation (KT) has traditionally been performed by open renal transplantation, but recently, a few groups including our own have described a minimally invasive approach to KT. We aim to discuss the current status of robotic kidney transplantation (RKT) and describe our technique of RKT with regional hypothermia. MATERIAL AND METHODS: We used the search terms "minimally invasive" OR "robotic" OR "robot assisted" AND "kidney transplantation." Papers written in English and concerning technical and/or clinical outcomes following minimally invasive kidney transplantation were selected. Three hundred and eighteen unique articles were retrieved and nine were relevant. Comparative outcomes data following RKT with regional hypothermia versus open KT (OKT) from our own group were also included. FINDINGS: Nine papers, so far, have evaluated the role of robotic approach in KT and have conclusively established the feasibility, safety, and reproducibility of RKT, although these studies have been performed by experienced robotic surgeons/teams. The contemporary published series note that rejection rates were similar in RKT and OKT patients. Mean serum creatinine at 6 months in RKT and OKT patients was equivalent, across the three series. Most of the studies also note a dramatic reduction in the wound-related complication rates. CONCLUSION: RKT appears to be a safe surgical alternative to the standard open approach of KT. RKT is associated with reduced postoperative pain, analgesic requirement, and better cosmesis. RKT, although in its infancy, appears to be associated with lower complication rates.

Robotic surgical skill acquisition: What one needs to know?

Robotic surgery has been eagerly adopted by patients and surgeons alike in the field of urology, over the last decade. However, there is a lack of standardization in training curricula and accreditation guidelines to ensure surgeon competence and patient safety. Accordingly, in this review, we aim to highlight 'who' needs to learn 'what' and 'how', to become competent in robotic surgery. We demonstrate that both novice and experienced open surgeons require supervision and mentoring during the initial phases of robotic surgery skill acquisition. The experienced open surgeons possess domain knowledge, however, need to acquire technical knowledge under supervision (either in simulated or clinical environment) to successfully transition to robotic surgery, whereas, novice surgeons need to acquire both domain as well as technical knowledge to become competent in robotic surgery. With regard to training curricula, a variety of training programs such as academic fellowships, mini-fellowships, and mentored skill courses exist, and cater to the needs and expectations of postgraduate surgeons adequately. Fellowships provide the most comprehensive training, however, may not be suitable to all surgeon-learners secondary to the long-term time commitment. For these surgeon-learners short-term courses such as the mini-fellowships or mentored skill courses might be more apt. Lastly, with regards to credentialing uniformity in criteria regarding accreditation is lacking but earnest efforts are underway. Currently, accreditation for competence in robotic surgery is institutional specific.

Robotic kidney transplantation with intraoperative regional hypothermia.

OBJECTIVE: To describe a novel and reproducible technique of robotic kidney transplantation (RKT) that requires no repositioning, and permits intraoperative regional hypothermia. PATIENTS AND METHODS: A GelPOINT™ (Applied Medical, Santa Ranchero, CA, USA) access port was used for delivery of ice-slush and introduction of the graft kidney. The new RKT technique using ice-slush has been performed in 39 patients. RESULTS: At a mean follow-up of 3 months all of the grafts functioned. There was a marked reduction in pain and analgesic requirement compared with patients undergoing open KT, with a propensity towards quicker graft recovery and lower complication rate. CONCLUSION: RKT has been shown to be safe and feasible in patients undergoing living-donor related KT. A prospective trial is underway to assess outcomes definitively.