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

Author

Sharma, G, Shah, M, Ahluwalia, P, Dasgupta, P, Challacombe, BJ, Bhandari, M, Ahlawat, R, Rawal, S, Buffi, NM, Sivaraman, A, Porter, JR, Rogers, C, Mottrie, A, Abaza, R, Rha, KH, Moon, D, Thyavihally, YB, Parekh, DJ, Capitanio, U, Maes, KK, Porpiglia, F, Turkeri, L, Gautam, G, Sharma, G, Shah, M, Ahluwalia, P, Dasgupta, P, Challacombe, BJ, Bhandari, M, Ahlawat, R, Rawal, S, Buffi, NM, Sivaraman, A, Porter, JR, Rogers, C, Mottrie, A, Abaza, R, Rha, KH, Moon, D, Thyavihally, YB, Parekh, DJ, Capitanio, U, Maes, KK, Porpiglia, F, Turkeri, L, and Gautam, G

Abstract

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.

Published
2022

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

Author

Tan, J-LS, Sathianathen, N, Cumberbatch, M, Dasgupta, P, Mottrie, A, Abaza, R, Rha, KH, Yuvaraja, TB, Parekh, DJ, Capitanio, U, Ahlawat, R, Rawal, S, Buffi, NM, Sivaraman, A, Maes, KK, Gautham, G, Porpiglia, F, Turkeri, L, Bhandari, M, Challacombe, B, Porter, JR, Rogers, CR, Moon, DA, Tan, J-LS, Sathianathen, N, Cumberbatch, M, Dasgupta, P, Mottrie, A, Abaza, R, Rha, KH, Yuvaraja, TB, Parekh, DJ, Capitanio, U, Ahlawat, R, Rawal, S, Buffi, NM, Sivaraman, A, Maes, KK, Gautham, G, Porpiglia, F, Turkeri, L, Bhandari, M, Challacombe, B, Porter, JR, Rogers, CR, and Moon, DA

Abstract

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 indicat

Published
2021

9. Utilization of pelvic lymph node dissection in patients undergoing robot-assisted radical prostatectomy in India versus the United States - A Vattikuti Collective Quality Initiative database analysis

Author

Abdollah, F., Arora, S., Jindal, T., Gild, P., Sood, A., Yuvaraja, T., Ahlawat, R., Gupta, N., Bhandari, M., and Menon, M.

Subjects
Prostatectomy -- Usage -- Safety and security measures -- Methods, Epidemiology -- Analysis, Prostate cancer -- Care and treatment -- Risk factors, Lymph nodes -- Health aspects -- Analysis, Health
Abstract

Byline: F. Abdollah, S. Arora, T. Jindal, P. Gild, A. Sood, T. Yuvaraja, R. Ahlawat, N. Gupta, M. Bhandari, M. Menon BACKGROUND: The utilization and extent of pelvic lymph node [...]

Published
2017

17. Predicting intraoperative complications and 30-days morbidity using machine learning techniques for patients undergoing robotic partial nephrectomy (RPN)

Author

Bhandari, M., primary, Nallabasannagari, A.R., additional, Reddiboina, M., additional, Porter, J., additional, Jeong, W., additional, Mottrie, A., additional, Dasgupta, P., additional, Challacombe, B., additional, Abaza, R., additional, Rha, K.H., additional, Parekh, D., additional, Ahlawat, R., additional, Capitanio, U., additional, Yuvaraja, T., additional, Rawal, S., additional, Moon, D., additional, Buffi’s, N., additional, Sivaraman, A., additional, Maes, K., additional, Porpiglia, F., additional, Gautam, G., additional, Turkeri, L., additional, Preethi, P., additional, Menon, M., additional, and Rogers, C., additional

Published
2020
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20. 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

Author

Bhandari, M, Nallabasannagari, AR, Reddiboina, M, Porter, JR, Jeong, W, Mottrie, A, Dasgupta, P, Challacombe, B, Abaza, R, Rha, KH, Parekh, DJ, Ahlawat, R, Capitanio, U, Yuvaraja, TB, Rawal, S, Moon, DA, Buffi, NM, Sivaraman, A, Maes, KK, Porpiglia, F, Gautam, G, Turkeri, L, Meyyazhgan, KR, Patil, P, Menon, M, Rogers, C, Bhandari, M, Nallabasannagari, AR, Reddiboina, M, Porter, JR, Jeong, W, Mottrie, A, Dasgupta, P, Challacombe, B, Abaza, R, Rha, KH, Parekh, DJ, Ahlawat, R, Capitanio, U, Yuvaraja, TB, Rawal, S, Moon, DA, Buffi, NM, Sivaraman, A, Maes, KK, Porpiglia, F, Gautam, G, Turkeri, L, Meyyazhgan, KR, Patil, P, Menon, M, and Rogers, C

Abstract

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.

Published
2020

22. PT186 - Predicting intraoperative complications and 30-days morbidity using machine learning techniques for patients undergoing robotic partial nephrectomy (RPN)

Author

Bhandari, M., Nallabasannagari, A.R., Reddiboina, M., Porter, J., Jeong, W., Mottrie, A., Dasgupta, P., Challacombe, B., Abaza, R., Rha, K.H., Parekh, D., Ahlawat, R., Capitanio, U., Yuvaraja, T., Rawal, S., Moon, D., Buffi’s, N., Sivaraman, A., Maes, K., Porpiglia, F., Gautam, G., Turkeri, L., Preethi, P., Menon, M., and Rogers, C.

Published
2020
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23. PADUA and RENAL nephrometry scores correlate with perioperative outcomes of robot-assisted partial nephrectomy: analysis of the Vattikuti Global Quality Initiative in Robotic Urologic Surgery (GQI-RUS) database

Author

Schiavina, R, Novara, G, Borghesi, M, Ficarra, V, Ahlawat, R, Moon, DA, Porpiglia, F, Challacombe, BJ, Dasgupta, P, Brunocilla, E, La Manna, G, Volpe, A, Verma, H, Martorana, G, Mottrie, A, Schiavina, R, Novara, G, Borghesi, M, Ficarra, V, Ahlawat, R, Moon, DA, Porpiglia, F, Challacombe, BJ, Dasgupta, P, Brunocilla, E, La Manna, G, Volpe, A, Verma, H, Martorana, G, and Mottrie, A

Abstract

OBJECTIVES: To evaluate and compare the correlations between Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) and R.E.N.A.L. [Radius (tumour size as maximal diameter), Exophytic/endophytic properties of the tumour, Nearness of tumour deepest portion to the collecting system or sinus, Anterior (a)/posterior (p) descriptor and the Location relative to the polar line] nephrometry scores and perioperative outcomes and postoperative complications in a multicentre, international series of patients undergoing robot-assisted partial nephrectomy (RAPN) for masses suspicious for renal cell carcinoma (RCC). PATIENTS AND METHODS: We retrospectively evaluated the clinical records of patients who underwent RAPN between 2010 and 2013 for clinical N0M0 renal tumours in four international centres that completed all the data required for the Vattikuti Global Quality Initiative in Robotic Urologic Surgery (GQI-RUS) database. All patients underwent preoperative computed tomography or magnetic resonance imaging to define the clinical stage and anatomical characteristics of the tumours. PADUA and R.E.N.A.L. scores were retrospectively assessed in each centre. Univariate and multivariate analyses were used to evaluate the correlations between age, gender, Charlson comorbidity index, clinical tumour size, PADUA and R.E.N.A.L. complexity group categories and warm ischaemia time (WIT) of >20 min, urinary calyceal system closure, and grade of postoperative complications. RESULTS: Overall, 277 patients were evaluated. The median (interquartile range) tumour size was 33.0 (22.0-43.0) mm. The median PADUA and R.E.N.A.L. scores were eight and seven, respectively; 112 (40.4%), 86 (31.0%) and 79 (28.5%) patients were classified in the low-, intermediate- or high-complexity group according to PADUA score, while 118 (42.5%), 139 (50.1%) and 20 (7.2%) were classified in the low-, intermediate- or high-complexity group according to R.E.N.A.L. score, respectively. Both nephrometry tool

Published
2017

24. From Incompatibility to Accommodation – The Journey of Taming ‘Self’: Guide to Perioperative Management of Solid Organ Transplantation across ABO and Rh Barrier

Author

Mehta Y, J. Das, GhoshP, Ahlawat R, S. Khanna, S. Kumar, Jha P, and Kher

Subjects
Nephrology, medicine.medical_specialty, education.field_of_study, business.industry, Population, Intensivist, Perioperative, Organ transplantation, End stage renal disease, Surgery, Transplantation, Internal medicine, ABO blood group system, medicine, Intensive care medicine, education, business
Abstract

The fate of every organ allografting is ‚rejection’ if nothing is done to halt this natural process. The risks of ‘hyperacute’ ‘accelerated acute’ and ‘acute’ rejection have restricted scientists and clinicians over the years in performing organ transplantationwithin ABO blood group matched pairs only. Subsequent to the development in the field of immunosuppression, ABO incompatible transplants have gained momentum to incorporate a significant population of end stage renal disease patients with incompatible blood group donors into the transplant program. However, optimizing the recipient for transplantation and subsequent accommodation with optimal graft function without tilting to the much easier path of rejection is a challenge. Although most of these steps come under the domain of the nephrologist, it is crucial that as the perioperative physician of a very high stake life modifying surgery, the anesthesiologist, surgeons as well as the intensivist should understand the complex process of desensitization, patient preparation and perioperative management for the best outcome. Lack of understanding about a couple of crucial considerations can jeopardize the delicate balance of immunotolerance and can prove catastrophic. The article highlights these considerations important for the perioperative clinicians along with a description of first 20 patients of blood group incompatible renal transplantation at our Institute.

Published
2015
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41. Transplantation - clinical studies II

Author

Marques, I. B., primary, Silva, R. d. M., additional, Moraes, C. E., additional, Azevedo, L. S., additional, Nahas, W. C., additional, David-Neto, E., additional, Furmanczyk-Zawiska, A., additional, Baczkowska, T., additional, Chmura, A., additional, Szmidt, J., additional, Durlik, M., additional, Joslin, J., additional, Blaker, P., additional, White, B., additional, Marinaki, A., additional, Sanderson, J., additional, Goldsmith, D. J., additional, Medani, S., additional, Traynor, C., additional, Mohan, P., additional, Little, D., additional, Conlon, P., additional, Molina, M., additional, Gonzalez, E., additional, Gutierrez, E., additional, Sevillano, A., additional, Polanco, N., additional, Morales, E., additional, Hernandez, A., additional, Praga, M., additional, Morales, J. M., additional, Andres, A., additional, Park, S. J., additional, Kim, T. H., additional, Kim, Y. W., additional, Kim, Y. H., additional, Kang, S. W., additional, Kujawa-Szewieczek, A., additional, Szotowska, M., additional, Kuczera, P., additional, Chudek, J., additional, Wiecek, A., additional, Kolonko, A., additional, Mahrova, A., additional, Svagrova, K., additional, Bunc, V., additional, Stollova, M., additional, Teplan, V., additional, Hundt, F., additional, van Heteren, P., additional, Woitas, R., additional, Cavallo, M. C., additional, Sepe, V., additional, Conte, F., additional, Albrizio, P., additional, Bottazzi, A., additional, Geraci, P. M., additional, Alpay, N., additional, Gumber, M. R., additional, Kute, V. B., additional, Vanikar, A. V., additional, Patel, H. V., additional, Shah, P. R., additional, Engineer, D. P., additional, Trivedi, H. L., additional, Golebiewska, J. E., additional, Debska-Slizien, A., additional, Rutkowski, B., additional, Matias, P., additional, Martins, A. R., additional, Raposo, L., additional, Jorge, C., additional, Weigert, A., additional, Birne, R., additional, Bruges, M., additional, Adragao, T., additional, Almeida, M., additional, Mendes, M., additional, Machado, D., additional, Masin-Spasovska, J., additional, Dohcev, S., additional, Stankov, O., additional, Stavridis, S., additional, Saidi, S., additional, Dejanova, B., additional, Rambabova-Busletic, I., additional, Dejanov, P., additional, Spasovski, G., additional, Nho, K. W., additional, Han, D. J., additional, Park, S.-K., additional, Kim, S. B., additional, Fenoglio, R., additional, Lazzarich, E. E., additional, Cagna, D., additional, Cena, T., additional, Conti, N., additional, Quaglia, M., additional, Radin, E., additional, Izzo, C., additional, Stratta, P., additional, Oh, I. H., additional, Park, J.-S., additional, Lee, C. H., additional, Kang, C. M., additional, Kim, G.-H., additional, Leone, F., additional, Lofaro, D., additional, Gigliotti, P., additional, Lupinacci, S., additional, Toteda, P., additional, Vizza, D., additional, Perri, A., additional, Papalia, T., additional, Bonofiglio, R., additional, di Loreto, P., additional, de Silvestro, L., additional, Montanaro, D., additional, Martino, F., additional, Sandrini, S., additional, Minetti, E., additional, Cabiddu, G., additional, Yildirim, T., additional, Yilmaz, R., additional, Turkmen, E., additional, Abudalal, A., additional, Altindal, M., additional, Ertoy-Baydar, D., additional, Erdem, Y., additional, Panuccio, V., additional, Tripepi, R., additional, Parlongo, G., additional, Versace, M. C., additional, Politi, R., additional, Zoccali, C., additional, Mallamaci, F., additional, Porrini, E., additional, Silva, I., additional, Diaz, J., additional, Ibernon, M., additional, Moreso, F., additional, Benitez, R., additional, Delgado Mallen, P., additional, Osorio, J., additional, Lauzurica, R., additional, Torres, A., additional, Ersoy, A., additional, Koca, N., additional, Gullu Koca, T., additional, Kirhan, E., additional, Sarandol, E., additional, Ersoy, C., additional, Dirican, M., additional, Milne, J., additional, Suter, V., additional, Mikhail, A., additional, Akalin, H., additional, Dizdar, O., additional, Pascual, J., additional, Torio, A., additional, Garcia, C., additional, Hernandez, J., additional, Perez-Saez, M. J., additional, Mir, M., additional, Anna, F., additional, Crespo, M., additional, Carta, P., additional, Zanazzi, M., additional, Antognoli, G., additional, Di Maria, L., additional, Caroti, L., additional, Ray, D. S., additional, Mukherjee, K., additional, Bohidar, N. P., additional, Pattanaik, A., additional, Das, P., additional, Thukral, S., additional, Kimura, T., additional, Yagisawa, T., additional, Ishikawa, N., additional, Sakuma, Y., additional, Fujiwara, T., additional, Nukui, A., additional, Gavela, E. E., additional, Sancho, A. A., additional, Kanter, J. J., additional, Avila, A. A., additional, Beltran, S. S., additional, Pallardo, L. L., additional, Dawoud, F. G., additional, Aithal, V., additional, Majernikova, M., additional, Rosenberger, J., additional, Prihodova, L., additional, Nagyova, I., additional, Jarcuskova, M., additional, Roland, R., additional, Groothoff, J. W., additional, van Dijk, J. P., additional, van Agteren, M., additional, de Weerd, A., additional, van de Wetering, J., additional, IJzermans, J., additional, Betjes, M., additional, Weimar, W., additional, Popoola, J., additional, Reed, A., additional, Tavarro, R., additional, Chryssanthopoulou, C., additional, MacPhee, I., additional, Mayor, M., additional, Franco, S., additional, Jara, P., additional, Ayala, R., additional, Orue, M. G., additional, Martinez, A., additional, Martinez, M., additional, Wasmouth, N., additional, Arik, G., additional, Yasar, A., additional, Yilmaz, S., additional, Arici, M., additional, Bihari Bansal, S., additional, Pokhariyal, S., additional, Jain, S., additional, Sethi, S., additional, Ahlawat, R., additional, Kher, V., additional, Martins, L. S., additional, Aguiar, P., additional, Dias, L., additional, Fonseca, I., additional, Henriques, A. C., additional, Cabrita, A., additional, Davide, J., additional, Sparkes, T. M., additional, Trofe-Clark, J., additional, Reese, P. P., additional, Jakobowski, D., additional, Goral, S., additional, Doll, S. L., additional, Abt, P. L., additional, Sawinski, D., additional, MBloom, R. D., additional, Knap, B., additional, Lukac, J., additional, Lukin, M., additional, Majcen, I., additional, Pavlovec, F., additional, Kandus, A., additional, Bren, A. F., additional, Kong, J. M., additional, Jeong, J. H., additional, Ahn, J., additional, Lee, D. R., additional, Son, S. H., additional, Kim, B. C., additional, Choi, W. Y., additional, Whang, E. J., additional, Czajka, B., additional, Malgorzewicz, S., additional, Panizo, N., additional, Rengel, M. A., additional, Vega, A., additional, Abad, S., additional, Tana, L., additional, Arroyo, D., additional, Rodriguez-Ferrero, M., additional, Perez de Jose, A., additional, Lopez-Gomez, J. M., additional, Koutroutsos, K., additional, Sackey, J., additional, Paolini, L., additional, Ramkhelawon, R., additional, Chowrimootoo, M., additional, Whelan, D., additional, Slatinska, J., additional, Honsova, E., additional, Wohlfahrtova, M., additional, Slimackova, E., additional, Rajnochova, S. B., additional, Viklicky, O., additional, Yankovoy, A., additional, Smith, I. S. J., additional, Wylie, E., additional, Ruiz-Esteban, P., additional, Lopez, V., additional, Garcia-Frias, P., additional, Cabello, M., additional, Gonzalez-Molina, M., additional, Vozmediano, C., additional, Hernandez, D., additional, Pavlovic, J., additional, Radivojevic, D., additional, Lezaic, V., additional, Simic-Ogrizovic, S., additional, Lausevic, M., additional, Naumovic, R., additional, Sakhuja, V., additional, Gundlapalli, S., additional, Rathi, M., additional, Jha, V., additional, Kohli, H. S., additional, Sharma, A., additional, Minz, M., additional, Nimgirova, A., additional, Esayan, A., additional, Kayukov, I., additional, Zuyeva, E., additional, Bilen, Y., additional, Cankaya, E., additional, Keles, M., additional, Gulcan, E., additional, Turkeli, M., additional, Albayrak, B., additional, Uyanik, A., additional, Yildirim, R., additional, Molitor, N., additional, Praktiknjo, M., additional, Abeygunaratne, T. N., additional, Balasubramanian, S., additional, Baker, R., additional, Nicholson, T., additional, Toprak, O., additional, Sari, Y., additional, Keceli, S., additional, Kurt, H., additional, Rocha, A., additional, Malheiro, J., additional, Pedroso, S., additional, Henriques, A., additional, Nihei, C., additional, Bacelar Marques, I., additional, Seguro, C. A., additional, Mate, G., additional, Martin, N., additional, Colon, L., additional, Casellas, L., additional, Garangou, D., additional, de la Torre, M., additional, Torguet, P., additional, Garcia, I., additional, Calabia, J., additional, Valles, M., additional, Pruthi, R., additional, Calestani, M., additional, Leydon, G., additional, Ravanan, R., additional, Roderick, P., additional, Korkmaz, S., additional, and Gulten, S., additional

Published
2013
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42. Renal transplantation across ABO barrier

Author

Gupta, PN, primary, Pokhariyal, S, additional, Bansal, S, additional, Jain, S, additional, Saxena, V, additional, Jain, M, additional, Jha, P, additional, Sethi, SK, additional, Ghosh, P, additional, Ahlawat, R, additional, Kher, V, additional, Sharma, R, additional, and Tewari, A, additional

Published
2013
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