Yonsei nomogram: A predictive model of new‐onset chronic kidney disease after on‐clamp partial nephrectomy in patients with T1 renal tumors

Raheem, Ali Abdel; Shin, Tae Young; Chang, Kihun; Santok, Glen Denmer; Alenzi, Mohamed Jayed; Yoon, Young Eun; Ham, Won Sik; Han, Woong Kyu; Choi, Young Deuk; Rha, Koon Ho

doi:10.1111/iju.13705

Cited by 13 publications

(16 citation statements)

References 33 publications

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“…As for patients with comorbidities, previous studies showed that those with diabetes mellitus (DM) were more likely to develop CKD after nephrectomy. 16,28,29 While in our study, DM alone was not significantly associated with AKD. CCI is a weighted score for each of the comorbid conditions.…”

Section: Discussioncontrasting

confidence: 64%

“…Previous studies have demonstrated that risk factors such as surgery approach, perioperative eGFR, complications, age, and sex were associated with AKI and CKD postoperatively. 15,16 However, as far as we know, the incidence rate and risk factors for AKD have not been studied and the prediction model for AKD after nephrectomy in RCC patients has not been established.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

<p>Development and Validation of a Nomogram Model to Predict Acute Kidney Disease After Nephrectomy in Patients with Renal Cell Carcinoma</p>

Hu¹,

Li²,

Qiao³

et al. 2020

CMAR

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Section: Discussioncontrasting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

<p>Development and Validation of a Nomogram Model to Predict Acute Kidney Disease After Nephrectomy in Patients with Renal Cell Carcinoma</p>

Hu¹,

Li²,

Qiao³

et al. 2020

CMAR

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“…Second, this study only included surgeries that used minimally invasive laparoscopic or robotic techniques, and not open techniques. One study reported a lower risk of CKD in minimally invasive approaches [ 14 ], whereas others reported a similar risk [ 10 , 13 ]. However, minimally invasive approaches are being used more frequently for RN and PN [ 27 ]; thus, our model may be appropriate for future studies.…”

Section: Discussionmentioning

confidence: 99%

“…Numerous studies have investigated the predictive factors for CKD following RN or PN [ 9 – 16 ], some of which developed predictive models for CKD [ 13 , 14 ]. However, these studies analyzed preoperative and intraoperative factors (such as patient characteristics, preoperative laboratory values, and surgical type or technique) as possible predictors, without including postoperative laboratory values [ 9 – 14 ].…”

Section: Introductionmentioning

confidence: 99%

Predictive models for chronic kidney disease after radical or partial nephrectomy in renal cell cancer using early postoperative serum creatinine levels

Chae

Kim

et al. 2021

J Transl Med

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Background Several predictive factors for chronic kidney disease (CKD) following radical nephrectomy (RN) or partial nephrectomy (PN) have been identified. However, early postoperative laboratory values were infrequently considered as potential predictors. Therefore, this study aimed to develop predictive models for CKD 1 year after RN or PN using early postoperative laboratory values, including serum creatinine (SCr) levels, in addition to preoperative and intraoperative factors. Moreover, the optimal SCr sampling time point for the best prediction of CKD was determined. Methods Data were retrospectively collected from patients with renal cell cancer who underwent laparoscopic or robotic RN (n = 557) or PN (n = 999). Preoperative, intraoperative, and postoperative factors, including laboratory values, were incorporated during model development. We developed 8 final models using information collected at different time points (preoperative, postoperative day [POD] 0 to 5, and postoperative 1 month). Lastly, we combined all possible subsets of the developed models to generate 120 meta-models. Furthermore, we built a web application to facilitate the implementation of the model. Results The magnitude of postoperative elevation of SCr and history of CKD were the most important predictors for CKD at 1 year, followed by RN (compared to PN) and older age. Among the final models, the model using features of POD 4 showed the best performance for correctly predicting the stages of CKD at 1 year compared to other models (accuracy: 79% of POD 4 model versus 75% of POD 0 model, 76% of POD 1 model, 77% of POD 2 model, 78% of POD 3 model, 76% of POD 5 model, and 73% in postoperative 1 month model). Therefore, POD 4 may be the optimal sampling time point for postoperative SCr. A web application is hosted at https://dongy.shinyapps.io/aki_ckd. Conclusions Our predictive model, which incorporated postoperative laboratory values, especially SCr levels, in addition to preoperative and intraoperative factors, effectively predicted the occurrence of CKD 1 year after RN or PN and may be helpful for comprehensive management planning.

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“…Abdel Raheem et al . reported a novel nomogram for new‐onset CKD after PN in patients with T1 renal tumors . This nomogram will play a prominent role in the selection of appropriate therapy and adequate follow up after PN in these patients.…”

mentioning

confidence: 99%

Editorial Comment to Yonsei nomogram: A predictive model of new‐onset chronic kidney disease after on‐clamp partial nephrectomy in patients with T1 renal tumors

Kobayashi

2018

Int J of Urology

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Yonsei nomogram: A predictive model of new‐onset chronic kidney disease after on‐clamp partial nephrectomy in patients with T1 renal tumors

Cited by 13 publications

References 33 publications

<p>Development and Validation of a Nomogram Model to Predict Acute Kidney Disease After Nephrectomy in Patients with Renal Cell Carcinoma</p>

<p>Development and Validation of a Nomogram Model to Predict Acute Kidney Disease After Nephrectomy in Patients with Renal Cell Carcinoma</p>

Predictive models for chronic kidney disease after radical or partial nephrectomy in renal cell cancer using early postoperative serum creatinine levels

Editorial Comment to Yonsei nomogram: A predictive model of new‐onset chronic kidney disease after on‐clamp partial nephrectomy in patients with T1 renal tumors

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