Screening, identifying, and treating chronic kidney disease: why, who, when, how, and what?

1 in 7 American adults have chronic kidney disease (CKD); a disease that increases risk for CKD progression, cardiovascular events, and mortality. Currently, the US Preventative Services Task Force does not have a screening recommendation, though evidence suggests that screening can prevent progression and is cost-effective. Populations at risk for CKD, such as those with hypertension, diabetes, and age greater than 50 years should be targeted for screening. CKD is diagnosed and risk stratified with estimated glomerular filtration rate utilizing serum creatinine and measuring urine albumin-to-creatinine ratio. Once identified, CKD is staged according to C-G-A classification, and managed with lifestyle modification, interdisciplinary care and the recently expanding repertoire of pharmacotherapy which includes angiotensin converting enzyme inhibitors or angiotensin-II receptor blockers, sodium-glucose-cotransporter-2 inhibitors, and mineralocorticorticoid receptor antagonists. In this paper, we present the why, who, when, how, and what of CKD screening.

Natural Language Processing in Nephrology.

Unstructured data in the electronic health records contain essential patient information. Natural language processing (NLP), teaching a computer to read, allows us to tap into these data without needing the time and effort of manual chart abstraction. The core first step for all NLP algorithms is preprocessing the text to identify the core words that differentiate the text while filtering out the noise. Traditional NLP uses a rule-based approach, applying grammatical rules to infer meaning from the text. Newer NLP approaches use machine learning/deep learning which can infer meaning without explicitly being programmed. NLP use in nephrology research has focused on identifying distinct disease processes, such as CKD, and extraction of patient-oriented outcomes such as symptoms with high sensitivity. NLP can identify patient features from clinical text associated with acute kidney injury and progression of CKD. Lastly, inclusion of features extracted using NLP improved the performance of risk-prediction models compared to models that only use structured data. Implementation of NLP algorithms has been slow, partially hindered by the lack of external validation of NLP algorithms. However, NLP allows for extraction of key patient characteristics from free text, an infrequently used resource in nephrology.

Outcomes Assessment of Treating Completely Edentulous Patients with a Fixed Implant-Supported Profile Prosthesis Utilizing a Graftless Approach. Part 1: Clinically Related Outcomes.

PURPOSE: To assess outcomes of treating completely edentulous patients with a fixed implant-supported profile prosthesis utilizing a graftless approach for the maxilla and for the mandible, with emphasis on clinically related outcomes, specifically implant and prosthesis survival. MATERIALS AND METHODS: This was a retrospective study with the following inclusion criteria: completely edentulous patients rehabilitated with a fixed implant-supported profile denture utilizing a graftless approach. Patients fulfilling the inclusion criteria were asked to participate in the study during their follow-up visits, and hence a consecutive sampling strategy was used. Data regarding implant and prosthesis cumulative survival rates (CSRs) were gathered and calculated. RESULTS: Thirty-four patients were identified with a total of 220 implants placed. An overall CSR of 98.2% was recorded with an observation of up to 10 years. For tilted, axial, and zygomatic implants, CSRs of 96.9%, 98.0%, and 100%, respectively, were observed for up to 10 years. For provisional prostheses, CSRs of 92.3% at 1 year, and 84.6% at 2 years were observed. For final prostheses, a CSR of 93.8% was observed at 10 years. CONCLUSION: The results suggest that treating completely edentulous patients with a fixed profile prosthesis utilizing a graftless approach in the maxilla and the mandible can be a reliable treatment option.

Surgical Management of Advanced and Metastatic Renal Cell Carcinoma: A Multidisciplinary Approach.

The past decade has seen a rapid proliferation in the number and types of systemic therapies available for renal cell carcinoma. However, surgery remains an integral component of the therapeutic armamentarium for advanced and metastatic kidney cancer. Cytoreductive surgery followed by adjuvant cytokine-based immunotherapy (predominantly high-dose interleukin 2) has largely given way to systemic-targeted therapies. Metastasectomy also has a role in carefully selected patients. Additionally, neoadjuvant systemic therapy may increase the feasibility of resecting the primary tumor, which may be beneficial for patients with locally advanced or metastatic disease. Several prospective trials examining the role of adjuvant therapy are underway. Lastly, the first immune checkpoint inhibitor was approved for metastatic renal cell carcinoma (mRCC) in 2015, providing a new treatment mechanism and new opportunities for combining systemic therapy with surgery. This review discusses current and historical literature regarding the surgical management of patients with advanced and mRCC and explores approaches for optimizing patient selection.