Machine learning progressive CKD risk prediction model is associated with CKD-mineral bone disorder.

Background: Recently, we developed the machine learning (ML)-based Progressive CKD Risk Classifier (PCRC), which accurately predicts CKD progression within 5 years. While its performance is robust, it is unknown whether PCRC categorization is associated with CKD-mineral bone disorder (CKD-MBD), a critical, yet under-recognized, downstream consequence. Therefore, we aimed to 1) survey real-world testing utilization data for CKD-MBD and 2) evaluate ML-based PCRC categorization with CKD-MBD.

CKD Progression Prediction in a Diverse US Population: A Machine-Learning Model.

Rationale & Objective: Chronic kidney disease (CKD) is a major cause of morbidity and mortality. To date, there are no widely used machine-learning models that can predict progressive CKD across the entire disease spectrum, including the earliest stages. The objective of this study was to use readily available demographic and laboratory data from Sonic Healthcare USA laboratories to train and test the performance of machine learning-based predictive risk models for CKD progression.

Social Media Engagement at Academic Conferences: Report of the Association of Pathology Chairs 2018 and 2019 Annual Meeting Social Media Committee.

The use of social media at academic conferences is expanding, and platforms such as Twitter are used to share meeting content with the world. Pathology conferences are no exception, and recently, pathology organizations have promoted social media as a way to enhance meeting exposure. A social media committee was formed ad hoc to implement strategies to enhance social media involvement and coverage at the 2018 and 2019 annual meetings of the Association of Pathology Chairs.

Gross Dissection Time Values of Pathologists' Assistants Using Standardized Metrics.

Objectives: A validated and objective method to quantify the gross dissection time of pathologists' assistants (PAs) does not exist. We propose a method to calculate standardized work units (dissection time values [DTVs]) to monitor PA productivity.

Methods: The Current Procedural Terminology system specifies six levels of specimen complexity encompassing 176 unique specimen types.

Active Monitoring and Feedback to Improve Blood Culture Fill Volumes and Positivity Across a Large Integrated Health System.

Background: The sensitivity of blood cultures increases with the volume of blood collected. However, hospitals face challenges in collecting adequate volume, and underfilled blood bottles are ubiquitous.

Methods: Blood bottle fill volumes were measured using an automated monitoring system across multiples sites (10 hospitals, 3 laboratories) within a large suburban/urban health system.

Impact of Daily Electronic Laboratory Alerting on Early Detection and Clinical Documentation of Acute Kidney Injury in Hospital Settings.

Acute kidney injury, especially early-stage disease, is a common hospital comorbidity requiring timely recognition and treatment. We investigated the effect of daily laboratory alerting of patients at risk for acute kidney injury as measured by documented diagnoses. A quasi-experimental study was conducted at 8 New York hospitals between January 1, 2014, and June 30, 2017.

The Role of the Pathologist in Population Health.

Context.—: As part of its value-based care initiative, the College of American Pathologists has pursued research to better understand the role pathologists can have in population health.

Objectives.

Improving American Healthcare Through "Clinical Lab 2.0": A Project Santa Fe Report.

Project Santa Fe was established both to provide thought leadership and to help develop the evidence base for the valuation of clinical laboratory services in the next era of American healthcare. The participants in Project Santa Fe represent major regional health systems that can operationalize laboratory-driven innovations and test their valuation in diverse regional marketplaces in the United States. We provide recommendations from the inaugural March 2016 meeting of Project Santa Fe.