Rare Causes of Hydronephrosis in Adults and Diagnosis Algorithm: Analysis of 100 Cases During 15 Years

Interoperability of phenome-wide multimorbidity patterns: a comparative study of two large-scale EHR systems

Background

Electronic health records (EHR) are increasingly used for studying multimorbidities. However, concerns about accuracy, completeness, and EHRs being primarily designed for billing and administrative purposes raise questions about the consistency and reproducibility of EHR-based multimorbidity research.

Methods

Utilizing phecodes to represent the disease phenome, we analyzed pairwise comorbidity strengths using a dual logistic regression approach and constructed multimorbidity as an undirected weighted graph. We assessed the consistency of the multimorbidity networks within and between two major EHR systems at local (nodes and edges), meso (neighboring patterns), and global (network statistics) scales. We present case studies to identify disease clusters and uncover clinically interpretable disease relationships. We provide an interactive web tool and a knowledge base combining data from multiple sources for online multimorbidity analysis.

Findings

Analyzing data from 500,000 patients across Vanderbilt University Medical Center and Mass General Brigham health systems, we observed a strong correlation in disease frequencies (Kendall's τ = 0.643) and comorbidity strengths (Pearson ρ = 0.79). Consistent network statistics across EHRs suggest similar structures of multimorbidity networks at various scales. Comorbidity strengths and similarities of multimorbidity connection patterns align with the disease genetic correlations. Graph-theoretic analyses revealed a consistent core-periphery structure, implying efficient network clustering through threshold graph construction. Using hydronephrosis as a case study, we demonstrated the network's ability to uncover clinically relevant disease relationships and provide novel insights.

Interpretation

Our findings demonstrate the robustness of large-scale EHR data for studying phenome-wide multimorbidities. The alignment of multimorbidity patterns with genetic data suggests the potential utility for uncovering shared biology of diseases. The consistent core-periphery structure offers analytical insights to discover complex disease interactions. This work also sets the stage for advanced disease modeling, with implications for precision medicine.

Funding

VUMC Biostatistics Development Award, the National Institutes of Health, and the VA CSRD.

Etiology of Hydronephrosis in adults and children: Ultrasonographic Assessment in 233 patients

Objectives:

Hydronephrosis (HN) is dilatation of the collecting system of the kidney due to obstruction of urine outflow. This study intended firstly, to investigate the efficacy of ultrasound (US) imaging to determine the cause of HN, and secondly, to list the causes of HN.

Methods:

In this retrospective study, 233 patients with HN were scanned to determine the cause of the HN in the period from 1^st January 2016 to 31^st October 2017. Categorical results were written as frequencies and percentages.

Results:

Out of 233, 91.41% were adults and 8.58% were children (P<0.001), 66.10% were male and 33.90% were female (P<0.001). In 55.36%, HN was in the right kidney and 44.64% was in the left (P=0.116). Exactly 58% of patients were suffering from grade-2, 21.5% grade-3, 11.6% grade-1, and 8.2% grade-4 HN. US imaging can determine the cause of HN in 70.4% of patients. Kidney or ureteric calculi were the cause of HN in 54.1% of cases, reflux was in 7.3%, and pelviureteric junction (PUJ) stenosis was in 3.9%.

In cases of calculi induced HN, 25.3% of the calculi were in the vesicoureteric (VUJ) junction, 21.5% were in the renal pelvis, 6.4% were in the PUJ or upper ureter, and only 0.9% were in the middle ureter.

Conclusion:

Ultrasound imaging can determine the cause of HN in more than two thirds of patients. Calculi are the most common cause of HN even in children and are most common in the VUJ junction.