Human ; Neoplasms ; Radiation ; Radiologists ; Research ; Tomography

Background: The criteria for admission at the University of the Philippine College of Medicine (UPCM) are sixty
percent premed general weighted average grade (PMGWAG), thirty percent National Medical Admission Test
(NMAT) scores and ten percent Interview Scores. Through the years, because of the highly competitive nature
of the selection process, the admissions cut-offs in PMGWAG and average NMAT has continuously risen.
Objectives: This study that covered a twenty four year period, aimed to determine the correlation and
predictive value between the admissions criteria (%Pre-med GWAG, NMAT and Interview Score) with
academic performance parameters (%Med GWAG and Class Ranking) and Board Rating.
Methods: The pre-admission and academic records of accepted lateral entrants from Class 1990 to Class 2013
were retrieved, reviewed and analyzed. These included the pre-med GWAG (%PMGWAG), NMAT and
Interview Scores, Med GWAG (%MGWAG), Class Ranking and Board Rating. Pearsons Correlation and Multiple
Linear regression analysis were done.
Results: All criteria (%PMGWAG, NMAT, Interview Score) for admissions were correlated with the academic
performance parameters (%MGWAG, Class Rank) and Board Rating. The strongest correlation was observed in
%PMGWAG with %MGWAG and Class Rank. Interview score correlated weakly with the academic
performance. Strong correlations between %MGWAG, Class Rank and Board Rating were likewise observed.
Rank upon admission also correlated strongly with Class Rank upon graduation. On linear regression analysis,
%PMGWAG and NMAT were more predictive of %MGWAG, Class Rank and Board Rating.
Conclusion: The weight distribution of the different admissions criteria should be adjusted accordingly.
Interview score, a weak predictor of academic performance and a measure of non-cognitive traits, should be
treated separately and independently as an admission criteria.

We present a case of pathologically confirmed, relatively rare Pigmented Villonodular Synovitis (PVNS). The patient presented with knee and thigh swelling. While initially misdiagnosed, he eventually underwent an MRI and a biopsy. The MRI was helpful but not definitive. The biopsy confirmed PVNS. The patient underwent synovectomy and was subsequently referred for radiotherapy and physical therapy. Post-treatment MRI showed no evidence of disease.

Gorham-Stout disease is a rare osteolytic disorder with an unclear pathophysiology. It presents as lesions characterized by the loss of the bony matrix and the proliferation of malformed vasculature. At present, there are no gold-standard diagnostic evaluation protocols and it is diagnosed through a mixture of clinical, histopathologic, and radiographic findings. We report a case of a 19-year-old female with Gorham-Stout disease presenting with an 8-year progressive soft tissue mass in the mandible. Extensive osteolysis of the mandible with clustering of the mandibular dentition is noted on computed tomography (CT) imaging. Her case was discussed in a multidisciplinary conference and her treatment was radiotherapy followed by surgery ± reconstruction. We used a CT-based three-dimensional planning technique to give 40 Gy over 20 treatment sessions to the involved areas. Post treatment, a repeat CT was done at six weeks to reassess for disease progression or stabilization, followed by surgical excision. As of 31 October 2021, no evidence of recurrence is noted 48 months after treatment. Arriving at a definitive diagnosis with GorhamStout disease is challenging and a multidisciplinary team approach can help determine the treatment choice with best outcomes.
Gorham-Stout disease ; disappearing bone disease ; osteolysis, essential

Background: Despite the rigorous and extremely competitive selection process of medical students at the University of the Philippines College of Medicine (UPCM), a few still performed poorly in academics that resulted in delayed graduation or failure to graduate at all. Methodology: Factors potentially associated with delayed graduation and failure to graduate among UPCM medical students were analyzed using univariate and multivariable logistic regression with their demographic and pre-admission academic profiles, namely, Pre-medical General Weighted Average Grade (PGWAG), National Medical Admission Test Scores (NMATs), interview scores, pre-med courses, the school graduated from, and admissions categories as predictors. Objective: The objective of this study was to identify the factors that predict the likelihood of not graduating and delayed graduation among the medical students of 24 classes of the UPCM. Results: The odds of delayed graduation and failure to graduate were increased by lower PMGWAG, NMAT score, interview score, admission through the special categories, being a non-UP graduate, and with BS Psychology as pre-med course. Conclusion The predictors of poor academic performance based on delayed graduation and failure to graduate were the PMGWAG, NMAT, interview scores, admissions category, pre-med course, and the school graduated from. It is recommended that the minimum admissions requirements for PMGWAG be increased particularly among the candidates in the special categories. The selection process in the special categories must put some bearing on the PMGWAGs and NMATs of their applicants.
Education, Medical ; Academic Performance

Background: Among the different criteria, the General Weighted Average Grade (PMGWAG) holds the biggest bearing on admission for the UP College of Medicine. However, GWAs are not comparable across different courses, different batches, different UP units and different schools. An Adjustment Factor is necessary to make PMGWAGs comparable and to level the playing field. Objectives: This study covering a 24-year period aimed to compare various proposed Admission Adjusted Factors of %PMGWAG (Pre-Med GWAG) in terms of Pearson's Correlation, Linear Regression Models and Mean Differences with %MGWAG (Medical GWAG), Class Rank and Board Rating as Outcome variables. Methodology: Various proposed Adjustment Factors were applied to %PMGWAG of medical students from Class 1990 to Class 2014 and Pearson's Correlation, Linear Regression Models and Mean Differences with %MGWAG, Class Rank and Board Rating were derived and analyzed. Results: Adjustment Factor A3 as applied to %PMGWAG correlates best with Board Rating and Class Rank while Adjustment Factor A6 with %MGWAG. On Linear Regression, A3 likewise bested other Adjustment Factors in predicting %MGWAG and %Board Rating while A6 on predicting Class Ranking. Among the various adjustments, A3 exerted the most impact on the outcome variables, based on mean differences. Conclusion The A3 Adjustment Factor is the preferred and most ideal among the various proposed adjustment factors. Its application on %PMGWAG, correlated best with, most predictive of and most influential to %MGWAG, Board Rating and Class Rating.
Education, Medical ; Academic Performance