Association between tears of the posterior root of the medial meniscus and far posterior femoral condyle osteoarthritis

PURPOSEWe aimed to evaluate whether tears of the posterior horn of the medial meniscus root ligament (PHMM RL) are associated with osteoarthritis of the far posterior femoral condyles (FPFC).METHODSRetrospective review of 1158 patients who underwent arthroscopy identified 49 patients with confirmed tears of the medial meniscus posterior root ligament attachment. Preoperative magnetic resonance imaging (MRI) studies were reviewed to identify advanced osteoarthritis involving the medial and lateral FPFC. Control patients (n=48) had no meniscal tears confirmed by arthroscopy. Cases and controls were age- and sex-matched exactly 1:1. One case patient was excluded since there was no age- and sex-matched control available. The International Cartilage Research Society (ICRS) MRI cartilage grade was recorded for the medial and lateral FPFC. Associations were evaluated using univariate and multivariable conditional logistic regression analyses.RESULTSThere were 48 case and 48 control patients (10 men in each group, 20.8%) with median age 53 years (range, 21–67). Medial FPFC ICRS Grade 2 or higher lesions were present in 34 (70.8%) of case patients and 16 (33.3%) of control patients. Lateral FPFC ICRS Grade 2 or higher lesions were present in 24 (50%) of case patients and 14 (28.2%) of control patients. Increased body mass index (BMI) was associated with PHMM RL tears (OR=1.11, 95% CI [1.01, 1.22], P = 0.020). MRI was 81.2% (39/48) sensitive and 91.2% (44/48) specific for detection of PHMM RL tears. PHMM RL tears were associated with Grade 2 or higher medial FPFC osteoarthritis (OR=10.00, 95% CI (2.34, 42.78), P < 0.001). This association remained after adjusting for BMI (OR=11.79, 95% CI [2.46, 56.53], P = 0.002). There was also an association between PHMM RL tears and lateral FPFC osteoarthritis, which persisted after adjusting for BMI (OR =3.00, 95% CI [1.07, 8.37], P = 0.036).CONCLUSIONPHMM RL tears are associated with advanced osteoarthritis of the FPFC. Radiologists identifying FPFC osteoarthritis should look carefully for PHMM RL tears

Including diverse and admixed populations in genetic epidemiology research

The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations

Ancestry-related assortative mating in Latino populations

Examination of ancestry-informative genetic markers shows that Puerto Rican and Mexican populations have shown strong assortative mating that continues to this day

Does NIH funding differ between medical specialties? A longitudinal analysis of NIH grant data by specialty and type of grant, 2011–2020

Objectives Differences in National Institutes of Health (NIH) funding between specialties may affect research and patient outcomes in specialties that are less well funded.The aim of this study is to evaluate how NIH funding has been awarded by medical specialty. This study assesses differences and trends in the amount of funding, by medical specialty, for the years 2011–2020, via a retrospective analysis of data from the NIH RePORTER (Research Portfolio Online Reporting Tools Expenditures and Results).Study design Longitudinal cross-sectional studySetting NIH RePORTER data from 2011 to 2020 for awarded NIH grants (F32, T32, K01, K08, K23, R01, R03, R21, U01, P30) in the following medical specialties: anaesthesiology, dermatology, emergency medicine, family medicine, internal medicine, neurology, neurosurgery, obstetrics and gynaecology, ophthalmology, orthopaedic surgery, otolaryngology, pathology, paediatrics, physical medicine and rehabilitation, plastic surgery, psychiatry, radiation-diagnostic/oncology, surgery, and urology.Participants NIH grant awardees for the years 2011-2020Intervention NonePrimary and secondary outcome measures The following measures were studied: (1) number of grants by specialty, (2) number of grants per active physician in each specialty, (3) total dollar amount of grants by specialty, (4) total dollar amount of grants per active physician in each specialty and (5) mean dollar amount awarded by specialty for each grant type. We investigated whether any of these measures varied between medical specialties.Results In general, internal medicine/medicine, psychiatry, paediatrics, pathology and neurology received the most grants per year, had the highest number of grants per active physician, had the highest total amount of funding and had the highest amount of funding per active physician, whereas fields like emergency medicine, plastic surgery, orthopaedics, and obstetrics and gynaecology had the lowest. The mean dollar amount awarded by grant type differed significantly between specialties (p value less than the Bonferroni-corrected alpha=0.00029).Conclusions NIH funding varies significantly between medical specialties. This may affect research progress and the careers of scientists and may affect patient outcomes in less well funded specialties

Machine Learning for Opportunistic Screening for Osteoporosis from CT Scans of the Wrist and Forearm

Background: We investigated whether opportunistic screening for osteoporosis can be done from computed tomography (CT) scans of the wrist/forearm using machine learning. Methods: A retrospective study of 196 patients aged 50 years or greater who underwent CT scans of the wrist/forearm and dual-energy X-ray absorptiometry (DEXA) scans within 12 months of each other was performed. Volumetric segmentation of the forearm, carpal, and metacarpal bones was performed to obtain the mean CT attenuation of each bone. The correlations of the CT attenuations of each of the wrist/forearm bones and their correlations to the DEXA measurements were calculated. The study was divided into training/validation (n = 96) and test (n = 100) datasets. The performance of multivariable support vector machines (SVMs) was evaluated in the test dataset and compared to the CT attenuation of the distal third of the radial shaft (radius 33%). Results: There were positive correlations between each of the CT attenuations of the wrist/forearm bones, and with DEXA measurements. A threshold hamate CT attenuation of 170.2 Hounsfield units had a sensitivity of 69.2% and a specificity of 77.1% for identifying patients with osteoporosis. The radial-basis-function (RBF) kernel SVM (AUC = 0.818) was the best for predicting osteoporosis with a higher AUC than other models and better than the radius 33% (AUC = 0.576) (p = 0.020). Conclusions: Opportunistic screening for osteoporosis could be performed using CT scans of the wrist/forearm. Multivariable machine learning techniques, such as SVM with RBF kernels, that use data from multiple bones were more accurate than using the CT attenuation of a single bone

Declining racial and ethnic representation in clinical academic medicine: A longitudinal study of 16 US medical specialties.

OBJECTIVE:To evaluate trends in racial, ethnic, and sex representation at US medical schools across 16 specialties: internal medicine, pediatrics, surgery, psychiatry, radiology, anesthesiology, obstetrics and gynecology, neurology, family practice, pathology, emergency medicine, orthopedic surgery, ophthalmology, otolaryngology, physical medicine and rehabilitation, and dermatology. Using a novel, Census-derived statistical measure of diversity, the S-score, we quantified the degree of underrepresentation for racial minority groups and female faculty by rank for assistant, associate, and full professors from 1990-2016. METHODS:This longitudinal study of faculty diversity uses data obtained from the American Association of Medical Colleges (AAMC) Faculty Roster from US allopathic medical schools. The proportion of professors of racial minority groups and female faculty by rank was compared to the US population based on data from the US Census Bureau. The Roster includes data on 52,939 clinical medical faculty in 1990, and 129,545 in 2016, at the assistant professor level or higher. The primary measure used in this study was the S-score, a measure of representation based on the probability of the observed frequency of faculty from a racial/ethnic group and sex, given the racial and ethnic distribution of the US. Pearson correlations and 95% confidence intervals for S-score with time were used to measure trends. RESULTS:Blacks and Hispanics showed statistically significant trends (p<0.05) towards increasing underrepresentation in most specialties and are more underrepresented in 2016 than in 1990 across all ranks and specialties analyzed, except for Black females in obstetrics & gynecology. White females were also underrepresented in many specialties and in a subset of specialties trended toward greater underrepresentation. CONCLUSIONS:Current efforts to improve faculty diversity are inadequate in generating an academic physician workforce that represents the diversity of the US. More aggressive measures for faculty recruitment, retention, and promotion are necessary to reach equity in academia and healthcare

FDG PET/CT evaluation of pathologically proven pulmonary lesions in an area of high endemic granulomatous disease

PURPOSE: The goal of this study is to assess how reliable the threshold maximum standardized uptake value (maxSUV) of 2.5 on positron emission tomography–computed tomography (PET/CT) is for evaluation of solitary pulmonary lesions in an area of endemic granulomatous disease and to consider other imaging findings that may increase the accuracy of PET/CT. MATERIALS AND METHODS: The staging PET/CT of 72 subjects with solitary pulmonary lesions (nodules (less than 3 cm) or masses (greater than 3 cm)) were retrospectively reviewed. Pathology proven diagnosis from tissue samples was used as the gold standard. Logistic regression was used to assess whether the subject’s age, maxSUV, size of lesion, presence of emphysema, or evidence of granulomatous disease was predictive of malignancy. RESULTS: Malignant lesions were identified in 84.7 % (61/72) of the 72 subjects. A threshold maxSUV of 2.5 had a sensitivity of 95.1 % (58/61), specificity of 45.5 % (5/11), positive predictive value of 90.6 % (58/64), negative predictive value of 62.5 % (5/8) and an accuracy of 87.5 % (63/72). The false negative rate was 4.9 %, and the false positive rate was 54.5 %. All 3 false negatives were less than or equal to 1.0 cm; however, false positives ranged from 1.1 to 5.6 cm. The false negatives had a mean (SD) maxSUV of 2.0 (0.4), whereas the false positives had a mean (SD) maxSUV of 5.6 (3.0). Emphysema was associated with 1.1 higher odds of malignancy, and evidence of granulomatous disease was associated with 0.34 lower odds of benign disease, however, neither was statistically significant (p = 0.92 and p = 0.31, respectively). Higher maxSUV was significantly associated with increased risk of malignancy (p = 8.3 × 10(−3)). Older age and larger size of lesion were borderline associated with increased risk of malignancy (p = 0.05 and p = 0.07, respectively). CONCLUSION: In an area of high endemic granulomatous disease, the PET/CT threshold maxSUV of 2.5 retains a high sensitivity (95.1 %) and positive predictive value (90.6 %) for differentiating benign from malignant pulmonary lesions; however, the specificity (45.5) and negative predictive value (62.5) decrease due to increased false positives. The presence of emphysema and absence of evidence of granulomatous disease increases the probability that a pulmonary lesion is malignant; however, these were not statistically significant

Structured mating: Patterns and implications.

Genetic similarity of spouses can reflect factors influencing mate choice, such as physical/behavioral characteristics, and patterns of social endogamy. Spouse correlations for both genetic ancestry and measured traits may impact genotype distributions (Hardy Weinberg and linkage equilibrium), and therefore genetic association studies. Here we evaluate white spouse-pairs from the Framingham Heart Study (FHS) original and offspring cohorts (N = 124 and 755, respectively) to explore spousal genetic similarity and its consequences. Two principal components (PCs) of the genome-wide association (GWA) data were identified, with the first (PC1) delineating clines of Northern/Western to Southern European ancestry and the second (PC2) delineating clines of Ashkenazi Jewish ancestry. In the original (older) cohort, there was a striking positive correlation between the spouses in PC1 (r = 0.73, P = 3x10(-22)) and also for PC2 (r = 0.80, P = 7x10(-29)). In the offspring cohort, the spouse correlations were lower but still highly significant for PC1 (r = 0.38, P = 7x10(-28)) and for PC2 (r = 0.45, P = 2x10(-39)). We observed significant Hardy-Weinberg disequilibrium for single nucleotide polymorphisms (SNPs) loading heavily on PC1 and PC2 across 3 generations, and also significant linkage disequilibrium between unlinked SNPs; both decreased with time, consistent with reduced ancestral endogamy over generations and congruent with theoretical calculations. Ignoring ancestry, estimates of spouse kinship have a mean significantly greater than 0, and more so in the earlier generations. Adjusting kinship estimates for genetic ancestry through the use of PCs led to a mean spouse kinship not different from 0, demonstrating that spouse genetic similarity could be fully attributed to ancestral assortative mating. These findings also have significance for studies of heritability that are based on distantly related individuals (kinship less than 0.05), as we also demonstrate the poor correlation of kinship estimates in that range when ancestry is or is not taken into account

Scatter plots of spouses for PC1 and PC2, by generational cohort.

<p><b>Scatter plots of spouse-pair male versus female:</b> Top left: Fig 4a, PC1 in the original cohort. Top right: Fig 4b, PC2 in the original cohort. Bottom left: Fig 4c, PC1 in the offspring cohort. Bottom right: Fig 4d, PC2 in the offspring cohort.</p