Fracture of Femur in a Young Obese Individual With Type 2 Diabetes, Hypogonadism and Low Vitamin D: As in the Titanic We Are Only Seeing the Tip of the Iceberg?
Bibliographic record
Abstract
We report a case of a 42-year-old male with poorly controlled type 2 diabetes and body mass index (BMI) of 35 kg/m 2 who was admitted with fracture of right head of the femur after small fall from stepladder. Imaging of the pelvis in the form of an X-ray showed multi-fragmented fracture through trochanteric region of the right femur. His fracture was fixed with an intramedullary device. However, subsequent tests revealed low testosterone (4.2 nmol/L and reference range 10 - 35 nmol/L) and low vitamin D (13.2 nmol/L and reference range > 50). His bone densitometry scan showed no evidence of osteoporosis. Furthermore, his diabetes control was poor with an average HbA1c of 11% and he was also known to have background diabetic retinopathy. The combination of poor diabetes control, obesity, hypogonadism and low vitamin D may all have contributed to an increase in risk of fracture in association with simple fall in this young man. Obesity and type 2 diabetes are associated with hypogonadism and low vitamin D. In view of the high epidemic of diabetes and obesity, it is possible to suggest that there are large numbers of these individuals with high risk for fracture likely to be induced upon any mild degree of trauma. Furthermore, it is possible to suggest that obesity-induced fracture will increase the burden in orthopedic department and the current numbers of fractures related to obesity may represent the tip of iceberg. Our case report is unique as the fracture occurred in a young individual with all these metabolic disorders. Therefore, our case report illustrates the needs for close collaboration between orthopedic surgeons, general practioners and endocrinologists and importantly the need for robust methods for screening and risk stratifications. J Med Cases. 2016;7(2):77-79 doi: http://dx.doi.org/10.14740/jmc2402w
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".