Ovarian hyperstimulation is a recognised complication of longstanding hypothyroidism. A 12 year old girl with atrophicthyroiditis who presented with abdominal pain and distensionis reported. She was noted to have brui...Ovarian hyperstimulation is a recognised complication of longstanding hypothyroidism. A 12 year old girl with atrophicthyroiditis who presented with abdominal pain and distensionis reported. She was noted to have bruising in the vicinity of the umbilicus (Cullen’s sign). She had pronounced ovarian enlargement on ultrasonography and it was hypothesised that this profound phenotype might reflect an abnormal FSH receptor.However sequencing of the FSH receptor was normal.The ovarian enlargement resolved with thyroxine replacement.Physicians and surgeons should consider longstanding hypothyroidismin patients presenting with Cullen’s sign.展开更多
AIM: To investigate the role of artifi cial neural networks in predicting the presence of thyroid disease in atrophic body gastritis patients. METHODS: A dataset of 29 input variables of 253 atrophic body gastritis pa...AIM: To investigate the role of artifi cial neural networks in predicting the presence of thyroid disease in atrophic body gastritis patients. METHODS: A dataset of 29 input variables of 253 atrophic body gastritis patients was applied to artifi cial neural networks (ANNs) using a data optimisation procedure (standard ANNs,T&T-IS protocol,TWIST protocol). The target variable was the presence of thyroid disease. RESULTS: Standard ANNs obtained a mean accuracy of 64.4% with a sensitivity of 69% and a specifi city of 59.8% in recognizing atrophic body gastritis patients with thyroid disease. The optimization procedures (T&T-IS and TWIST protocol) improved the performance of the recognition task yielding a mean accuracy,sensitivity and specifi city of 74.7% and 75.8%,78.8% and 81.8%,and 70.5% and 69.9%,respectively. The increase of sensitivity of the TWIST protocol was statistically signifi cant compared to T&T-IS. CONCLUSION: This study suggests that artificial neural networks may be taken into consideration as a potential clinical decision-support tool for identifying ABG patients at risk for harbouring an unknown thyroid disease and thus requiring diagnostic work-up of their thyroid status.展开更多
文摘Ovarian hyperstimulation is a recognised complication of longstanding hypothyroidism. A 12 year old girl with atrophicthyroiditis who presented with abdominal pain and distensionis reported. She was noted to have bruising in the vicinity of the umbilicus (Cullen’s sign). She had pronounced ovarian enlargement on ultrasonography and it was hypothesised that this profound phenotype might reflect an abnormal FSH receptor.However sequencing of the FSH receptor was normal.The ovarian enlargement resolved with thyroxine replacement.Physicians and surgeons should consider longstanding hypothyroidismin patients presenting with Cullen’s sign.
基金funds from MIUR 2005 (Italian Ministry for University and Research) and University Sapienza Roma
文摘AIM: To investigate the role of artifi cial neural networks in predicting the presence of thyroid disease in atrophic body gastritis patients. METHODS: A dataset of 29 input variables of 253 atrophic body gastritis patients was applied to artifi cial neural networks (ANNs) using a data optimisation procedure (standard ANNs,T&T-IS protocol,TWIST protocol). The target variable was the presence of thyroid disease. RESULTS: Standard ANNs obtained a mean accuracy of 64.4% with a sensitivity of 69% and a specifi city of 59.8% in recognizing atrophic body gastritis patients with thyroid disease. The optimization procedures (T&T-IS and TWIST protocol) improved the performance of the recognition task yielding a mean accuracy,sensitivity and specifi city of 74.7% and 75.8%,78.8% and 81.8%,and 70.5% and 69.9%,respectively. The increase of sensitivity of the TWIST protocol was statistically signifi cant compared to T&T-IS. CONCLUSION: This study suggests that artificial neural networks may be taken into consideration as a potential clinical decision-support tool for identifying ABG patients at risk for harbouring an unknown thyroid disease and thus requiring diagnostic work-up of their thyroid status.
