Development and validation of a clinical prediction model for poor ovarian response in assisted reproductive technology
Xin Xin, Zhaoxia Cheng, Ting Hu, Yi Guo, Nan Li, Junbo Zhao, Shuaishuai Guo · 2026
Read Development and validation of a clinical prediction model for poor ovarian response in assisted reproductive technology by Xin Xin, Zhaoxia Cheng, Ting Hu, Yi Guo, Nan Li, Junbo Zhao, Shuaishuai Guo (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13310710.txt.
Description
Xin Xin and colleagues built a 2026 prediction tool for poor ovarian response during fertility treatment. Some patients make few eggs during stimulation, which lowers the chance of success. Early warning would let doctors adjust plans in advance. The team used past cases from a hospital in Shenyang, China, to find the best warning signs.
Records covered 1,789 patients treated from 2020 to 2023, split into build and test groups by date. Four methods were compared, and a stepwise method won. Hormone levels, body weight, and follicle counts proved the strongest signs. A simple chart turns those signs into a personal risk score for clinic use.
Catalog record
| CREATOR | Xin Xin, Zhaoxia Cheng, Ting Hu, Yi Guo, Nan Li, Junbo Zhao, Shuaishuai Guo |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 34465 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |