Trends in the Use and Indications for Intracytoplasmic Sperm Injection Between 2005 and 2017: A State‐Wide Descriptive Cohort Analysis
Bibliographic record
Abstract
ABSTRACT Background Intracytoplasmic sperm injection (ICSI) was first developed to overcome male factor infertility. ICSI has increased in uptake globally, including in cases where its use is non‐essential for fertilisation. Aims To identify temporal trends in the use of, and indications for ICSI in an Australian context. Materials and Methods A statewide descriptive cohort study examining the trends in ICSI uptake and reported indication/s for ICSI use. The cohort included women undergoing IVF between 2005 and 2017 at IVF clinics across Victoria, Australia that resulted in a birth after 20 weeks' gestation. Results The dataset comprised 32 102 assisted reproduction cycles: 22 873 (71.3%) ICSI and 9229 (28.7%) conventional IVF. In 2005, ICSI accounted for 60.6% (1182/1952) of cycles, increasing to 79.5% (2344/2947) by 2017 ( p trend < 0.001). Testicular sperm retrieval as an indication for ICSI remained consistent over time ( p trend = 0.15). Male factor infertility as an indication decreased over time ( p trend = 0.007). Vitrified oocyte thaw ( p trend = 0.016) and ‘unexplained subfertility’ ( p trend = 0.30) cycles did not surpass 1.7% (39/2293) and 0.4% (9/2048), respectively of total cycles in any year. Donor sperm ( p trend = 0.001), pre‐implantation genetic testing ( p trend = 0.004), female factors associated with poor IVF outcome ( p trend = 0.005) and advanced maternal age ( p trend = 0.005) all increased as indications for ICSI over time. ‘Unspecified’ indication accounted for the majority of ICSI cycles after 2008 ( p trend = 0.015). Conclusions During our study period, the total use of ICSI increased by 18.9%. Notably, most of these cycles were not medically indicated.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".