Comparison of Clinical Characteristics and Pregnancy Outcome Prediction Models Between AIH and AID Patients

Artificial insemination by husband (AIH) and artificial insemination by donor (AID) are core assisted reproductive techniques for infertile couples; however, few head-to-head comparative prediction models exist for their pregnancy outcomes. This study aimed to compare clinical population characteristics, construct independent pregnancy outcome prediction nomogram models for AIH and AID patients, identify differential independent predictive factors, and evaluate model discrimination performance.

This single-center retrospective observational cohort study enrolled 11651 AIH cycles and 3064 AID cycles from 2015 to 2025. All baseline demographic, clinical, treatment and laboratory parameters were collected and compared between groups. Binary univariate logistic regression was used to screen candidate predictors; variables with P<0.05 were included in multivariate forward stepwise logistic regression to identify independent predictive factors, visualized via forest plots. Visual nomogram prediction models were built using R software. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were adopted to preliminarily assess model predictive ability. Employs the within-cohort bootstrap method for validation.

Baseline profiles and pregnancy rates differed significantly between groups (P<0.05). Seven independent predictors were identified for AIH and three for AID. For AIH, advancing female age (OR=0.97, 95% CI:0.95~0.99), prolonged infertility duration (OR=0.96, 95% CI:0.93~0.98) and more treatment cycles (OR=0.92, 95% CI:0.86~0.98) reduced pregnancy probability, while thicker endometrium (OR=1.03, 95% CI:1.00~1.07), optimized ovulation induction (OR=1.27, 95% CI:1.13~1.42), unexplained infertility (OR=1.37, 95% CI:1.23~1.53) and double insemination (OR=1.18, 95% CI:1.06~1.32) elevated pregnancy odds (all P<0.05). For AID, longer infertility duration (OR=0.95, 95% CI:0.91~0.99) and repeated cycles (OR=0.88, 95% CI:0.82~0.95) impaired pregnancy, yet double insemination markedly improved outcomes (OR=4.75, 95% CI:2.78~8.10, P<0.05). The AIH and AID nomogram achieved AUC of 0.577 (95% CI:0.56~0.59) and 0.582 (95% CI:0.56~0.60) separately (P<0.05). Internal validation revealed acceptable calibration of the model, though its discriminative performance remained modest in both AID and AIH cohorts.

Ovarian status and baseline fertility profiles differed substantially between the AIH and AID groups. The two nomogram models only demonstrated limited discrimination ability for predicting clinical pregnancy.