BACKGROUND: The relation between Chlamydia trachomatis infection and subsequent tubal damage is widely recognized. As such, C. trachomatis antibody (CAT) testing can be used to triage women for immediate tubal testing with hysterosalpingography (HSG) or laparoscopy. However, once invasive tubal testing has ruled out tubal pathology, CAT serology status is ignored, as its clinical significance is currently unknown. This study aimed to determine whether positive CAT serology is associated with lower spontaneous pregnancy rates in women in whom HSG and/or diagnostic laparoscopy showed no visible tubal pathology. METHODS: We studied ovulatory women in whom HSG or laparoscopy showed patent tubes. Women were tested for C. trachomatis immunoglobulin G (IgG) antibodies with either micro-immunofluorescence (MIF) or an ELISA. CAT serology was positive if the MIF titre was ≥ 1:32 or if the ELISA index was >1.1. The proportion of couples pregnant without treatment was estimated at 12 months of follow-up. Time to pregnancy was considered censored at the date of the last contact when the woman was not pregnant or at the start of treatment. The association between CAT positivity and an ongoing pregnancy was evaluated with Cox regression analyses. RESULTS: Of the 1882 included women without visible tubal pathology, 338 (18%) had a treatment-independent pregnancy within 1 year [estimated cumulative pregnancy rate 31%; 95% confidence interval (CI): 27-35%]. Because of differential censoring after 9 months of follow-up, regression analyses were limited to the first 9 months after tubal testing. Positive C. trachomatis IgG serology was associated with a statistically significant 33% lower probability of an ongoing pregnancy [adjusted fecundity rate ratio 0.66 (95% CI 0.49-0.89)]. CONCLUSIONS: Even after HSG or laparoscopy has shown no visible tubal pathology, subfertile women with a positive CAT have lower pregnancy chances than CAT negative women. After external validation, this finding could be incorporated into existing prognostic models.
BACKGROUND: The relation between Chlamydia trachomatis infection and subsequent tubal damage is widely recognized. As such, C. trachomatis antibody (CAT) testing can be used to triage women for immediate tubal testing with hysterosalpingography (HSG) or laparoscopy. However, once invasive tubal testing has ruled out tubal pathology, CAT serology status is ignored, as its clinical significance is currently unknown. This study aimed to determine whether positive CAT serology is associated with lower spontaneous pregnancy rates in women in whom HSG and/or diagnostic laparoscopy showed no visible tubal pathology. METHODS: We studied ovulatory women in whom HSG or laparoscopy showed patent tubes. Women were tested for C. trachomatis immunoglobulin G (IgG) antibodies with either micro-immunofluorescence (MIF) or an ELISA. CAT serology was positive if the MIF titre was ≥ 1:32 or if the ELISA index was >1.1. The proportion of couples pregnant without treatment was estimated at 12 months of follow-up. Time to pregnancy was considered censored at the date of the last contact when the woman was not pregnant or at the start of treatment. The association between CAT positivity and an ongoing pregnancy was evaluated with Cox regression analyses. RESULTS: Of the 1882 included women without visible tubal pathology, 338 (18%) had a treatment-independent pregnancy within 1 year [estimated cumulative pregnancy rate 31%; 95% confidence interval (CI): 27-35%]. Because of differential censoring after 9 months of follow-up, regression analyses were limited to the first 9 months after tubal testing. Positive C. trachomatis IgG serology was associated with a statistically significant 33% lower probability of an ongoing pregnancy [adjusted fecundity rate ratio 0.66 (95% CI 0.49-0.89)]. CONCLUSIONS: Even after HSG or laparoscopy has shown no visible tubal pathology, subfertile women with a positive CAT have lower pregnancy chances than CAT negative women. After external validation, this finding could be incorporated into existing prognostic models.
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