ABSTRACT
Infertility affects millions of people of reproductive age worldwide. Thyroid hormones and prolactin (PRL) affect reproduction and pregnancy; therefore, these two hormones influence fertility. This systematic review and meta-analysis aimed to summarise the strength of the correlation between serum PRL and thyroid stimulating hormone (TSH) in infertile women and to explore selected factors influencing the correlation. We conducted a systematic search of online databases (PubMed, Scopus, ScienceDirect, SAGE and Google Scholar) from inception until March 2021 and a manual search of the bibliographies of the included studies to identify relevant publications. The original research paper describing the correlation between PRL and TSH in reproductive-age women with infertility (primary and secondary) was included. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Analytical Cross-Sectional Studies. A random effect model was used to estimate the pooled correlations of PRL and TSH, followed by an assessment of heterogeneity and a sensitivity analysis. From a total of 822 relevant articles identified, 11 were eligible and included in this systematic review and meta-analysis. The random effect pooled correlation estimates between PRL and TSH was 0.431 (95% CI: 0.251, 0.582), with substantial heterogeneity between the included studies (I2 = 80%, τ2 = 0.067, P < 0.001). No significant publication bias was observed. Study region, types of infertility, sample size and year of the study did not influence the correlation estimates. Our results highlighted a significant positive moderate correlation between serum PRL and serum TSH in infertile women.
ABSTRACT
@#Introduction: Total calcium concentration is widely used to assess body calcium status although limited by many confounding factors. Thus, this study aimed to derive and internally validate an albumin-adjusted calcium equation for a selected Malaysian population. Method: This cross-sectional study involved 1011 adults at an emergency department of a tertiary hospital. Patients who had total calcium, ionised calcium and albumin measurements taken simultaneously were included. Derivation of the albumin-adjusted calcium equation was based on the adjustment equation obtained from the Association for Clinical Biochemistry and Laboratory Medicine 2015 position paper. Additionally, the equation was internally validated and compared with ionised calcium (gold standard) and the conventional Payne’s equation. Results: The newly derived equation = total calcium + 0.017 (41.35 – albumin). Internal validation exhibited the amount of shrinkage of 0.049. It tends to overestimate the adjusted calcium by a mean difference of 0.029 mmol/L compared to Payne’s equation. The comparison between Payne’s equation and the new equation with ionised calcium reclassified 402 and 486 patients, respectively into different calcium status. When both equations were compared, calcium status classification significantly differed in all and hypoalbuminaemic subjects by 90 and 16 patients, respectively. Conclusion: Locally derived albumin-adjusted calcium equation differed statistically in calcium status classification when compared to the Payne’s equation. However, to confirm this significance, the result must be compared to ionised calcium under strict, controlled preanalytical conditions. In terms of clinical significance, there was no difference in classification of calcium status between Payne’s and the new equation at medical decision limits.
