Does assessment of signs and symptoms add to the predictive value of an algorithm to rule out pregnancy?

Abstract

Background A World Health Organization-endorsed algorithm, widely published in international guidance documents and distributed in the form of a ‘pregnancy checklist’, has become a popular tool for ruling out pregnancy among family planning clients in developing countries. The algorithm consists of six criteria excluding pregnancy, all conditional upon a seventh ‘master criterion’ relating to signs or symptoms of pregnancy. Few data exist on the specificity to pregnancy among family planning clients of long-accepted signs and symptoms of pregnancy. The aim of the present study was to assess whether reported signs and symptoms of pregnancy add to the predictive value of an algorithm to rule out pregnancy. Methods Data from a previous observational study were used to assess the performance of the algorithm with and without the ‘signs and symptoms’ criterion. The study group comprised 1852 new, non-menstruating family planning clients from seven clinics in Kenya. Results Signs and symptoms of pregnancy were rare (1.5%) as was pregnancy (1%). Signs and symptoms were more common (18.2%) among the 22 clients who tested positive for pregnancy than among the 1830 clients (1.3%) who tested negative, but did not add significantly to the predictive value of the algorithm. Most women with signs or symptoms were not pregnant and would have been unnecessarily denied a contraceptive method using the current criteria. Conclusions The ‘signs and symptoms’ criterion did not substantially improve the ability of the algorithm to exclude pregnant clients, but several reasons (including use of the algorithm for intrauterine device clients) render it unlikely that the algorithm will be changed