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Introduction: Pregnancy is a physiological process accompanied by immuno-dynamic changes (inflammatory stages) that could influence or predict pregnancy outcomes. However, overlapping data intervals among biologically distinct conditions may hinder such differentiation. Here, a retrospective, proof-of-concept study was conducted to (a) differentiate pregnancy-related inflammatory stages, and (b) to prognosticate birth-related double risks (low birth weight and pre-term birth) based on blood tests of pregnant women. Method: Blood samples collected from 131 Indian pregnant females (192 temporal observations) were retrospectively analyzed with: (1) a reductionist approach, which investigates cell types individually; and (2) a non-reductionist alternative, which uses a proprietary software package to explore pre-partum multicellular interactions and birth-related outcomes. Leukocyte percentages collected during the second and third trimesters were utilized to predict double risks. Results: While the reductionist analysis failed to distinguish double risks (ambiguity was observed), the non-reductionist method differentiated four inflammatory stages, characterized by: (i) no double risk and a high phagocyte/lymphocyte (P/L) ratio (class 'A'), (ii) no double risk and a very low P/L ratio (class 'B'), (iii) 16.6% double risks and a moderately elevated phagocyte/ lymphocyte (P/L) ratio (class 'C'), and (iv) 83.3% double risks and the highest monocyte percentage (class 'D'). All double risks observations were associated with statistically higher concentrations of serum ferritin. Discussion: Combined, longitudinal clinical-inflammatory and personalized data patterns inform whether a pregnancy is associated with double risks and/or when changes occur. Considering pre-partum observations anticipated birth-related outcomes, personalized and prognostic features were demonstrated. Since antenatal care involves routine blood sampling (a low-cost procedure), this methodology is inherently translational. Because construct, internal, external, and statistical validity were supported, if corroborated with prospective studies, this method may assist United Nations' 2023 goals toward reducing infant mortality.
Shankar et al. (Wed,) studied this question.