Exploring the impact of pregnancy on cognitive function: a comparative study in a low-income setting
Bibliographic record
Abstract
BACKGROUND: Cognitive dysfunction is a significant contributor to mental health complexities during pregnancy, potentially leading to heightened rates of pregnancy-related mortality and inadequate prenatal care. However, limited research has been conducted to explore the relationship between pregnancy and cognitive decline, especially in low-income settings such as Pakistan. Therefore, this study aimed to establish a clear link between cognitive function and pregnancy. METHODS: A cross-sectional comparative study was conducted at a tertiary care hospital in Karachi, Pakistan with a sample size of 160 participants, divided into two groups of 83 pregnant (aged 25.63 ± 4.22) and 77 nonpregnant women (aged 27.79 ± 3.89). First, the participants were interviewed to collect demographic information and pregnancy status. Then, the Montreal Cognitive Assessment (MoCA) scale, which evaluates cognitive function across multiple domains, including visuospatial/executive function, naming, attention, language, abstraction, delayed recall, orientation, and memory was used on each group separately. The analysis investigated the relationship between cognitive function and pregnancy, considering the influence of low-income status and gestational age. The statistical analyses included Spearman Rho (for non-normal data), t-tests, and linear regression models. T-tests were used to compare the means of MoCA scores between different groups and to analyze the effect of pregnancy status on the specific domains of MoCA. Multiple linear regression models were employed to examine the relationships between MoCA scores and various predictors, such as pregnancy status, education level, gestational age, and active complaints. RESULTS: The study found a significant difference in MoCA scores between pregnant and nonpregnant women (B=-1.55, t=-2.37, p = 0.019), indicating a decline in cognitive function during pregnancy. Education level (B = 2.34, t = 8.38, p = 0.000) and gestational age (B=-1.61, t=-2.51, p = 0.014) were identified as significant factors influencing cognitive function. Higher education was associated with better cognitive function while increasing gestational age correlated with a decline in cognitive function. In addition, active complaints (B=-1.86, t=-2.25, p = 0.028) during pregnancy were associated with lower MoCA scores. CONCLUSION: Our preliminary analyses suggest that there is notable cognitive impairment associated with pregnancy. More attention and research in this aspect can contribute to better prenatal care and promote the well-being of pregnant women.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".