Approach to dyspnea, palpitations, and headaches in pregnancy
Bibliographic record
Abstract
Pregnant individuals commonly experience symptoms such as dyspnea, palpitations, and headache. While often benign and physiologic, these symptoms can also signal serious conditions that require urgent investigation and treatment. General Internists are increasingly called upon to assess such concerns in both outpatient and acute care settings. This review offers a symptom-based, practical approach to evaluating these presentations during pregnancy, with emphasis on balancing maternal and fetal safety. Dyspnea is frequently reported and usually reflects normal respiratory and cardiovascular adaptations. However, clinicians must be vigilant for life-threatening causes such as pulmonary embolism, peripartum cardiomyopathy, or preeclampsia-associated pulmonary edema. Palpitations are common due to increased heart rate and cardiac output, but may reflect arrhythmias that require prompt assessment and, in some cases, pharmacologic therapy. Headaches may be due to primary headache disorders like migraine, but new or worsening headache in pregnancy warrants careful evaluation for preeclampsia, stroke, or cerebral venous thrombosis. Throughout this review, we highlight key physiological adaptations in pregnancy, discuss relevant differential diagnoses, and provide practical guidance on investigations and treatment options that balance maternal and fetal safety. This article aims to equip internists with the tools to recognize when symptoms require further workup and to ensure pregnant individuals receive timely, evidence-informed care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".