ArticleCureus2026
Clinical Drivers of Cesarean Sections During the COVID-19 Pandemic: A Robson Classification-Based Multivariable Analysis.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveThe COVID-19 pandemic severely disrupted global maternity care, prompting concerns that logistical pressures and infection risks lowered the clinical threshold for performing cesarean sections (LSCS). This study aimed to determine whether delivering during the pandemic epoch independently increased a patient's odds of undergoing a surgical delivery, adjusting for pandemic-induced demographic shifts using the WHO Robson Ten Group Classification System.
methodsA retrospective cohort study of 3,656 deliveries was conducted at a tertiary care center, comparing pre-pandemic (n = 2,819) and pandemic (n = 837) epochs. Baseline demographics, antenatal comorbidities, and delivery outcomes were analyzed. A multivariable binomial logistic regression model was constructed to isolate the independent effect of the pandemic on delivery mode, adjusting for maternal age, comorbidities, and Robson mega-groups.
resultsThe pandemic induced a significant "triage effect," concentrating high-risk admissions. The pandemic cohort was significantly older (p < 0.001) and possessed a higher burden of metabolic comorbidities, including gestational diabetes mellitus (38.2% vs. 26.6%, p < 0.001). Despite this increased clinical complexity, the overall crude LSCS rate remained stable (33.5% vs. 34.8%, p = 0.518). Multivariable regression confirmed that the pandemic epoch did not independently increase the odds of a surgical delivery (aOR = 0.942; 95% CI: 0.768-1.156; p = 0.567). Surgical intervention was overwhelmingly driven by established obstetric indications, notably previous uterine scars (Robson 5; aOR = 22.45), malpresentations or multiple gestation (Robson 6-9; aOR = 10.70), and severe preeclampsia (aOR = 3.05). Unadjusted associations between metabolic comorbidities and LSCS lost significance in the adjusted model, proving them to be confounding variables mediated by age and prior uterine scars.
conclusionWhile the COVID-19 lockdown fundamentally shifted the demographic profile of obstetric admissions toward a highly complex, comorbid population, evidence-based surgical thresholds were rigorously maintained. Institutional increases in surgical urgency were a direct mathematical reflection of the triaged patient profile rather than a degradation of clinical practice standards.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.