Abstract
Introduction: The Pap test aims at diagnosing precancerous or cancerous lesions of the cervix, hormonal evaluation, and bacterial flora. Objectives: Determine the proportion of non-neoplastic findings, squamous and glandular epithelial abnormalities referred to the district of Hospital Nacional Docente Madre Niño San Bartolome. Methods: A prospective, analytical, correlational, cross-sectional research was designed for all vaginal smear which were referred from five health networks and micro-networks. Cytological processing was carried out in accordance with applicable international requirements. Cytologic interpretation was performed according to Bethesda System. Results: Out of 72,644 cervical smears evaluated by Bethesda quality system, the proportion of results with cervical uterine disorders (prevalence 6.5% CI 95%: 6.32%, 6.68%) were 4724 (6.5%) samples, negative posevaluación was 35318 (51.7%) samples, and nonneoplastic findings 32 602 (48.2%) samples, (p< 0.005). Posttest probability was 89.3% (CI 95%: 87.1% to 91.1%; likelihood ratio LR > 10) and a significant direct correlation was established between the findings/nLiM and ages of patients (rho= 0.477; p< 0.005). Moreover, 46.53% of NIM flora suggestive corresponds to bacterial vaginosis (BV), 22.5% to reactive changes associated with inflammation and squamous metaplasia 21% (MET). The most frequent association was MET, VB, and severe inflammation 5.5% (1495 results). Conclusions: The proportion of non-neoplastic findings was considerable; squamous and glandular epithelial abnormalities were above average standard.
| Translated title of the contribution | Non neoplastic findings and epithelial cell abnormalities in cervical cytology |
|---|---|
| Original language | Spanish |
| Journal | Revista Cubana de Obstetricia y Ginecologia |
| Volume | 42 |
| Issue number | 1 |
| State | Published - 2016 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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