@article{Akhtar_Shams_Iqbal_Ahmed_Jan_Nawaz_2021, title={Analysis of Caesarean Section Rates in a Tertiary Care Hospital through Robson’s Ten Group Classification System (RTGCS)}, volume={5}, url={https://abms.kmu.edu.pk/index.php/abms/article/view/183}, DOI={10.35845/abms.2021.1.183}, abstractNote={<p><span class="fontstyle0"><strong>Objective</strong><br></span><span class="fontstyle1">To analyse the trend of caesarean sections at a tertiary care hospital according to Robson’s Ten<br>Group Classification System<br></span><span class="fontstyle0"><strong>Methodology</strong><br></span><span class="fontstyle1">This retrospective study was conducted at the department of obstetrics and gynecology Unit “B”<br>Hayatabad Medical Complex, Peshawar from January to December 2019.<br>Data for all births including live births and stillbirths by C-section (n=1538) was extracted from<br>the patient’s record and grouped into Robson’s 10 categories. Data was analyzed using<br>descriptive statistics and the outcome expressed as frequencies and percentages.<br></span><span class="fontstyle0"><strong>Results</strong><br></span><span class="fontstyle1">During the study period, 5609 women were delivered in this hospital. The overall cesarean section<br>was 27.42%. The leading contributor to the overall cesarean section rate was group 5 i.e. women<br>with previous cesarean section, the contribution being 6.63% of the overall 27.42%.<br></span><span class="fontstyle0"><strong>Conclusion</strong><br></span><span class="fontstyle1">The Robson classification is an effective tool to identify the areas/factors which significantly<br>contribute to the high C-section rate and accordingly provide basis to formulate strategies aimed<br>to decrease the C-section rate.<br></span><span class="fontstyle0"><strong>Key words</strong><br></span><span class="fontstyle1">Caesarean section, Robson’s Ten Group Classification System</span></p>}, number={1}, journal={ADVANCES IN BASIC MEDICAL SCIENCES}, author={Akhtar, Rubina and Shams, Ghazala and Iqbal, Madiha and Ahmed, Basharat and Jan, Zara Alam and Nawaz, Aisha}, year={2021}, month={Aug.}, pages={11–14} }