Prevalence of depression and quality of life in polycystic ovary syndrome patients at a tertiary care hospital: a cross-sectional study

Background: Polycystic ovary syndrome (PCOS) is one of the most common endocrinopathy among women of reproductive age. Physical symptoms in PCOS cause depression and decrease the Quality of Life (QoL). The objective was to study the prevalence of depression in women suffering from PCOS and to assess its correlation with QoL.Methods: This was a cross sectional study conducted among one hundred patients diagnosed with PCOS. Women 18-40 years of age diagnosed with PCOS were included in the study. Patients with known psychiatric illness were excluded. Depression severity was assessed with Hamilton depression (HAM-D) scale. The quality of life (QoL) was assessed with Polycystic ovary syndrome questionnaire (PCOSQ). The data was analyzed using SPSS 20.0 for Windows.Results: The mean age and BMI was 25.64±3.25 years and 26.78±2.72 kg/m2 respectively. The mean depression score was 12.46±6.18. QoL domains showed that the lowest score was in the menstrual problem with a mean of 12.48±4.44 and the highest was in the emotional domain with a mean of 28.07±11.17. The negative correlations were between age and Hamilton score (p < 0.05). The Hamilton score was negatively correlated with the emotional score (p <0.01) and weight score was positively correlated with infertility score (p <0.01).Conclusions: PCOS was clearly associated with depression and reduced QoL. This should warrant health professionals to consider routine screening for depression and assess the impact of symptoms on their QoL to improve patient outcomes

Assessing the Validity of Nine Different Formulae for LDL-C Estimation in a Tertiary Care Centre, Hyderabad, India

Introduction: Conventionally, Friedewald’s formula has been used to calculate Low Density Lipoprotein- Cholesterol (LDL-C) due to its simplicity and convenience although it has limitations. Many researchers have proposed different formulae to increase the accuracy of calculated LDL-C, but none of those have concluded about a single best formula owing to differences in selected study populations. As LDL-C measurement is of utmost importance for assessing the cardiovascular risk according to National Cholesterol Education Programme’s (NCEP) Adult Treatment Panel III (ATP III), a search for a better formula to improve accuracy of cardiovascular disease (CVD) risk prediction is essential. Aim: To assess the validity of calculated LDL-C by nine formulae and compare them to values obtained by the direct method. Materials and Methods: A total of 324 participants were assessed retrospectively for serum lipid profile by standard methods from December 2020 to February 2021 at Employee State Insurance Corporation Medical College and Hospital, Sanathnagar, Hyderabad, Telangana, India. LDL-C was calculated using nine different formulae (Ahmadi, Anand, Chen, de Cordova, Friedewald, Hattori, Martin-Hopkins, Puavillai and Vujovic) and correlated with direct LDL-C. For further analysis, subjects were divided into five groups based on the Triglyceride levels (TG) viz; group 1 (TG <100 mg/dL), group 2 (TG: 100-150 mg/dL), group 3 (TG: 151-200 mg/dL), group 4 (TG: 201-400 mg/dL), group 5 (TG >400 mg/dL). Statistical analysis was done using Statistical Package for Social Sciences (SPSS) version 23.0. Results: Total of 324 lipid profile reports were analysed and calculated LDL-C by nine formulas were compared. At TG levels 400 mg/dL, Puavillai had better accuracy. But, none of the formulae showed strong correlation with Direct LDL-C at TG >400 mg/dL. ROC curves also showed that Puavillai performed better among all formulae, at all TG levels. Conclusion: Among the nine equations, Puavillai and Martin-Hopkins showed highest accuracy and better performance than others in the present study population. Martin-Hopkins can be used at TG levels of 100-200 mg/dL while Puavillai can be used at lower and higher TG levels in this demographic population for estimating LDL-C