ABSTRACT
Purpose: To compare the quality of life (QoL) in patients with glaucoma on medical therapy and after trabeculectomy and glaucoma drainage device (GDD) using vision, glaucoma, and surgery?specific questionnaires. Methods: This cross?sectional study enrolled 30 patients of moderate to severe glaucoma, each in medical, trabeculectomy, and GDD groups. National Eye Institute Visual Function Questionnaire 25 (NEIVFQ?25), Glaucoma Quality of Life (GQL?15), and Surgery Specific Questionnaire (SSQ) were administered, and cumulative scores were compared. Results: The mean age of the participants was 58.95 ± 13.6 years with a male preponderance (73.3%, n = 66). The mean scores (SD) in the medical, trabeculectomy, and GDD groups using NEIVFQ?25 were 68.97 (6.98), 72.83 (7.81), and 75.20 (8.77), respectively, those using GQL?15 were 20.63 (6.00), 26.23 (9.12), and 28.43 (7.74), respectively, and for the SSQ, they were 74.33 (8.75) and 72.10 (5.92) in trabeculectomy and GDD groups, respectively. NEIVFQ?25 showed a better QoL in the GDD group compared to the medical group, whereas GQL?15 showed a better QoL in the medical group and comparable QoL in trabeculectomy and GDD. Both these QoL scores correlated to the LogMAR visual acuity. SSQ scores did not show a significant difference in the QoL across both surgical groups. Conclusion: NEIVFQ?25 questionnaire scores provided a holistic measure of QoL. GQL?15 assessed the activity limitation and visual disability of the patients but did not take into account the general health and psychological factors influencing the QoL. We did not find a significant difference between trabeculectomy and GDD using the SSQ. For QoL assessment in medically or surgically treated glaucoma, vision?specific and disease?specific questionnaires should always be used in conjunction
ABSTRACT
Purpose: COVID?19?associated mucormycosis (CAM) was a serious public health problem during the second wave of COVID?19 in India. We planned to analyze public perceptions by sentiment analysis of Twitter data regarding CAM. Methods: In this observational study, the application programming interface (API) provided by the Twitter platform was used for extracting real?time conversations by using keywords related to mucormycosis (colloquially known as “black fungus”), from May 3 to August 29, 2021. Lexicon?based sentiment analysis of the tweets was done using the Vader sentiment analysis tool. To identify the overall sentiment of a user on any given topic, an algorithm to label a user “k” based on their sentiments was used. Results: A total of 4,01,037 tweets were collected between May 3 and August 29, 2021, and the peak frequency of 1,60,000 tweets was observed from May 17 to May 23, 2021. Positive sentiment tweets constituted a larger share as compared to negative sentiment tweets, with weekly variations. A temporal analysis of the demand for utilities showed that the demand was high in the initial period but decreased with time, which was associated with the availability of resources. Conclusion: Sentiment analysis using Twitter data revealed that social media platforms are gaining popularity to express one’s emotions during the ongoing COVID?19 pandemic. In our study, time?based assessment of tweets showed a reduction over time in the frequency of negative sentiment tweets. The polarization in the retweet network of users, based on sentiment polarity, showed that the users were well connected, highlighting the fact that such issues bond our society rather than segregating it.