8 results on '"Priti Kapadia"'
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2. Observational study for assessing the relation of visual impairment with symptoms of depression
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Chandni Satani and Priti Kapadia Gupta
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General Medicine - Abstract
To assess the relation of visual impairment related to the refractive error with symptoms of depressionin relation to age, gender, educational qualification, level of visual impairment, type of refractive error, and use of corrective measures taken by the patient.: Observational cross-sectional study. A total of 260 participants above the age of 12 years with unaided visual acuity below 6/18 were examined for their refractive error using objective and subjective tests of refraction. Depressive symptoms were assessed using patient health questionnaire – 9 (PHQ-9).: Chi-square and fisher’s exact test to find an association between qualitative variables. : Overall 70.77% of participants had depressive symptoms of varying degree. On assessing its severity 8.46% had moderate, 23.68% had mild, 38.46% had minimal depressive symptoms. Depressive symptoms were more prevalent in the younger age group, educated patients, and similar in both genders, but none were statistically significant. A statistically significant association was found between the level of visual impairment with depressive symptoms (p=0.01) and its severity (p=0.03). Relation of depressive symptoms with various types of refractive error were significant (p=0.01). The prevalence of depressive symptoms increased with an increasing degree of myopia (p=0.015) and hypermetropia (p=0.68). Participants who were not using corrective measures had more depressive symptoms in comparison to those using it. (p=0.19): Statistically significant association was found between depressive symptoms and its severity with the level of visual impairment, types, and degree of refractive error, especially myopia. There was no statistically significant association of refractive error with depressive symptoms and its severity in relation to age, gender, education.
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- 2022
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3. The attitude towards strabismus and barriers for its treatment in parents from rural and urban areas
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Divya Upendra Caculo and Priti Kapadia Gupta
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genetic structures ,business.industry ,Stigma (botany) ,medicine.disease ,eye diseases ,Neuro-ophthalmology ,medicine ,Pediatric ophthalmology ,Rural area ,business ,Strabismus ,Esotropia ,Psychosocial ,Exotropia ,Clinical psychology - Abstract
It has been observed that children having strabismus who are being left untreated face a lot of psychosocial and functional difficulties in adulthood. In this study, an attitude and a barrier scale was structured and validated on the basis of the adult strabismus 20 questionnaire and a Barrier Scale. The attitude scale had two subscales-psychosocial subscale and functional subscale. A total of 1747 children; 828 from urban and 919 from rural areas, between the age group of 5 to 12 years were screened from urban and rural schools for strabismus. 36 children with strabismus were identified and studied on the basis of various parameters. None of these children had taken previous treatment for strabismus. The ratio of urban is to rural school children was 5:7 and the ratio between male and female was 7:5. 25 (69.4%) had exotropia, 11(30.6%) had esotropia among which 18(50%) had moderate degree of squint, 12(33.3%) had mild degree of squint. Mean Scores in the psychosocial subscale scale in Urban and rural areas were as 65.89±31.19 and 59.56±26.74 with p value 0.51. Mean Scores in Functional Subscale were as 77.63±32.58 and 66.67±31.66 with p value of 0.31. The most important barrier for treatment was the unawareness of the treatment of strabismus at the appropriate time. The attitude of parents towards strabismus was based on an amalgamation of multiple variables like age of the child, amount of squint, type of squint and also the gender of the child. Keywords: Attitude, Barriers, Early treatment, Refractive error, Strabismus, Stigma.
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- 2021
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4. Clinical profile and associated risk factors of uveitis in patients attending tertiary care hospital
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Devangi Patel, Priti Kapadia Gupta, and Nishtha Patel
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medicine.medical_specialty ,business.industry ,Panuveitis ,Disease ,medicine.disease ,Neuro-ophthalmology ,Internal medicine ,medicine ,Etiology ,Intermediate uveitis ,Population study ,Pediatric ophthalmology ,business ,Uveitis - Abstract
Purpose: To study clinical profile of uveitis in tertiary care centre. Materials and Methods: In a cross-sectional study, total of 66 patients were identified as having uveitis visiting tertiary care centre. The diagnosis of uveitis and associated systemic diseases was based on a detailed clinical history, ophthalmological examination, general physical examination, and available laboratory tests. The patients were classified according to the standardization of uveitis nomenclature (SUN) working group. All patients were offered treatment as per possible investigation reports or through clinical work up. Results: Out of sixty-six patients M: F ratio was 1.87; unilateral 62.12%; bilateral 37.87%. Minimum age among study population was 18, while maximum age among study population was 72. Most cases of uveitis recorded in 25-44 years age group (51.51%). Specific diagnosis could be made in 26 (39.39%) patients. Anterior uveitis was the most common variant (n = 43 [65.15%]), followed by posterior (n = 12 [18.18%]), intermediate uveitis (n = 8 [12.12%]), and panuveitis (n=3 [4.54%]). 29 (43.93%) patients had acute, 23 (34.84%) had chronic, 13 (19.69%) had recurrent course of disease and 1 (1.51%) patients had quiescent phase of disease on presentation. Conclusion: We found specific etiology in one third of patients with the help of investigations. Despite of much efforts to identify the cause of uveitis, majority of the cases remained idiopathic or undiagnosed. However, the prompt clinical diagnosis and early initiation of appropriate treatment could achieve good response. Majority of patients in our study received topical corticosteroids. Keywords: Human leukocyte antigen (HLA) association, Newer emerging uveitis entity, Ocular tuberculosis, Toxoplasmosis, Uveitis.
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- 2021
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5. Machine Learning Prediction of Adenovirus D8 Conjunctivitis Complications from Viral Whole-Genome Sequence
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Kenji Nakamichi, Lakshmi Akileswaran, Thomas Meirick, Michele D. Lee, James Chodosh, Jaya Rajaiya, David Stroman, Alejandro Wolf-Yadlin, Quinn Jackson, W. Bradley Holtz, Aaron Y. Lee, Cecilia S. Lee, Russell N. Van Gelder, Gregg J. Berdy, James D. Branch, El-Roy Dixon, Sherif M. El-Harazi, Jack V. Greiner, Joshua Herz, Larry L. Lothringer, Damien Macaluso, Andrew L. Moyes, George Nardin, Bernard R. Perez, Lawerence E. Roel, Syamala H.K. Reddy, Stephanie Becker, Neil Shmunes, Stephen Smith, Michael Tepedino, Jonathan Macy, Prashant Garg, Nivedita Patil, Yasmin Bhagat, Malavika Krishnaswamy, Nagappa Somshekhar, Manisha Acharya, Shree Kumar Reddy, Mary Abraham, Shobha Kini, Nita Shanbag, P.N. Biswas, Virendra Agarwal, Anshu Sahai, P.S. Girija Devi, Vupputuri Venkata Lakshmi, Narasimha Rao, Radhika Tandon, Priti Kapadia, Deepak Mehta, Anju Kochar, Adriana dos Santos Forseto, Rubens Belfort, Jacob Moyses Cohen, Ramon Coral Ghanem, Roberta De Ventura, Sergio Luis Gianotti Pimentel, Sergio Kwitko, Maria Cristina Nishiwaki Dantas, Anna Maria Hofling-Lima, Walton Nose, D. Wariyapola, M. Wijetunge, Charith Fonseka, Champa Banagala, K.A. Salvin, and D.R. Kodikara
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General Medicine - Abstract
To obtain complete DNA sequences of adenoviral (AdV) D8 genome from patients with conjunctivitis and determine the relation of sequence variation to clinical outcomes.This study is a post hoc analysis of banked conjunctival swab samples from the BAYnovation Study, a previously conducted, randomized controlled clinical trial for AdV conjunctivitis.Ninety-six patients with AdV D8-positive conjunctivitis who received placebo treatment in the BAYnovation Study were included in the study.DNA from conjunctival swabs was purified and subjected to whole-genome viral DNA sequencing. Adenovirus D8 variants were identified and correlated with clinical outcomes, including 2 machine learning methods.Viral DNA sequence and development of subepithelial infiltrates (SEIs) were the main outcome measures.From initial sequencing of 80 AdV D8-positive samples, full adenoviral genome reconstructions were obtained for 71. A total of 630 single-nucleotide variants were identified, including 156 missense mutations. Sequence clustering revealed 3 previously unappreciated viral clades within the AdV D8 type. The likelihood of SEI development differed significantly between clades, ranging from 83% for Clade 1 to 46% for Clade 3. Genome-wide analysis of viral single-nucleotide polymorphisms failed to identify single-gene determinants of outcome. Two machine learning models were independently trained to predict clinical outcome using polymorphic sequences. Both machine learning models correctly predicted development of SEI outcomes in a newly sequenced validation set of 16 cases (Adenovirus D8 has ≥ 3 prevalent molecular substrains, which differ in propensity to result in SEIs. Development of SEIs can be accurately predicted from knowledge of full viral sequence. These results suggest that development of SEIs in AdV D8 conjunctivitis is largely attributable to pathologic viral sequence variants within the D8 type and establishes machine learning paradigms as a powerful technique for understanding viral pathogenicity.
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- 2022
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6. Determinants of Outcomes of Adenoviral Keratoconjunctivitis
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Anshu Sahai, Damien Macaluso, Shree Kumar Reddy, Malavika Krishnaswamy, Nivedita Patil, M. Wijetunge, Gregg J. Berdy, James D. Branch, Bernard R. Perez, Nagappa Somshekhar, Charith Fonseka, Deepak Mehta, P.S. Girija Devi, Neil Shmunes, Shobha Kini, Russell N. Van Gelder, El-Roy Dixon, Anna Maria Hofling-Lima, Stephanie Becker, P.N. Biswas, Walton Nosé, Jacob Moyses Cohen, Lawerence E. Roel, James Chodosh, Syamala H.K. Reddy, Radhika Tandon, Michael Tepedino, Lakshmi Akileswaran, D. Wariyapola, Anna Wald, Sherif M. El-Harazi, Sérgio Kwitko, Ramon C. Ghanem, D.R. Kodikara, Andrew L. Moyes, Roberta De Ventura, K.A. Salvin, Kathryn Najafi-Tagol, Stephen J. Smith, Narasimha Rao, Maria Cristina Nishiwaki Dantas, Nita Shanbag, Aaron Y. Lee, Joshua Herz, Virendra Agarwal, David W. Stroman, Sergio Luis Gianotti Pimentel, Jack V. Greiner, Prashant Garg, Yasmin Bhagat, Jonathan I. Macy, Amalia Magaret, Champa Banagala, Vupputuri Venkata Lakshmi, Cecilia S Lee, Anju Kochar, Adriana dos Santos Forseto, Rubens Belfort, Manisha Acharya, George Nardin, Mary Abraham, Priti Kapadia, Larry L Lothringer, and Steve Kleiboeker
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Male ,0301 basic medicine ,Visual acuity ,animal diseases ,viruses ,Adenoviridae Infections ,Keratoconjunctivitis ,Eye Infections, Viral ,Polymerase Chain Reaction ,0302 clinical medicine ,Child ,Aged, 80 and over ,Incidence ,Incidence (epidemiology) ,virus diseases ,Middle Aged ,Child, Preschool ,Adenoviral keratoconjunctivitis ,Female ,medicine.symptom ,Viral load ,Brazil ,Adult ,endocrine system ,medicine.medical_specialty ,Adolescent ,India ,Article ,Adenoviridae ,Young Adult ,03 medical and health sciences ,Internal medicine ,medicine ,Humans ,Aged ,Retrospective Studies ,Sri Lanka ,business.industry ,Infant ,Retrospective cohort study ,Eye infection ,medicine.disease ,United States ,Epidemic Keratoconjunctivitis ,Ophthalmology ,ophthalmology ,030104 developmental biology ,DNA, Viral ,030221 ophthalmology & optometry ,business ,Follow-Up Studies - Abstract
Purpose To determine host and pathogen factors predictive of outcomes in a large clinical cohort with keratoconjunctivitis. Design Retrospective analyses of the clinical and molecular data from a randomized, controlled, masked trial for auricloscene for keratoconjunctivitis (NVC-422 phase IIB, NovaBay; clinicaltrials.gov identifier, NCT01877694). Participants Five hundred participants from United States, India, Brazil, and Sri Lanka with clinical diagnosis of keratoconjunctivitis and positive rapid test results for adenovirus. Methods Clinical signs and symptoms and bilateral conjunctival swabs were obtained on days 1, 3, 6, 11, and 18. Polymerase chain reaction (PCR) analysis was performed to detect and quantify adenovirus in all samples. Regression models were used to evaluate the association of various variables with keratoconjunctivitis outcomes. Time to resolution of each symptom or sign was assessed by adenoviral species with Cox regression. Main Outcome Measures The difference in composite scores of clinical signs between days 1 and 18, mean visual acuity change between days 1 and 18, and time to resolution of each symptom or sign. Results Of 500 participants, 390 (78%) showed evidence of adenovirus by PCR. Among adenovirus-positive participants, adenovirus D species was most common (63% of total cases), but a total of 4 species and 21 different types of adenovirus were detected. Adenovirus D was associated with more severe signs and symptoms, a higher rate of subepithelial infiltrate development, and a slower decline in viral load compared with all other adenovirus species. The clinical courses of all patients with non–adenovirus D species infection and adenovirus-negative keratoconjunctivitis were similar. Mean change in visual acuity between days 1 and 18 was a gain of 1.9 letters; worse visual outcome was associated with older age. Conclusions A substantial proportion of keratoconjunctivitis is not associated with a detectable adenovirus. The clinical course of those with adenovirus D keratoconjunctivitis is significantly more severe than those with non–adenovirus D species infections or adenovirus-negative keratoconjunctivitis; high viral load at presentation and non-United States origin of participants is associated with poorer clinical outcome.
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- 2018
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7. EpImpact of the use of digital devices on e of COVID-19-associated rhino-orbital-cerebral mucormycosis in 2826 patients in India – Collaborative OPAI-IJO Study on Mucormycosis in COVID-19 (COSMIC), Report 1
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SantoshG Honavar, Mrittika Sen, Sabyasachi Sengupta, Raksha Rao, Usha Kim, Mukesh Sharma, Mahipal Sachdev, AshokK Grover, Abhidnya Surve, Abhishek Budharapu, AbhishekK Ramadhin, AbhishekKumar Tripathi, Adit Gupta, Aditya Bhargava, Animesh Sahu, Anjali Khairnar, Anju Kochar, Ankita Madhavani, AnkurK Shrivastava, AnujaK Desai, Anujeet Paul, Anuradha Ayyar, Aparna Bhatnagar, Aparna Singhal, ArchanaSunil Nikose, Arun Bhargava, ArvindL Tenagi, Ashish Kamble, Ashiyana Nariani, Bhavin Patel, Bibbhuti Kashyap, Bodhraj Dhawan, Busaraben Vohra, Charuta Mandke, Chinmayee Thrishulamurthy, Chitra Sambare, Deepayan Sarkar, DevanshiShirishbhai Mankad, Dhwani Maheshwari, Dilip Lalwani, Dipti Kanani, Diti Patel, FairoozP Manjandavida, Frenali Godhani, GarimaAmol Agarwal, Gayatri Ravulaparthi, GondhiVijay Shilpa, Gunjan Deshpande, Hansa Thakkar, Hardik Shah, HareRam Ojha, Harsha Jani, Jyoti Gontia, JyotikaP Mishrikotkar, Kamalpreet Likhari, Kamini Prajapati, Kavita Porwal, Kirthi Koka, KulveerSingh Dharawat, LakshmiB Ramamurthy, Mainak Bhattacharyya, Manorama Saini, MaremC Christy, Mausumi Das, Maya Hada, Mehul Panchal, Modini Pandharpurkar, MohammadOsman Ali, Mukesh Porwal, Nagaraju Gangashetappa, Neelima Mehrotra, Neha Bijlani, Nidhi Gajendragadkar, NitinM Nagarkar, Palak Modi, Parveen Rewri, Piyushi Sao, PrajaktaSalunkhe Patil, Pramod Giri, Priti Kapadia, Priti Yadav, Purvi Bhagat, Ragini Parekh, Rajashekhar Dyaberi, RajenderSingh Chauhan, Rajwinder Kaur, RamKishan Duvesh, Ramesh Murthy, RaviVarma Dandu, Ravija Kathiara, Renu Beri, Rinal Pandit, RitaHepsi Rani, Roshmi Gupta, Ruchi Pherwani, Rujuta Sapkal, Rupa Mehta, Sameeksha Tadepalli, Samra Fatima, Sandeep Karmarkar, SandeepSuresh Patil, Sanjana Shah, Sankit Shah, Sapan Shah, Sarika Dubey, Saurin Gandhi, Savitha Kanakpur, Shalini Mohan, Sharad Bhomaj, Sheela Kerkar, Shivani Jariwala, Shivati Sahu, Shruthi Tara, ShrutiKochar Maru, Shubhda Sharma, Shweta Gupta, Shwetha Kumari, Sima Das, Smita Menon, Snehal Burkule, SonamPoonam Nisar, Subashini Kaliaperumal, Subramanya Rao, Sudipto Pakrasi, Sujatha Rathod, SunilG Biradar, Suresh Kumar, Susheen Dutt, Svati Bansal, SwatiAmulbhai Ravani, Sweta Lohiya, SyedWajahat Ali Rizvi, Tanmay Gokhale, TatyaraoP Lahane, Tejaswini Vukkadala, Triveni Grover, Trupti Bhesaniya, Urmil Chawla, Usha Singh, VaishaliL Une, Varsha Nandedkar, Venkata Subramaniam, Vidya Eswaran, VidyaNair Chaudhry, Viji Rangarajan, Vipin Dehane, VivekM Sahasrabudhe, Yarra Sowjanya, Yashaswini Tupkary, and Yogita Phadke
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medicine.medical_specialty ,business.industry ,Mortality rate ,Mucormycosis ,Disease ,Functional endoscopic sinus surgery ,medicine.disease ,Surgery ,Ophthalmology ,Amphotericin B ,Diabetes mellitus ,Epidemiology ,medicine ,Stage (cooking) ,business ,medicine.drug - Abstract
Purpose: COVID-19-associated rhino-orbital-cerebral mucormycosis (ROCM) has reached epidemic proportion during India's second wave of COVID-19 pandemic, with several risk factors being implicated in its pathogenesis. This study aimed to determine the patient demographics, risk factors including comorbidities, and medications used to treat COVID-19, presenting symptoms and signs, and the outcome of management. Methods: This was a retrospective, observational study of patients with COVID-19-associated ROCM managed or co-managed by ophthalmologists in India from January 1, 2020 to May 26, 2021. Results: Of the 2826 patients, the states of Gujarat (22%) and Maharashtra (21%) reported the highest number of ROCM. The mean age of patients was 51.9 years with a male preponderance (71%). While 57% of the patients needed oxygen support for COVID-19 infection, 87% of the patients were treated with corticosteroids, (21% for > 10 days). Diabetes mellitus (DM) was present in 78% of all patients. Most of the cases showed onset of symptoms of ROCM between day 10 and day 15 from the diagnosis of COVID-19, 56% developed within 14 days after COVID-19 diagnosis, while 44% had delayed onset beyond 14 days. Orbit was involved in 72% of patients, with stage 3c forming the bulk (27%). Overall treatment included intravenous amphotericin B in 73%, functional endoscopic sinus surgery (FESS)/paranasal sinus (PNS) debridement in 56%, orbital exenteration in 15%, and both FESS/PNS debridement and orbital exenteration in 17%. Intraorbital injection of amphotericin B was administered in 22%. At final follow-up, mortality was 14%. Disease stage >3b had poorer prognosis. Paranasal sinus debridement and orbital exenteration reduced the mortality rate from 52% to 39% in patients with stage 4 disease with intracranial extension (p < 0.05). Conclusion: : Corticosteroids and DM are the most important predisposing factors in the development of COVID-19-associated ROCM. COVID-19 patients must be followed up beyond recovery. Awareness of red flag symptoms and signs, high index of clinical suspicion, prompt diagnosis, and early initiation of treatment with amphotericin B, aggressive surgical debridement of the PNS, and orbital exenteration, where indicated, are essential for successful outcome.
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- 2021
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8. Cytomegalovirus retinitis in acquired immunodeficiency syndrome patients: A problem worth giving attention to
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Priti Kapadia Gupta, Nikunj Patel, Shivani D Patel, and Kunjan J Patel
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Pediatrics ,medicine.medical_specialty ,business.industry ,Opportunistic infection ,Incidence (epidemiology) ,Public Health, Environmental and Occupational Health ,Congenital cytomegalovirus infection ,virus diseases ,Retinitis ,Dermatology ,highly active antiretroviral therapy ,medicine.disease ,CD4 ,Acquired immunodeficiency syndrome ,Natural history ,Infectious Diseases ,Acquired immunodeficiency syndrome (AIDS) ,Immunology ,Medicine ,Original Article ,In patient ,Cytomegalovirus retinitis ,business ,cytomegalovirus retinitis - Abstract
Background: Cytomegalovirus (CMV) retinitis remains the most common ocular opportunistic infection in patients with acquired immunodeficiency syndrome even in the era of highly active antiretroviral therapy (HAART). Increased survival of patients on HAART has increased incidence of blindness, which will further increase in the future. The objective of this study was to determine the incidence of CMV retinitis and the effect of HAART on the natural history of CMV retinitis in patients referred from ART center. Materials and Methods: Patients with baseline/current CD4 counts
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- 2014
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