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1.
Ann Indian Acad Neurol ; 25(1): 60-67, 2022.
Article in English | MEDLINE | ID: covidwho-1726286

ABSTRACT

Objective: To study impact of COVID-19 pandemic on frequency, clinical/electrophysiological profile and treatment outcomes in pediatric Guillain-Barré syndrome (GBS). Background: GBS is the most frequent cause of pediatric acute flaccid paralysis. The effect of the COVID-19 pandemic on pediatric GBS is unclear in the literature. Methods: We conducted an ambispective, multicentric, cohort study involving 12 of 27 centres in GBS Consortium, during two periods: pre-COVID-19 (March-August 2019) and during COVID-19 (March-August 2020). Children ≤12 years who satisfied National Institute of Neurological Diseases and Stroke criteria for GBS/variants were enrolled. Details pertaining to clinical/laboratory parameters, treatment and outcomes (modified Rankin Scale (mRS) at discharge, GBS Disability score at discharge and 3 months) were analysed. Results: We enrolled 33 children in 2019 and 10 in 2020. Children in 2020 were older (median 10.4 [interquartile range 6.75-11.25] years versus 5 (2.5-8.4) years; P = 0.022) and had more sensory symptoms (50% versus 18.2%; P = 0.043). The 2020 group had relatively favourable mRS at discharge (median 1 (1-3.5) versus 3 (2-4); P = 0.042) and GBS disability score at 3 months (median 0 (0-0.75) versus 2 (0-3); P = 0.009) compared to 2019. Multivariate analysis revealed bowel involvement (P = 0.000) and ventilatory support (P = 0.001) as independent predictors of disability. No child in 2020 had preceding/concurrent SARS-CoV2 infection. Conclusions: The COVID-19 pandemic led to a marked decline in pediatric GBS presenting to hospitals. Antecedent illnesses, clinical and electrophysiological profile of GBS remained largely unchanged from the pre-pandemic era.

2.
Int J Health Plann Manage ; 37(2): 632-642, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1530151

ABSTRACT

Tuberculosis (TB) is the leading cause of death from a single infectious agent worldwide. The COVID-19 pandemic has overburdened healthcare services around the world especially in resource constrained settings. It has shaken already unstable foundation of TB control programs in India and other high burden states. A 25% decline is expected in TB detection while estimates suggest 13% increase in TB deaths due to the impact of the pandemic. However, the significant intersections between the two diseases perhaps offer potential opportunities for consolidating the efforts to tackle both. The widespread implementation and acceptance of universal masking and social distancing in India has helped limit transmission of both diseases. Integrating the capacity building strategies for the two diseases, optimizing the existing the surveillance and monitoring systems which have been achieved over the years will result in a single vertically integrated national program addressing both, rather than multiple parallel program which utilize the already sparse primary care manpower and infrastructure. In this article, we explore the impact of the COVID-19 pandemic on tuberculosis in India and offer suggestions on how effective health planning can efficiently integrate infrastructure and manpower at primary level to provide care for both COVID-19 and tuberculosis.


Subject(s)
COVID-19 , Tuberculosis , Health Planning , Humans , India/epidemiology , Pandemics/prevention & control , Primary Health Care , SARS-CoV-2 , Tuberculosis/epidemiology , Tuberculosis/prevention & control
4.
Indian J Endocrinol Metab ; 25(1): 14-19, 2021.
Article in English | MEDLINE | ID: covidwho-1332215

ABSTRACT

OBJECTIVE: COVID-19 has emerged as a multi-system disease with the potential for endocrine dysfunction. We aimed to study the hormonal profile of hospitalized patients with COVID-19 at a tertiary care referral hospital at Jodhpur, India. DESIGN: A hospital-based clinical study of endocrine profile of COVID-19 patients conducted from 15th May to 30th June 2020 after ethical approval. MEASUREMENTS: Fasting blood samples for free thyroxine (T4), free tri-iodothyronine (T3), thyroid stimulating Hormone (TSH), serum prolactin; basal and 1 h post-intramuscular adrenocorticotropic hormone (ACTH) stimulated cortisol, interleukin-6 (IL-6), and high sensitivity C-reactive protein (hsCRP) were collected within 24 h of admission after written informed consent. All hormones and IL-6 were analyzed by chemiluminescent immunoassay. hsCRP was measured by immune-turbidimetric assay. RESULTS: Of 235 patients studied, 14% had severe disease and 5.5% died. Adrenal insufficiency was present in 14%, most of whom had mild disease. A robust adrenal response was observed in those with severe disease. Basal and post-ACTH serum cortisol were significantly increased in severe disease or those who died compared to those who were mild or asymptomatic. Basal and post-ACTH serum cortisol showed a significant positive correlation with hsCRP but not with IL-6. Low T3 and low T4 syndrome were documented in 25% and 5%, respectively. Serum TSH and FT3 levels declined significantly from asymptomatic to severe category. Hyperprolactinemia was found in 21 patients. hsCRP showed a rising trend with disease severity while IL-6 did not. CONCLUSIONS: Endocrine dysfunction in the form of adrenal insufficiency, low T3, and low TSH syndrome and hyperprolactinemia were common COVID-19 hospitalized patients.

5.
Endocr Connect ; 10(6): 589-598, 2021 Jun 08.
Article in English | MEDLINE | ID: covidwho-1221864

ABSTRACT

OBJECTIVE: Plasma glucose has been correlated with in-hospital mortality among many diseases including infections. We aimed to study the plasma glucose at the admission of hospitalized patients with COVID-19 at a tertiary care referral hospital at Jodhpur, India and its relation with mortality. DESIGN: A hospital-based clinical study of plasma glucose of COVID-19 patients conducted from May 15 to June 30, 2020 after ethical approval. MEASUREMENTS: Random blood samples at admission were collected for plasma glucose, interleukin-6 (IL6) and high sensitivity C-reactive protein (hsCRP) after written informed consent was obtained. Plasma glucose was analyzed by the automated analyzer, IL6 by chemiluminescent immunoassay and hsCRP by immune-turbidimetric assay. RESULTS: A total of 386 patients were studied (female 39.6%); 11.1% had severe disease and 4.1% expired. There were 67 (17.4%) patients with known diabetes mellitus (DM). Patients with a history of DM had three times higher mortality (6/67, 9%) than those without DM (10/309, 3.1%). Patients with moderate and severe disease according to ICMR and WHO grading had higher plasma glucose than those with asymptomatic or mild disease (P < 0.0001). Plasma glucose levels at admission were significantly higher in non-survivors when compared to those who survived (297 ± 117 vs 131 ± 73; P < 0.0001). COVID-19 patients showed increased mortality with incremental plasma glucose levels. The hazard ratio for mortality was 1.128 (95% CI 0.86-14.860), 1.883 (95% CI 0.209-16.970), and 4.005 (95% CI 0.503-32.677) in random plasma glucose group of >100-200, >200-300 and >300 mg/dL, respectively, compared to those with random plasma glucose of <100 mg/dL at admission. Plasma glucose was strongly correlated with hsCRP (P < 0.001) and IL6 (P < 0.0001). CONCLUSIONS: Plasma glucose at admission in hospitalized COVID-19 patients is a strong predictor of mortality.

6.
Adv Respir Med ; 88(6): 515-519, 2020.
Article in English | MEDLINE | ID: covidwho-1059980

ABSTRACT

INTRODUCTION: Chloroquine and its analogues are currently being investigated for the treatment and post exposure prophylaxis of COVID-19 due to its antiviral activity and immunomodulatory activity. MATERIAL AND METHODS: Confirmed symptomatic cases of COVID-19 were included in the study. Patients were supposed to receive chloroquine (CQ) 500 mg twice daily for 7 days. Due to a change in institutional protocol, initial patients received chloroquine and subsequent patients who did not receive chloroquine served as negative controls. Clinical effectiveness was determined in terms of timing of symptom resolution and conversion rate of reverse transcriptase polymerase chain reaction (RT-PCR) on day 14 and day 15 of admission. RESULTS: Twelve COVID-19 patients formed the treatment arm and 17 patients were included in the control arm. The duration of symptoms among the CQ treated group (6.3 ± 2.7 days) was significantly (p-value = 0.009) lower than that of the control group (8.9 ± 2.2 days). There was no significant difference in the rate of RT-PCR negativity in both groups. 2 patients out of 12 developed diarrhea in the CQ therapy arm. CONCLUSION: The duration of symptoms among the treated group (with chloroquine) was significantly lower than that of the control group. RT-PCR conversion was not significantly different between the 2 groups.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/diet therapy , COVID-19/drug therapy , Chloroquine/therapeutic use , Post-Exposure Prophylaxis , Adult , COVID-19/prevention & control , Case-Control Studies , Female , Humans , Male , Middle Aged , Treatment Outcome
7.
Indian J Endocrinol Metab ; 24(5): 381-386, 2020.
Article in English | MEDLINE | ID: covidwho-958322

ABSTRACT

Coronavirus 2019 (COVID -19) has rapidly emerged as a global pandemic with multi-system involvement. Involvement of the endocrine system is expected in COVID-19 as the interplay between severe acute respiratory syndrome corona virus-2 (SARS CoV-2) and the endocrine system occurs at multiple levels. The widespread presence of ACE-2 receptors on various tissues suggests scope for direct viral infection. The interactions via the activation of inflammatory mediators and indirect immune-mediated damage are also postulated. Evidence so far suggests that COVID-19 can cause functional hypopituitarism by direct and indirect effects on the hypothalamo-pituitary axis resulting in inappropriate adrenal response to stress. Several reports highlight possible immune-mediated damage to thyroid glands resulting in subacute thyroiditis. COVID-19 is implicated in precipitating hyperglycemia in known diabetics and uncovering insulin resistance in those previously undiagnosed. COVID-19 has also been shown to trigger Type 1 Diabetes with ketosis. Various mechanisms including direct virus-induced beta cell apoptosis and immune-mediated beta-cell damage have been demonstrated. The presence of virus in semen has unclear clinical significance at present. In this mini-review summarize the endocrine manifestations reported so far in COVID-19 disease and explore mechanisms to decipher how SARS CoV-2 may affect various endocrine organs.

8.
Adv Respir Med ; 88(5): 400-405, 2020.
Article in English | MEDLINE | ID: covidwho-908391

ABSTRACT

INTRODUCTION: Machine learning algorithms have been used to develop prediction models in various infectious and non-infectious settings including interpretation of images in predicting the outcome of diseases. We demonstrate the application of one such simple automated machine learning algorithm to a dataset obtained about COVID-19 spread in South Korea to better understand the disease dynamics. MATERIAL AND METHODS: Data from 20th January 2020 (when the first case of COVID-19 was detected in South Korea) to 4th March 2020 was accessed from Korea's centre for disease control (KCDC). A future time-series of specified length (taken as 7 days in our study) starting from 5th March 2020 to 11th March 2020 was generated and fed to the model to generate predictions with upper and lower trend bounds of 95% confidence intervals. The model was assessed for its ability to reliably forecast using mean absolute percentage error (MAPE) as the metric. RESULTS: As on 4th March 2020, 145,541 patients were tested for COVID-19 (in 45 days) in South Korea of which 5166 patients tested positive. The predicted values approximated well with the actual numbers. The difference between predicted and observed values ranged from 4.08% to 12.77% . On average, our predictions differed from actual values by 7.42% (MAPE) over the same period. CONCLUSION: Open source and automated machine learning tools like Prophet can be applied and are effective in the context of COVID-19 for forecasting spread in naïve communities. It may help countries to efficiently allocate healthcare resources to contain this pandemic.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Machine Learning/statistics & numerical data , Models, Statistical , Pneumonia, Viral/epidemiology , Algorithms , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Female , Forecasting , Humans , Information Storage and Retrieval , Male , Pandemics , SARS-CoV-2
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