Background Defining cut-off values of flap glucose levels in diagnosing free flap vascular compromise, without taking patients' glucose levels into account, does not hold good in all circumstances, especially in cases of high fluctuations in patients' capillary blood glucose and in diabetic patients. The aim of our study was to establish the role of capillary blood glucose measurements of the flap in relation to patients' fingertip, as an objective tool for postoperative free flap monitoring. Methods A total of 76 free flaps underwent postoperative monitoring with reference test (clinical parameters) and simultaneously with our index test (difference between capillary blood glucose of free flap and the patient), in non-diabetic and diabetic patients. Patients' demography and flap characteristics were also recorded. An ROC curve was plotted to determine diagnostic accuracy and cut-offs of the index test in diagnosing free flap vascular compromise. Results Our Index test has a cut-off value of 24.5 mg/dL with 68.75% sensitivity and 93% specificity, with an accuracy of 91.54%. Conclusion The difference between capillary blood glucose of free flap and the patient is simple, feasible, and inexpensive, and can be done by any health care professional and does not require any specialized facilities or training. It has an excellent diagnostic accuracy to detect impending free flap vascular compromise, especially in non-diabetics. Although in diabetics, this test becomes less accurate. Being an observer-independent objective test, the difference in capillary blood glucose of patient and flap measurement can be used as a highly reliable tool for postoperative free flap monitoring.
Background: COVID-19 vaccination is still a matter of concern among the public since its inception. Primary care physicians being in prime position can share accurate and ample information about COVID-19 vaccination so we estimated proportion and determinants of adverse events following immunization (AEFI) with Covishield vaccine, vaccination and reasons of non-vaccination. Methods: A cross-sectional study was conducted from January to April 2021. Data collection was done by using data capture tool Epicollect-5. Regression analysis was performed to evaluate the association of AEFI and vaccine acceptance with various demographic variables. Results: Of 520 subjects, 408 got vaccinated, and of these 125 (30.6%) developed AEFI. Females without AEFI had lower median age than females having AEFI. Only religion (aOR = 5.311; 95% CI: 1. 216–23.1) was significantly associated with AEFI. Education (aOR = 0.399; 95% CI: 0. 199–0.799), marital status (aOR = 0.459; 95% CI: 0. 245–0.858), and religion (aOR = 3.874; 95% CI: 1. 96–7.648) were significantly associated with vaccination. Most common local AEFIs were inflammation (46; 36.8%) followed by lump (10; 8%) at the site of injection. Most common systemic AEFI were fever (87; 69.6%), feeling unwell (65; 52%), generalized weakness/fatigue (30; 20%), tiredness (26; 20.8%), flu-like symptoms (12; 9.6%), dizziness (10; 8%), headache (8; 6.4%) and gastrointestinal events (7; 5.6%). Conclusion: Most of the AEFI were mild and transient, resolved without any medical management. This study warrants active reporting of AEFI, public release of safety, and efficacy data. Primary care physicians can play a pivotal role by targeted awareness campaigns and trust-building activities to alleviate fear and anxiety related to vaccine.
Vaccination is a potential public health solution for the prevention of infection. It reduces the severity of symptoms in case of COVID-19. Despite the availability of vaccines, some people are hesitant to be vaccinated. The objectives of the study were to measure the proportion of vaccine hesitancy among the peri-urban population and identify its determinants. An adult population of 303 from two peri-urban areas in the field practice area of Urban Health Training Centre, Rama Medical College were interviewed from 22nd February 2021 to 25th March 2021. Epicollect 5 was used for collecting data and STATA 16 was used for analysis. Multivariable logistic regression was applied to compute the adjusted odd ratio (95% confidence interval) to find out the determinants of vaccine hesitancy. Three Cs model guided tools of data collection and analyses. More than one fourth (28%) of the participants were vaccine-hesitant whereas 34.6% of participants had no confidence in the vaccine. Other reasons were complacency (40.6%) and convenience (35.9%). Vaccine hesitancy was significantly associated with gender [AOR = 2.40 (1.12-5.16)] and trust in government [AOR = 0.18 (0.08-0.45)] but no association with age group, political affiliation and source of information about the vaccine. It is important to build the trust of people in vaccines, make it convenient and resolve the issues that are making them complacent. The health system needs to involve non-governmental organisations to reach out to those for whom there are issues of availability and approach.
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