ABSTRACT
INTRODUCTION: The interpretation of quantitative test results requires the availability of appropriate reference intervals (RIs). Every laboratory has been advised by scientific literature and reagent manufacturers to establish RIs for all analytes. Measuring RIs using direct methods is very costly, and it poses ethical and practical challenges. To overcome these challenges, indirect methods, such as Hoffman, and newer automated approaches, such as KOSMIC and refineR, are used to verify RIs for thyroid hormones. OBJECTIVE: To verify RIs for thyroid hormones in adult patients using Hoffman, KOSMIC and refineR methods and to compare these with reference ranges given in kit literature or standard textbooks. MATERIALS AND METHODS: The observed values (results) of thyroid hormone were collected from the LIS (Laboratory Information System) of the Biochemistry Department at the B. J. Medical College and Civil Hospital in Ahmedabad between 1 January 2021 and 31 May 2022. Hoffman, KOSMIC and refineR methods were used to verify the RIs. The computerised Hoffman approach, which Katayev et al. describe, is a simple method for determining RI from hospital data. Zierk et al. pre-validated and suggested the KOSMIC method based on Python programming, whereas refineR was proposed by Tatjana et al. based on R programming language. RESULTS: Hoffman, KOSMIC and refineR's indirect RI techniques revealed comparable results with kit literature in free T3 and T4, whereas higher upper reference limits of thyroid-stimulating hormone (TSH) compared to kit literature were observed with KOSMIC and refineR methods. However, the computerised Hoffman method revealed comparable results with TSH also. CONCLUSION: Indirect approaches, such as Hoffman, KOSMIC and refineR, provide reliable RI verification for free T3 and T4 utilising patient samples obtained from LIS. However, the manual Hoffman method provides reliable RI verification for TSH data derived from the hospital population as compared to automated approaches, such as KOSMIC and refineR.
ABSTRACT
Background The high prevalence of pneumonia and renal involvement in coronavirus disease 2019 (COVID-19) leads to frequent acid-base abnormalities in serious patients and affects prognosis. In this study, we aimed to assess the arterial blood gas (ABG) and acid-base patterns in COVID-19 patients admitted to a tertiary care hospital. Methodology A retrospective observational study was conducted in a designated COVID-19 hospital involving 267 reverse transcription-polymerasechain reaction-positive COVID-19 patients. Demographic and laboratory data including ABG data within the ï¬rst day after admission and in patients with multiple ABG analyses, only the first measurement was collected and analyzed statistically, including its association with comorbidities. Results The most common age group of the patients was 51-60 years (30.8%), with a male predominance (male:female = 2.7:1). The most common comorbidities were hypertension, diabetes mellitus, and chronic obstructive pulmonary disease found in 147 (55%) COVID-19 patients. Alkalosis and acidosis were observed in 145 (54.3%) and 50 (18.7%) patients, respectively. The most common ABG abnormality observed was primary respiratory alkalosis with secondary metabolic acidosis in 67 (25.1%) patients, followed by primary respiratory alkalosis with secondary metabolic alkalosis in 54 (20.2%) patients. Statistically significant negative correlation was found with PaCO2 and pH (r = -0.530, p < 0.0001), statistically significant positive correlation was found between pH and base (r = 0.533, p < 0.0001), pH and TCO2 (r = 0.260, p < 0.0001), and pH and HCO3 (r = 0.354, p < 0.0001). Conclusions Acid-base abnormalities are commonly encountered in COVID-19 patients. Respiratory alkalosis as a part of a single or mixed pattern on ABG was the most common pattern found in critically ill COVID-19 patients. ABG on admission in moderate-to-severe COVID-19 patients can help in the early correction of metabolic abnormalities leading to improved patient outcomes.
