Assessment of hypokalemia and clinical prognosis in Patients with COVID-19 in Yangzhou, China

Real-World Evidence on Levetiracetam-Induced Hypokalemia: An Active Comparator Cohort Study

BACKGROUND

Levetiracetam is an anti-seizure medication (ASM) with an established safety profile. However, a potential safety signal of hypokalemia following levetiracetam use was published in the World Health Organization newsletter.

OBJECTIVE

To investigate the possible causal association between the use of levetiracetam and the development of hypokalemia.

METHOD

This was a new-user, active-comparator retrospective cohort study using Real-world Evidence Research Network data at the Saudi Food and Drug Authority from 2016 to 2022. Adults (≥ 18 years old) with an incident prescription for either levetiracetam or carbamazepine were followed for up to 6 months from the prescription date. Hypokalemia was ascertained by using diagnostic code (i.e., E87.6) or by serum potassium level below 3.5 mmol/L. A Cox proportional hazards model, adjusted with stabilized inverse probability of treatment weight, was fitted to compare the hazard of hypokalemia between levetiracetam and carbamazepine exposed patients.

RESULTS

A total of 8,982 patients entered the study cohort. The incidence rate of hypokalemia was 303 cases per 10,000 patient-years in the levetiracetam-exposed cohort compared to 57 cases per 10,000 patient-years among carbamazepine users. Compared to carbamazepine users, patients exposed to levetiracetam had an adjusted hazard ratio related to induced hypokalemia of 1.99 (95% confidence interval, 0.88-4.49). Results of sensitivity analyses were comparable to the main analysis.

CONCLUSION

The hazard ratio for hypokalemia with the use of levetiracetam versus carbamazepine was statistically comparable. However, the potential association between levetiracetam use and hypokalemia cannot be ruled out given the elevated hazard ratios from the main and sensitivity analyses. Further studies may provide a more precise assessment of this association.

Approaching Personalized Medicine: The Use of Machine Learning to Determine Predictors of Mortality in a Population with SARS-CoV-2 Infection

The COVID-19 pandemic demonstrated the need to develop strategies to control a new viral infection. However, the different characteristics of the health system and population of each country and hospital would require the implementation of self-systems adapted to their characteristics. The objective of this work was to determine predictors that should identify the most severe patients with COVID-19 infection. Given the poor situation of the hospitals in the first wave, the analysis of the data from that period with an accurate and fast technique can be an important contribution. In this regard, machine learning is able to objectively analyze data in hourly sets and is used in many fields. This study included 291 patients admitted to a hospital in Spain during the first three months of the pandemic. After screening seventy-one features with machine learning methods, the variables with the greatest influence on predicting mortality in this population were lymphocyte count, urea, FiO2, potassium, and serum pH. The XGB method achieved the highest accuracy, with a precision of >95%. Our study shows that the machine learning-based system can identify patterns and, thus, create a tool to help hospitals classify patients according to their severity of illness in order to optimize admission.

Incidence, Risk Factors and Prognosis of Hypokalaemia in Patients with Normokalaemia at Hospital Admission

Background

Hypokalaemia (K+<3.5 mmol/L) is observed in 20% of hospitalised patients. Previous studies have often dealt with the symptoms, prevalence and risk factors in hospitalised patients. Very few studies have dealt with hospital-induced hypokalaemia. The aim was to determine the incidence, predisposing risk factors and prognosis of patients developing hypokalaemia after admission.

Materials and Methods

A prospective observational study was performed for two months. Patients with at least two potassium values after admission and normal K values at admission were considered for inclusion. Clinical features, diagnoses, laboratory reports and treatment details, including antibiotics, were noted.

Results

A total of 653 patients were studied; 138 (21.1%) developed hypokalaemia. Diabetes, ischaemic heart disease (IHD), heart failure, chronic kidney disease, hypertension, chronic liver disease and chronic obstructive pulmonary disease (COPD) were the most associated comorbidities. Urea, creatinine, transaminases and neutrophilia at admission differed significantly between those with and without hypokalaemia groups. Most patients developed mild hypokalaemia (78.2%). Hypokalaemia developed mostly on the second (22.4%) and third (24.6%) days of hospitalisation. Antibiotics were used in 60% of patients. The potassium values returned to normal within 2.5 ± 1.9 days. Three patients subsequently developed hyperkalaemia.

Conclusion

Patients admitted under general medicine mostly developed mild hypokalaemia, even if they had multiple risk factors for developing hypokalaemia. Inpatient hypokalaemia had an incidence of 21%. An overwhelming majority (~88%) had at least one risk factor. Hypokalaemia was not attributed to causing mortality in any patient.

Associations between laboratory variables and clinical features in patients hospitalized with COVID-19 after non-mRNA vaccination in China: A cross-sectional study

Objectives

Based on the data during the outbreak of COVID-19 in Wuxi city in China, we explored the relationship between laboratory variables and clinical features in patients hospitalized with COVID-19 after non-mRNA vaccination, and attempted to identify the significant impact of vaccination and COVID-19 infection on humans.

Methods

A retrospective observational cohort study was carried out. Patients who received non-mRNA COVID-19 vaccines and were hospitalized with COVID-19 between June 28, 2022, and July 24, 2022 were included. The correlation between different vaccine statuses, the time to negative PCR test, and biochemical parameters were investigated.

Results

All patients had a mild COVID-19 disease. The number of vaccine doses exerted no effects on the time to negative PCR test (P = 0.559). No differences were evident among inactivated, adenoviral-vectored, and recombinant subunit vaccines in the time to negative PCR test.Patients who just received one dose had significantly lower blood glucose levels than those who received three doses (P = 0.024), whereas two doses had no effect on blood glucose levels (one dose vs. two doses, P = 0.223; two doses vs. three doses, P = 0.457).Body temperature (β = 0.168, P = 0.011) and the percentage of lymphocytes (β = -0.219, P = 0.001) were substantially correlated with the time to COVID-19 negative PCR test. The prolonged stay was linked to a rise in GOT that fell within the usual range (P = 0.025).The percentage of lymphocytes (P = 0.007) and serum potassium (P = 0.004) were concordant with the marked change in body temperature.

Conclusions

The dose and type of vaccination had no effect on the time to COVID-19 negative PCR test in patients with mild COVID-19. Comparing the first dose with the booster dose, the blood glucose levels increased within the normal range. The period at which the COVID-19 nucleic acid turned negative correlated with body temperature, the proportion of lymphocytes, GOT, and serum potassium.