Paradoxical association between atrial fibrillation/flutter and high cholesterol over age 75 years: The Kuakini Honolulu Heart Program and Honolulu-Asia Aging Study

Sex-related differences in the impact of nutritional status on length of hospital stay in atrial fibrillation: a retrospective cohort study

Background

Nutritional status is related to the length of hospitalization of patients with atrial fibrillation (AF). The aim of this study is to assess the prognostic impact of nutritional status and body mass index on length of hospital stay (LOHS) among patients with AF relative to their sex.

Methods

A retrospective analysis of the medical records of 1,342 patients admitted urgently with a diagnosis of AF (ICD10: I48) to the Cardiology Department (University Hospital in Wroclaw, Poland) between January 2017 and June 2021.

Results

In the study group, women were significantly older than men (72.94 ± 9.56 vs. 65.11 ± 12.68, p < 0.001). In an unadjusted linear regression model, malnutrition risk was a significant independent predictor of prolonged hospitalization in men (B = 1.95, p = 0.003) but not in women. In the age-adjusted linear regression model, malnutrition risk was a significant independent predictor of prolonged hospitalization in men (B = 1.843, p = 0.005) but not in women. In the model adjusted for age and comorbidities, malnutrition risk was a significant independent predictor of prolonged hospitalization in men only (B = 1.285, p = 0.043). In none of the models was BMI score a predictor of LOHS in either sex.

Conclusion

The risk of malnutrition directly predicts the length of hospital stays in men but not women. The study did not find a relationship between body mass index and length of hospital stay in both women and men.

The positive association between white blood cell count and metabolic syndrome is independent of insulin resistance among a Chinese population: a cross-sectional study

Background

The association between white blood cells (WBCs) and metabolic syndrome (MS) has been consistently reported in previous studies using regional samples. However, it remains unclear whether this relationship has urban-rural differences and is independent of insulin resistance using a large-scale representative sample. Additionally, accurate risk prediction in patients with MS is crucial for developing targeted interventions to enhance the quality of life and prognosis of patients.

Aims

The aims of this study were (1) to examine the cross-sectional association between WBCs and MS among the national population and analyze the urban-rural difference and whether insulin resistance plays a moderator effect in this association and (2) to describe the performance to predict MS using machine learning (ML) models.

Design

A cross-sectional study was performed using 7,014 data from the China Health and Nutrition Survey (CHNS).

Methods

WBCs were analyzed using an automatic hematology analyzer and MS was defined according to the criteria of the American Heart Association scientific statements of 2009. Variables on sociodemographic characteristics (sex, age, and residence), clinical laboratory (BMI and HOMA-IR), and lifestyle characteristics (smoking and drinking status) were used to construct ML models to predict MS [logistic regression (LR) and multilayer perceptron (MLP) neural network].

Results

We found that 21.1% of participants (1,479/7,014) were classified as having MS. In multivariate logistic regression (including insulin resistance), the result revealed a significant positive association between WBCs and MS. The odds ratios (95% CI) for MS with increasing WBC level were 1.00 (reference), 1.65 (1.18, 2.31), and 2.18 (1.36, 3.50) (p for trend: 0.001). For two ML algorithms, two models showed adequate calibration and good discrimination, but the MLP showed better performance (AUC-ROC = 0.862 and 0.867).

Conclusion

With the aim of confirming the association between WBCs and MS, this cross-sectional study is the first to show that maintaining normal WBC count levels is helpful to prevent the development of MS, and this association is independent of insulin resistance. The results also showed that the MPL algorithm represented a more prominent predictive performance to predict MS.

Relationship between nutritional status and length of hospital stay among patients with atrial fibrillation - a result of the nutritional status heart study

Background

Nutritional status is related to the prognosis and length of hospital stay (LOHS) of patients with atrial fibrillation (AF). This study aimed to assess how nutritional status affects LOHS for patients with AF.

Methods

We performed retrospective analysis of the medical records of 1,813 patients admitted urgently with a diagnosis of AF to the Institute of Heart Diseases of the University Clinical Hospital in Wroclaw, Poland.

Results

In total, 1,813 patients were included in the analysis. The average LOHS in the entire group was 3.53 ± 3.41 days. The mean BMI was 28.7 kg/m² (SD: 5.02). Patients who were hospitalized longer were statistically more likely to have a Nutritional Risk Score (NRS) ≥3 (p = 0.028). A higher percentage of longer hospitalized patients with LDL levels below 70 mg/dl (p < 0.001) and those with HDL ≥40 mg/dl (p < 0.001) were observed. Study participants with NRS ≥3 were an older group (M = 76.3 years), with longer mean LOHS (M = 4.44 days). The predictors of LOHS in the univariate model were age (OR = 1.04), LDL (OR = 0.99), HDL (OR = 0.98), TC (OR = 0.996), CRP (OR = 1, 02, p < 0.001), lymphocytes (OR = 0.97, p = 0.008) and in the multivariate model were age, LDL (mg/dl), HDL (mg/dl), Na, and K.

Conclusion

For nutritional status, factors indicating the risk of prolonged hospitalization in patients with AF are malnutrition, lower serum LDL, HDL, potassium, and sodium levels identified at the time of admission to the cardiology department. Assessment of nutritional status in patients with AF is important both in the context of evaluating obesity and malnutrition status, as both conditions can alter the prognosis of patients. Further studies are needed to determine the exact impact of the above on the risk of prolonged hospitalization.