Objective: To investigate the effect of temperature on hospital admission among patients with chronic systolic heart failure (CSHF).
Methods: Data regarding in-hospital patients with CSHF were gathered from 12 hospitals in Hubei province, between 2000 and 2010. Patients with a history of congenital heart disease and the history of cancer from this series, were excluded. Chi-square (χ(2)) tests and t tests were used for descriptive analysis. Univariate and multivariate logistic regression methods were performed to determinate the risk of hospital admission of every month to compare with the previous one. We used 2-tailed 95% confidence interval (CI), and tests with P < 0.01 to consider the significant levels, statistically. We also used the SPSS 13.0 for Windows, release 15, 2006 (SPSS Inc, Chicago, Ill) for data analyses.
Results: (1) 48 964 patients were enrolled in the present study. The numbers of admission increased 18.71%, 13.84%, -21.90%, -34.62%, -21.97%, -3.81%, -2.04%, 10.13%, -17.13%, -0.85%, 21.54% and 42.70% from January to December when compared to the average number of admission. (2) The odds ratios (ORs) (95% CI, P values) of hospital admission in January, February and December were 1.09 (0.96 - 1.23, 0.54), 0.98 (0.84 - 1.10, 0.46) and 0.96 (0.84 - 1.08, 0.59), respectively in females which did not show any significant differences when compared to the number in August. However the ratios were 0.61 (0.54 - 0.69, < 0.01), 0.80 (0.68 - 0.92, < 0.01) and 0.73 (0.64 - 0.83, < 0.01), respectively, in males that showed significant differences when, compared to the figures in August. (3) The OR of admission increased more when temperature got lower for patients with coronary artery disease, hypertension heart disease or rheumatic heart disease, but not with dilated cardiomyopathy. (4) The OR of admission showed a different impact on patients with different occupation, along with the change of temperature. Low or high temperature did not seem to have different effects on the OR of admission in patients who were free-lanced or unemployed.
Conclusion: Temperature seemed to have significant effects on the risk of admission, which related to gender, etiology or occupation.
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