Spss 18.0 for window

Statistical analysis was performed using SPSS 18.0 for Windows (IBM, Armonk, NY, USA). We used the chi-square test or the Fisher’s exact test to evaluate categorical data. The Mann–Whitney non-parametric test was used for comparisons of continuous data.
The Spearman’s rank correlation was used for correlation of methylation levels and bone marrow blast levels.
Overall survival (OS) was calculated from diagnosis day until the day of death or the last follow-up date (censored on 31 December 2012). OS was analyzed according to the Kaplan-Meier method and the log-rank test. The Cox proportional hazard regression model was used for the adjustment of independent prognostic factors in multivariate survival analysis. Two-tailed P values ≤ 0.05 were considered statistically significant.

All statistical analyses were performed using SPSS 18.0 for Windows (IBM, Armonk, NY, USA). Continuous variables were presented as the mean ± standard deviation (SD) or as median and interquartile range (IQR) according to the distributions. Categorical variables were presented as counts and percentages. To compare the variation between two groups, t-tests or Mann–Whitney tests were used in continuous variables; while Pearson’s Chi‑square test was used in categorical variables and presented with odds ratio (OR) and 95% confidence intervals (CI). In addition, Chi-square tests linear-by-linear association were used to compare the survival rates among discharged years, BW categories (per 100 g), regions and the major complication among BW categories (per 100 g), respectively. To further clarify the influencing cofactors (BW, GA, discharged year [1 = 2008, 2 = 2009, 3 = 2010, 4 = 2011, 5 = 2012, 6 = 2013, 7 = 2014, 8 = 2015, 9 = 2016, 10 = 2017], regions of economic development level [1 = low-level, 2 = middle-level, 3 = high-level] and type of hospital [1 = general hospitals, 2 = specialist hospitals]) to the outcome (0 = nonsurvivor, 1 = survivor) of the ELBW infants, binary logistic regression was used. The test level was set at α = 0.05, and the cutoff of p < 0.05 was considered statistically significant.

Data were analysed using SPSS 18.0 for Windows (IBM, Chicago, IL, USA). Categorical data were expressed as absolute or relative frequencies, while continuous data were expressed as mean ± SD. Sensitivities of the conventional and LCT methods were compared using the χ² test. The threshold of significance for all statistical tests was defined as a two-sided P < 0.05.

All statistical analyses were performed using SPSS 18.0 for Windows (IBM, Armonk, NY, USA). Continuous variables were shown as means ± standard deviation (SD) or as medians (P25, P75) when their distributions were highly skewed, which were analyzed using t-tests or Mann-Whitney tests. Categorical variables arepresented as rates and odds ratio with 95% confidence intervals (CI), which were analyzed using Chi-square tests. Multivariate analyses were performed by using logistic regression to analyze the risk factors of survival in preterm infants. P < 0.05 was considered statistically significant.