Sentence examples for multivariable model revealed from inspiring English sources

The multivariable model revealed no statistically significant IRR for the subgroup of women who had used only OC or MHT.

A multivariable model revealed that the effects of age and GDM status remained significant after additional adjustment for time after index pregnancy.

The final multivariable model revealed the overall associations of factors measured at any particular event with the risk of a subsequent suspected NAT event, after adjustment for other measured risk factors.

When evaluated with debulking status and response to primary platinum-based therapy, grade, and age, the Cox proportional hazards multivariable model revealed that the Transcription/CREB pathway gene expression signature score was an independent variable associated with survival (P=0.01).

Multivariable modeling revealed that implementation of PDMPs was associated with an 11% increase in drug overdose mortality (aRR = 1.11; 95% CI: 1.02 1.21), with the greatest increase observed in PDMPs that imposed no expectation on practitioners (aRR = 1.17; 95% CI: 1.02 1.34; Table 1).

Multivariable modeling revealed that mode and duration of mechanical ventilation, the norepinephrine dose, and HBE had statistically significant influences.

Our final multivariable models revealed that after controlling for the aforementioned potential confounders, there was no significant difference in mean BMC between ASD cases and TD controls (11.5 μg/L for ASD cases and 11.9 μg/L for TD controls; P = 0.48).

However, the multivariable regression model revealed that HCV patients aged less than 50 years had a significant 2.03-fold higher risk of breast cancer (OR = 2.03, 95% CI = 1.23-3.34) (Table 3).

Multivariable linear regression model revealed that MC4R (rs17782313) T>C (p = 0.02) and TMEM18 (rs6548238) C>T (p = 0.01) were significant predictors of physical activity volume, while SH2B1 (rs7498665) A>G trended towards significance (p = 0.08).

Univariable analyses were used to identify differences between hospital survivors and non-survivors, and a multivariable logistic regression model revealed independent determinants of hospital mortality.

Multivariable logistic regression model revealed that only pregnancy status, maternal illness on the date of interview, educational level of provider and number of gravida were significantly associated with prescribed drug use during pregnancy.