Sentence examples for multivariable analysis adjusting from inspiring English sources

Exact(38)

Multivariable analysis adjusting for patient- and hospital-related characteristics indicated that ACEI/ARB use independently had no impact on the risk of developing new-onset AF compared with non-users (adjusted HR: 0.99; 95% CI: 0.94, 1.04).

Multivariable analysis adjusting for potential confounders confirmed that age, both as a continuous and categoric variable, did not impact odds of functional improvement after OHT.

On multivariable analysis adjusting for patient and clinicopathologic characteristics, metformin use was independently associated with a decreased risk of mortality (hazard ratio [HR] = 0.79, 95 % CI 0.67-0.93, p = 0.005).

All the models were used in multivariable analysis adjusting for the duration of mechanical ventilation (< 7-day vs. 7 days or more), chronic respiratory failure (Yes/No) and MRC (< 48 vs. 48 or more).

Awareness of MOH as a side effect of regular analgesic use was noted in just 113 (23%) individuals, 74 (38%) in the healthcare educated group and 39 (14%) in the non-healthcare educated group (p < 0.001, Figure1A).The difference between the groups was significant (p < 0.001) in a multivariable analysis adjusting for age (p = 0.56) and gender (p = 0.82).

In a multivariable analysis, adjusting for sex, area, and number of doses, the OR was further reduced.

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Similar(22)

In a multivariable analysis adjusted for demographic and ECG characteristics, higher IIIQ+S values remained independently associated with HCM compared with athletes (OR=4.2 per 0.5mV, p<0.001).

Intraocular pressure fluctuation was not a risk factor for conversion to glaucoma both in univariable analysis (hazard ratio [HR], 1.30 per 1 mmHg higher; 95% confidence interval [CI], 0.76-1.96; P = 0.092) and in multivariable analysis (adjusted HR, 1.08 per 1 mmHg higher; 95% CI, 0.79-1.48; P = 0.620).

Characteristics remaining significant in a multivariable analysis adjusted for age.

Multivariable analysis, adjusted for confounding factors, was used to determine the hazard ratio (HR) for death.

Multivariable analysis adjusted for differences in age, gender, race/ethnicity, height and smoking history.

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