Decision-maker informed optimal policy design. by Hongru Du (4640212)

Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Data_Sheet_1_Sleeping <6.55 h per day was associated with a higher risk of low back pain in adults aged over 50 years: a Korean nationwide cross-sectional study.PDF by Dexin Hu (19710271)

“…Each additional hour of sleep was associated with a 13.6% decrease in the risk of LBP. No significant association was observed between sleep duration ≥6.55 h and the risk of LBP. …”

Renal function and risk of dementia: a Mendelian randomization study by Haowen Huang (1430386)

“…</p> <p>The findings indicate a significant correlation between each unit increase in cystatin C-based estimated glomerular filtration rate (eGFR-cys) levels was significantly associated with a reduction in the incidence of late-onset Alzheimer’s disease (LOAD) (IVW: OR = 0.35, 95% CI: 0.13–0.91, <i>p</i> = 0.031). …”

The sequence for qPCR primers and shRNA. by Xiaoming Liu (47653)

“…<div><p>Chronic kidney disease (CKD) is a global health issue that significantly threatens human health, with its incidence increasing annually. …”

Predictors in ordinal regression model for GDS. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Classification of hand grip strength. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Rating scale for functional severity [28]. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Regression model coefficients. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

ICOPE screening positive participant’s responses. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

WHO BMI classification for adults. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Histogram of the extracted parameters. by Qiuyu Du (20760848)

“…Logistic regression (n = 93) showed that a less steep contrast gradient (decreasing by 10 Hounsfield unit/%) was associated with a reduction in odds of the following short-term adverse outcomes: 48.1% for intensive care unit admission (odds ratio [OR] = 0.519, 95% confidence interval [CI]: 0.306–0.804), 29.3% for oxygen therapy >24 hours (OR = 0.707, 95% CI: 0.496–0.976), 60.6% for reperfusion therapy (OR = 0.394, 95% CI: 0.178–0.682), 57.5% for vasopressor therapy (OR = 0.425, 95% CI: 0.194–0.741), and 50.2% for PE-related death (OR = 0.498, 95% CI: 0.246–0.915). …”

Flow chart of research object screening. by Wenyao Xie (21567889)

“…Notably, these associations were significant only in non-cancer populations (testosterone: OR=0.97, P < 0.001; estradiol: OR=1.64, P < 0.001), and generally absent in cancer patients except for older cancer patients (≥60 years) where testosterone maintained a significant negative correlation with ALI (OR=0.96, P = 0.020). …”

Tracheostomy data. by Rajesh Kamath (17179960)

“…Patients with an ET had a significantly shorter ICU LOS median of 15 days (IQR 13,17) and a mechanical ventilation median of 13 days (IQR 11,14) than LT patients who had an ICU LOS median of 33 days (IQR 30,36) and a mechanical ventilation median of 31 days (IQR 27,33) respectively.…”

Flow diagram of patient selection. by Rajesh Kamath (17179960)

“…Patients with an ET had a significantly shorter ICU LOS median of 15 days (IQR 13,17) and a mechanical ventilation median of 13 days (IQR 11,14) than LT patients who had an ICU LOS median of 33 days (IQR 30,36) and a mechanical ventilation median of 31 days (IQR 27,33) respectively.…”

Table6_Use of non-specific immunoglobulins in Catalonia in three third-level hospitals: a descriptive analysis of a hospital-prescribed medication registry.docx by J. Riera-Arnau (20431328)

“…In the sensitivity analysis, the A-level usage rate decreased to one-third and the B-level usage rate increased by 2–3 times. …”

Table4_Use of non-specific immunoglobulins in Catalonia in three third-level hospitals: a descriptive analysis of a hospital-prescribed medication registry.docx by J. Riera-Arnau (20431328)

“…In the sensitivity analysis, the A-level usage rate decreased to one-third and the B-level usage rate increased by 2–3 times. …”

Table2_Use of non-specific immunoglobulins in Catalonia in three third-level hospitals: a descriptive analysis of a hospital-prescribed medication registry.docx by J. Riera-Arnau (20431328)

“…In the sensitivity analysis, the A-level usage rate decreased to one-third and the B-level usage rate increased by 2–3 times. …”

Table8_Use of non-specific immunoglobulins in Catalonia in three third-level hospitals: a descriptive analysis of a hospital-prescribed medication registry.docx by J. Riera-Arnau (20431328)

“…In the sensitivity analysis, the A-level usage rate decreased to one-third and the B-level usage rate increased by 2–3 times. …”

Table5_Use of non-specific immunoglobulins in Catalonia in three third-level hospitals: a descriptive analysis of a hospital-prescribed medication registry.docx by J. Riera-Arnau (20431328)

“…In the sensitivity analysis, the A-level usage rate decreased to one-third and the B-level usage rate increased by 2–3 times. …”