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The single variable analyses are listed in table 1.
Diagnosing sepsis can be challenging because clinical signs and results of laboratory variable analyses are not unique for septic patients and there is no reliable diagnostic marker.
Instrumental variable analyses are well established in non-healthcare settings such as econometrics as a means of adjusting for unmeasured confounding.
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All variable analyses were performed by using the SAS 9.2 (SAS Institute Inc., Cary, NC, USA).
However, on-study and baseline PP studied in the continuous variable analyses were associated with significant worsening of eGFR.
Multiple variable analyses were conducted using stepwise standardized logistic regression (SLR) with odds ratios and 95% Confidence intervals (CI).
The results of the multi-variable analyses are shown in table 2. The presence of a person with respiratory disease in the home, the belief that pollution is harmful, occupational class, home ownership and reporting noise and other peoples smoking as problems were all very strongly and independently associated (<0.001) with reporting behaviour.
Normal distribution of any variable analysed was checked by Kolgomorov Smirnov test.
The main variable analysed was TC/HDL ratio.
Another variable analysed was the relation between the occurrence of back pain and gender.
All the variable analysed were statistically significant also according to the US Endocrinology Society vitamin D status classification (P < 0.0001) (29).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com