ABSTRACT
Background: Almost every indoor patient requires some form of intravenous (IV) fluids and its infusion rate should be proper as recommended for best treatment outcomes. To overcome the same, a simple, quick and easily applicable new method for drip drop rate calculation is proposed, which is user-friendly at bedside and doesn’t require mathematical skills or help.Methods: Author compared this novel innovative method (IM) of IV fluid drip drop rate method for both regular macro and micro drop infusion set against conventional mathematical calculation method (MC) of infusion in various IV fluid indoor orders and assessed for time-to-initiation of treatment (TI) required and its accuracy. Ten resident doctors and ten nursing staff participated to grade both conventional and novel methods by using pre-printed forms of various parameters like time consumption, comfort level, accuracy and applicability in ward and these both methods were scored on a scale of 1 to 10.Results: Conventional method (CM) required 14.23±1.10seconds, while novel method (IM) required average 3.63±0.73seconds for calculation of drop rate. Average grading for conventional method was 3.63±0.49 and for novel method was 7.84±0.6 out of 10.Conclusions: Novel method of IV fluid drip drop rate formula is easy, quick and superior in comparison to conventional method and it doesn’t require any additional instrumental help. It is good alternative to conventional formula for IV drip drop rate calculation in absence of infusion pump.
ABSTRACT
Aims We compared various components of blood pressure and arterial stiffness of healthy control with those of coronary artery disease (CAD) patients using BP+ machine™. Methods In this prospective, case-control study, total 585 individuals of both the genders were enrolled. The study population consisted of 277 controls (healthy siblings of diseased subjects not having CAD – group A) and 308 CAD patients (group B). Age and sex adjusted regression and receiver operative curve (ROC) analysis was performed to assess the strength of association of these parameters. Results We found that mean systolic blood pressure (SBP) (137.14 ± 22.49 vs. 129.26 ± 19.86), central systolic blood pressure (CSBP) (130.78 ± 21.89 vs. 117.53 ± 17.98), augmentation index (AI) (108.55 ± 44.98 vs. 49.38 ± 21.03) and pulse rate variability (98.82 ± 231.09 vs. 82.86 ± 208.77) were significantly (p < 0.05) higher in CAD population as compared to healthy counterparts. Left ventricular contractibility as measured by dP/dt was significantly lower in CAD patients. All these parameters were significantly abnormal in CAD as compared to healthy control population irrespective of the gender of the patient except for SBP in females. Both – odds ratio (1.108; 95% CI: 1.081–1.135; p < 0.0001) and ROC analysis (AUC: 0.937; 95% CI: 0.919–0.956; p < 0.0001) showed AI as the strongest predictor of CAD, closely followed by CSBP. Conclusion Central aortic blood pressure parameters such as AI and CSBP measured noninvasively with BP+ machine could be the effective predictors of CAD in Asian Indians.