scholarly journals Base-excess chloride; the best approach to evaluate the effect of chloride on the acid-base status: A retrospective study

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250274
Author(s):  
Bulent Gucyetmez ◽  
Filiz Tuzuner ◽  
Hakan Korkut Atalan ◽  
Uğur Sezerman ◽  
Kaan Gucyetmez ◽  
...  
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Base Excess ◽  
Tertiary Care ◽  
Strong Ion Difference ◽  
Acid Base ◽  
Entire Cohort ◽  
Acid Base Status ◽  
Evaluation Approaches

To practically determine the effect of chloride (Cl) on the acid-base status, four approaches are currently used: accepted ranges of serum Cl values; Cl corrections; the serum Cl/Na ratio; and the serum Na-Cl difference. However, these approaches are governed by different concepts. Our aim is to investigate which approach to the evaluation of the effect of Cl is the best. In this retrospective cohort study, 2529 critically ill patients who were admitted to the tertiary care unit between 2011 and 2018 were retrospectively evaluated. The effects of Cl on the acid-base status according to each evaluative approach were validated by the standard base excess (SBE) and apparent strong ion difference (SIDa). To clearly demonstrate only the effects of Cl on the acid-base status, a subgroup that included patients with normal lactate, albumin and SIG values was created. To compare approaches, kappa and a linear regression model for all patients and Bland-Altman test for a subgroup were used. In both the entire cohort and the subgroup, correlations among BECl, SIDa and SBE were stronger than those for other approaches (r = 0.94 r = 0.98 and r = 0.96 respectively). Only BECl had acceptable limits of agreement with SBE in the subgroup (bias: 0.5 mmol L-1) In the linear regression model, only BECl in all the Cl evaluation approaches was significantly related to the SBE. For the evaluation of the effect of chloride on the acid-base status, BECl is a better approach than accepted ranges of serum Cl values, Cl corrections and the Cl/Na ratio.

scholarly journals Base-excess chloride; the best approach to evaluating the effect of chloride on the acid- base status: a retrospective study

2020 ◽  
Author(s):  
Bulent Gucyetmez ◽  
Filiz Tuzuner ◽  
Hakan Korkut Atalan ◽  
Ugur Sezerman ◽  
Kaan Gucyetmez ◽  
...  
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Base Excess ◽  
Strong Ion Difference ◽  
Acid Base ◽  
Standard Base Excess ◽  
Serum Chloride ◽  
Acid Base Status ◽  
Standard Base

Abstract Background: To determine the effect of chloride on the acid-base status, four approaches are currently used: 1) accepted ranges of serum chloride values; 2) chloride corrections, such as chloride deficiency/excess and chloride modification; 3) the Cl/Na ratio; and 4) the sodium- chloride difference, such as base-excess chloride. However, these approaches are governed by different concepts, and they can evaluate the effects of chloride on the acid-base status differently. Our aim is to investigate which approach to the evaluation of the effect of chloride is the best.Methods: In this retrospective cohort study, 2529 critically ill patients who were admitted to the tertiary care unit were evaluated between 2011 and 2018. Patient characteristics and blood gas parameters at the ICU admission and outcomes were recorded. The effects of chloride on the acid-base status according to each evaluative approach were validated by the standard base excess and apparent strong ion difference. To compare approaches, kappa and Bland-Altman tests and a linear regression model were used. Results: In the linear regression model for all patients, only base-excess chloride in all the chloride evaluation approaches was significantly related to the standard base excess. In the subgroup, the correlation and limits of agreement between base-excess chloride and the standard base excess were the strongest (r2=0.92 p<0.001 bias: 0.5mmol/L). Conclusions: For the evaluation of the effect of chloride on the acid-base status, base-excess chloride is a better approach than accepted ranges of serum chloride values, chloride corrections and the Cl/Na ratio.

scholarly journals Acid-Base Effects of a Bicarbonate-Balanced Priming Fluid during Cardiopulmonary Bypass: Comparison with Plasma-Lyte 148. A Randomised Single-Blinded Study

2008 ◽  
Vol 36 (6) ◽  
pp. 822-829 ◽  
Author(s):  
T. J. Morgan ◽  
G Power ◽  
B. Venkatesh ◽  
M. A. Jones
Keyword(s):  
Metabolic Acidosis ◽  
Cardiopulmonary Bypass ◽  
Base Excess ◽  
Strong Ion Difference ◽  
Acid Base ◽  
Elective Cardiac Surgery ◽  
Standard Base Excess ◽  
Acid Base Status ◽  
Standard Base ◽  
Normal Acid

Fluid-induced metabolic acidosis can be harmful and can complicate cardiopulmonary bypass. In an attempt to prevent this disturbance, we designed a bicarbonate-based crystalloid circuit prime balanced on physico-chemical principles with a strong ion difference of 24 mEq/l and compared its acid-base effects with those of Plasma-Lyte 148, a multiple electrolyte replacement solution containing acetate plus gluconate totalling 50 mEq/l. Twenty patients with normal acid-base status undergoing elective cardiac surgery were randomised 1:1 to a 2 litre prime of either bicarbonate-balanced fluid or Plasma-Lyte 148. With the trial fluid, metabolic acid-base status was normal following bypass initiation (standard base excess 0.1 (1.3) mEq/l, mean, SD), whereas Plasma-Lyte 148 produced a slight metabolic acidosis (standard base excess -2.2 (2.1) mEq/l). Estimated group difference after baseline adjustment was 3.6 mEq/l (95% confidence interval 2.1 to 5.1 mEq/l, P=0.0001). By late bypass, mean standard base excess in both groups was normal (0.8 (2.2) mEq/l vs. -0.8 (1.3) mEq/l, P=0.5). Strong ion gap values were unaltered with the trial fluid, but with Plasma-Lyte 148 increased significantly on bypass initiation (15.2 (2.5) mEq/l vs. 2.5 (1.5) mEq/l, P <0.0001), remaining elevated in late bypass (8.4 (3.4) mEq/l vs. 5.8 (2.4) mEq/l, P <0.05). We conclude that a bicarbonate-based crystalloid with a strong ion difference of 24 mEq/l is balanced for cardiopulmonary bypass in patients with normal acid-base status, whereas Plasma-Lyte 148 triggers a surge of unmeasured anions, persisting throughout bypass. These are likely to be gluconate and/or acetate. Whether surges of exogenous anions during bypass can be harmful requires further study.

scholarly journals Effect of the Independent Acid Base Variables on Anion Gap Variation in Cardiac Surgical Patients: A Stewart-Figge Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Michalis Agrafiotis ◽  
Ilias Keklikoglou ◽  
Sofia Papoti ◽  
George Diminikos ◽  
Konstantinos Diplaris ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Retrospective Study ◽  
Linear Regression ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Anion Gap ◽  
Surgical Patients ◽  
Strong Ion Difference ◽  
Strong Ion Gap ◽  
Acid Base

Purpose. To determine the effect of each of independent acid base variables on the anion gap (AG) value in cardiac surgical patients.Methods. This retrospective study involved 128 cardiac surgical patients admitted for postoperative care. The variation of AG (AGvar) between the day of admission and the first postoperative day was correlated via a multiple linear regression model with the respective variations of the independent acid base variables, that is, apparent strong ion difference (SIDa), strong ion gap (SIG), carbon dioxide (PCO2), and albumin and phosphate concentrations.Results. The variations of all the above variables contributed significantly to the prediction ofAGvar(adjustedR2=0.9999,F=201890.24, andP<0.001). According to the standardized coefficients (β),  SIGvar(β= 0.948,P<0.001),[Albumin]var(β= 0.260,P<0.001), and[Phosphate]var(β= 0.191,P<0.001) were the major determinants ofAGvarwith lesser contributions fromSIDa, var(β= 0.071,P<0.001) andPCO2, var(β= −0.067,P<0.001).Conclusions. All the independent acid base variables contribute to the prediction of the AG value. However, albumin and phosphate and SIG variations seem to be the most important predictors, while AG appears to be rather stable with changes in PCO2andSIDa.

Acid-base analysis during experimental anemia in rats

2000 ◽  
Vol 78 (10) ◽  
pp. 774-780 ◽  
Author(s):  
J Pesquero ◽  
V Alfaro ◽  
L Palacios
Keyword(s):  
Base Excess ◽  
Respiratory Alkalosis ◽  
Physicochemical Analysis ◽  
Weak Acid ◽  
Strong Ion Difference ◽  
Acid Base ◽  
Experimental Conditions ◽  
Physiological Relevance ◽  
Base Analysis ◽  
Acid Base Status

The present study evaluated the acid-base status of anemic rats by using two approaches of acid-base analysis: one based on the base excess (BE) calculation and the other based on Stewart's physicochemical analysis. Two sets of experimental data, derived from two different methods of inducing anemia, were used: repetitive doses of phenylhydrazine (PHZ) and bleeding (BL). A significant uncompensated respiratory alkalosis was found in both groups of anemic rats. BE increased slightly, whereas strong ion difference ([SID]) and weak acid buffers ([ATOT]) remained unchanged in anemic rats. The reasons for the absence of compensation for hypocapnia and the differences in the behaviour of acid-base variables are discussed. BE increase was considered paradoxical; its calculation was affected by the experimental conditions and BE had little physiological relevance during anemia. The absence of metabolic renal compensation in anemic rats could be due to a lower pH in the kidney due to anemic hypoxia. Finally, the changes in buffer strength related to low Hb and low Pc02 might influence plasma [SID] through counteracted shifts of strong ions between erythrocytes and plasma, finally resulting in unchanged [SID] during anemia.Key words: anemia, phenylhydrazine, bleeding, base excess, strong ion difference, non-carbonic buffers.

Physico-Chemical Analysis of Groundwater and Effect of Climatic Change in Angul-Talcher Area

2018 ◽  
Vol 6 (12) ◽  
pp. 26
Author(s):  
Aliva Bera ◽  
D.P. Satapathy
Keyword(s):  
Water Resources ◽  
Linear Regression ◽  
Regression Model ◽  
Climatic Change ◽  
Linear Regression Model ◽  
Ann Model ◽  
Quality Of Water ◽  
Physico Chemical ◽  
Simulation Based

In this paper, the linear regression model using ANN and the linear regression model using MS Excel were developed to estimate the physico-chemical concentrations in groundwater using pH, EC, TDS, TH, HCO3 as input parameters and Ca, Mg and K as output parameters. A comparison was made which indicated that ANN model had the better ability to estimate the physic-chemical concentrations in groundwater. An analytical survey along with simulation based tests for finding the climatic change and its effect on agriculture and water bodies in Angul-Talcher area is done. The various seasonal parameters such as pH, BOD, COD, TDS,TSS along with heavy elements like Pb, Cd, Zn, Cu, Fe, Mn concentration in water resources has been analyzed. For past 30 years rainfall data has been analyzed and water quality index values has been studied to find normal and abnormal quality of water resources and matlab based simulation has been done for performance analysis. All results has been analyzed and it is found that the condition is stable. 

Prediction of Surface Roughness and Optimization of Cutting Parameters in CNC Turning of Rotational Features

2020 ◽  
Vol 38 (8A) ◽  
pp. 1143-1153
Author(s):  
Yousif K. Shounia ◽  
Tahseen F. Abbas ◽  
Raed R. Shwaish
Keyword(s):  
Surface Roughness ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Feed Rate ◽  
Cutting Parameters ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Non Linear ◽  
Optimization Of Cutting Parameters

This research presents a model for prediction surface roughness in terms of process parameters in turning aluminum alloy 1200. The geometry to be machined has four rotational features: straight, taper, convex and concave, while a design of experiments was created through the Taguchi L25 orthogonal array experiments in minitab17 three factors with five Levels depth of cut (0.04, 0.06, 0.08, 0.10 and 0.12) mm, spindle speed (1200, 1400, 1600, 1800 and 2000) r.p.m and feed rate (60, 70, 80, 90 and 100) mm/min. A multiple non-linear regression model has been used which is a set of statistical extrapolation processes to estimate the relationships input variables and output which the surface roughness which prediction outside the range of the data. According to the non-linear regression model, the optimum surface roughness can be obtained at 1800 rpm of spindle speed, feed-rate of 80 mm/min and depth of cut 0.04 mm then the best surface roughness comes out to be 0.04 μm at tapper feature at depth of cut 0.01 mm and same spindle speed and feed rate pervious which gives the error of 3.23% at evolution equation.

An Enhanced Multiple Linear Regression Model for Seasonal Rainfall Prediction

2020 ◽  
Vol 10 (4) ◽  
pp. 473-483
Author(s):  
Pundra Chandra Shaker Reddy ◽  
Alladi Sureshbabu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Weather Prediction ◽  
Big Data Analytics ◽  
Multiple Linear Regression Model ◽  
Seasonal Rainfall ◽  
Climate Data ◽  
Rainfall Forecasting

Aims & Background: India is a country which has exemplary climate circumstances comprising of different seasons and topographical conditions like high temperatures, cold atmosphere, and drought, heavy rainfall seasonal wise. These utmost varieties in climate make us exact weather prediction is a challenging task. Majority people of the country depend on agriculture. Farmers require climate information to decide the planting. Weather prediction turns into an orientation in farming sector to deciding the start of the planting season and furthermore quality and amount of their harvesting. One of the variables are influencing agriculture is rainfall. Objectives & Methods: The main goal of this project is early and proper rainfall forecasting, that helpful to people who live in regions which are inclined natural calamities such as floods and it helps agriculturists for decision making in their crop and water management using big data analytics which produces high in terms of profit and production for farmers. In this project, we proposed an advanced automated framework called Enhanced Multiple Linear Regression Model (EMLRM) with MapReduce algorithm and Hadoop file system. We used climate data from IMD (Indian Metrological Department, Hyderabad) in 1901 to 2002 period. Results: Our experimental outcomes demonstrate that the proposed model forecasting the rainfall with better accuracy compared with other existing models. Conclusion: The results of the analysis will help the farmers to adopt effective modeling approach by anticipating long-term seasonal rainfall.

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