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Drabkin\'s reagent, containing 12 mM NaHCO 3 , 0.77 mM KCN and 0.88 mM K 3 Fe(CN

ID: 3224399 • Letter: D

Question

Drabkin's reagent, containing 12 mM NaHCO3, 0.77 mM KCN and 0.88 mM K3Fe(CN)6, is used to assay the concentration of hemoglobin ([Hb]) in whole blood. The light absorbance at 540 nm (ABS540) is proportional to the concentration of cyanmethemoglobin ([CyanmetHb]), which is in turn directly proportional to [Hb]. Preparation of a new Drabkin's solution requires the running of a "standard curve" to determine the relationship between ABS540 and known concentrations of [Hb]. The data in the table below are ABS540 in triplicate measures of standard samples containing standard [Hb] concentrations of 0, 3, 6, 9, 12, 15 and 18 grams·100 ml blood-1. 20 ml of well mixed whole blood is suspended in 5 ml of Drabkins. The erythrocytes are hemolyzed with the resulting formation of a cyanmethemoglobin compound that optimally absorbs light at a wave length of 540 nm. An exercise physiologist plans to use for Hb determination (prediction) in screening female distance runners for possible anemia ([Hb] < 12 g·100 ml-1) in females.

Part A) What statistical procedure is used to predict or determine the [Hb] in known blood samples based on the strong association between [Hb] and ABS540?

            a.         dependent t-test

            b.         multiple linear regression

            c.         simple linear regression

            d.         repeated measures ANOVA

            e.         Pearson product moment correlation coefficient

Part B) Select the correct statement.

            a.         The coefficient of determination is the proportion of error variance.

            b.         1-r2 is the common or shared variance.

c.         99.9% of the variance in [Hb] is explained by ABS540 nm in this the standard curve for this cyanmethemoglobin solution

Part C) Select the correct option below regarding hemoglobin concentration [Hb] and optical density at 540 nm (OD).

            a.         [Hb] = -8.732 + (0.030·ABS540)

            b.         [Hb] = 0.069 + (33.521·ABS540)

            c.         [Hb] = -0.002 + (8.734·ABS540)

            d.         [Hb] = 11.398 + (9.00·ABS540)

            e.         There is insufficient information to determine [Hb] from ABS540.

Y IHbl [CyanmetHbl X-Absorbance at 540 Hb? ABS540 CyanmetHb g 100 ml mg 100 ml nm (ABS540) ABS540 12.0 9.0 0.0081 6 239 0.175 36.0 00306 1.0500 9 35.9 0.265 81.0 0.0702 2.3850 12 47.8 0.350 144.00 0.1225 4.2000 59.8 0.445 225.0 0.1980 324.0 0.2916 9.7200 633 1.865 819.01 244.3000 0.7211 9.0 0.266 R 6.4830741 0.193 0.99983

Explanation / Answer

Answer:

Part A) What statistical procedure is used to predict or determine the [Hb] in known blood samples based on the strong association between [Hb] and ABS540?

            a.         dependent t-test

            b.         multiple linear regression

            Answer: c.         simple linear regression

            d.         repeated measures ANOVA

            e.         Pearson product moment correlation coefficient

Part B) Select the correct statement.

            a.         The coefficient of determination is the proportion of error variance.

            b.         1-r2 is the common or shared variance.

Answer: c.         99.9% of the variance in [Hb] is explained by ABS540 nm in this the standard curve for this cyanmethemoglobin solution

Part C) Select the correct option below regarding hemoglobin concentration [Hb] and optical density at 540 nm (OD).

            a.         [Hb] = -8.732 + (0.030·ABS540)

           Answer: b.         [Hb] = 0.069 + (33.521·ABS540)

            c.         [Hb] = -0.002 + (8.734·ABS540)

            d.         [Hb] = 11.398 + (9.00·ABS540)

            e.         There is insufficient information to determine [Hb] from ABS540.

Regression Analysis

1.000

n

7

r

1.000

k

1

Std. Error

0.132

Dep. Var.

Hb

ANOVA table

Source

SS

df

MS

F

p-value

Regression

251.9127

1  

251.9127

14425.34

7.59E-10

Residual

0.0873

5  

0.0175

Total

252.0000

6  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=5)

p-value

95% lower

95% upper

Intercept

0.0690

0.0896

0.770

.4762

-0.1613

0.2992

ABS540

33.5213

0.2791

120.106

7.59E-10

32.8039

34.2388

Regression Analysis

1.000

n

7

r

1.000

k

1

Std. Error

0.132

Dep. Var.

Hb

ANOVA table

Source

SS

df

MS

F

p-value

Regression

251.9127

1  

251.9127

14425.34

7.59E-10

Residual

0.0873

5  

0.0175

Total

252.0000

6  

Regression output

confidence interval

variables

coefficients

std. error

   t (df=5)

p-value

95% lower

95% upper

Intercept

0.0690

0.0896

0.770

.4762

-0.1613

0.2992

ABS540

33.5213

0.2791

120.106

7.59E-10

32.8039

34.2388

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