PNN Calculations, PNN Calculations, pnn biostatistics

Food Calories- PO intake (calories per gram)

Carbs: 4 cal/gram

Protein: 4 cal/gram

Alcohol: 7 cal/gram

Fat: 9 cal/gram

TPN Calories- IV TPN intake (Calories per gram)

Dextrose: 3.4 cal/gram

Protein (amino acids): 4 cal/gram

Fat emulsion about 10 cal/gram

- 1mL of 10% = 1.1 cal

- 1 mL of 20% = 2.0 cal

- 1mL of 30% = 3.0 cal

Minimum (Base) daily requirements (calories, fluids and protein)

DAILY CAL: 25-30 cal/kg of IBW

DAILY FLUID: 30mL/kg of ABW

Daily PROTEIN: 1-1.5g/kg of IBW

Ideal Body Weight (IBW)

Men: 50kg + (2.3 x height over 5")

Women: 45.5kg + (2.3 x height over 5")

Basal Energy Expenditure (BEE)

Harris-benedict formula OR

25-30 cal/kg of IBW per day

Total Energy Expenditure (TEE)

BEE x Stress Factor x activity factor

Body Mass Index (BMI)

Weight (kg) /Height (m)2

What are the BMI ranges (normal, overweight, obese)

Normal: 18.5-24.9 kg/m2

Overweight: 25-29 kg/m2

Obese: >30kg/m2

- Class I: 30-34.9 kg/m2

- Class II: 35- 39.9 kg/m2

- Class III: >40 kg/m2

Body Surface Area (BSA)

What is the equivalency of 1 mmole?

MW in mg

What is the equivalency of 1 mEq?

MW in mg / Valence

What is the equivalency of 1 mOsm?

MW in mg / #ions

What is the relationship between 1 mmole, mEq (valence), and mOsm (ions)?

1 mmole = MW in mg = mEq (valence) = mOsm (ions)

What is the mmole, mEq and mOsm equivalency of NS

1 L of NS = 9000mg/58.5mg (MW)= 153.8 mmole = 153.8 mEq

Percent strength forms

w/w =g/100g

w/v= g/100mL

v/v= mL/100mL

% strength to strength ratio conversion

x grams/ 100mL = 1 part/ x parts

1 fluid ounce

29.6 mL (30 mL)

1 gallon

3800mL = 128 fl oz

1 quart (qt) = ___ milliliters (mL) = _______ fl oz

946 milliliters (mL) = 32 fl oz

1 pint (pt)=___ml = _____ fl oz

473 mL= 16 fl oz

1 teaspoon (tsp) = _____ milliliters (mL)

5 milliliters (mL)

1 tablespoon (tbsp) = ____ ml

15 milliliters (mL) = 1/2 fl oz

1 Deciliter (dl) = ______ mL

100 mL

1 mg = ___ mcg

1000 mcg

1 kg = ___ lbs

2.2 lbs

1 grain (gr) = ___ milligrams (mg)

65 milligrams

1 meter = ____ centimeters

100 centimeters (cm)

1 centimeter = ___ millimeters

10 millimeters (mm)

1 grain (gr) = ____ grams (g)

28.35 grams (g)

1 inch = ____ centimeters

2.54 centimeters (cm)

1 fl oz

29.6 mL

1 gallon = ____ quarts

4 quarts

1 quart = ____ pints

2 pints

1 pint

473 mL

1 pint

16 fl oz

1 oz

28.35 g

1 grain

65 mg

1 meter

100 cm

1 deciliter = ___ milliliters

100

1:1000

1 mg/mL

MW of KCl

74.5 mg

MW of Cl

35.5

MW of mag

24 mg

BSA equation

SQUARE ROOT OF (height in cm x weight in kg)/3600

BMI

Wt (kg)/m^2

BMI (inches)

(Lb/in^2) * 703

Normal Distribution Curve

Discrete data

-Numerical data values that can be COUNTED

-whole numbers, no decimals

Continuous Data

More or a continuum in which use of decimals allows for an infinite number of possible values

measure values

ex: lab values, height, weight, or drug concentration

Nominal (categorical) data

type of discrete data

Assigning data to different categories based on the occurrence of an outcome

ex: people who had MI and people who did not (yes or no: two groups - dichotomous) or based on certain characteristics (Race, gender)

Ordinal (ranked) data

type of discrete data

data that come in a certain order or ranking but the intervals between the values are not necessarily equal

ex: pain scale, or NYHA HF classification 1-4

Continuous (parametric) data subtype

Interval data

Ratio data

Interval data

-type of continuous data

measurable data with equal intervals between values, that has no absolute zero

ex: temperature is measurable and difference between 33&34 is equal to difference between 35&36

cant have "zero temperature"

Ratio data

-type of continuous data

measurable data with equal intervals between values, that has an absolute zero

ex: height, weight, hemoglobin

zero weight does mean "no weight"

Statistical Tests

1. type of data (continous, nominal or ordinal)

2. number of groups tested

3. whether the groups are independent or paired

T-test

-continuous data

-means of 2 groups are being compared

Student's T-test

-continuous data

-means of 2 groups are being compared

-when the two groups are independent and separate

Paired t-test

-continuous data

-test group acts as its own control ("paired")

-same set of patients before and after the treatment

Analysis of Variance (ANOVA) test

-continuous data

-3 or more groups are being compared

-Can be used for both independent and paired groups

Chi-squared test

-nominal (categorical) data

- 2 or more independent groups are being compared

-ex: YES MI or NO MI

McNemar's test

-nominal (categorical) data

-2 paired groups

-same set of patients

Cochran's Q test

-nominal (categorical) data

-3 or more paired groups

Wilcoxon Rank Sum test

-ordinal data

-2 or more independent groups are compared

-similar to t-test

-ex: pain scale

Wilcoxon Signed Rank Test

-ordinal data

-2 paired groups

-same set of patients

Kruskal-Wallis test

-ordinal data

-3 or more independent groups

Friedman test

-ordinal data

-3 or more paired groups

Table of tests

Randomized Control Trial (RTC)

-Clinical study comparing an experimental group to a control group where the two groups were chosen randomly without bias and respect to characteristics so the groups are similar

-gold standard for clinical trials

Cohort studies

-Begin with a group (cohort) of people who share a common trait, then with regards to a risk factor or a therapeutic measure

-exposed and non-exposed are observed over time

-Prospective

-Clinical treatment trials of new medications are cohort studies

Case-control Studies

-Individuals with a particular outcome (case) compared to individuals who never had the outcome

-control: individuals who are not exposed to the particular risk or treatment

-retrospective

Cross-Sectional studies

-Risk factors and health status of a group is studied at one specific point in time

-help determine the prevalence of a disease at a specific point in time

Cross-Over studies

-Study participants serve as their own control.

-Subjects who were initially exposed to placebo for a certain amount of time will "cross-over" to the experimental group & vice versa.

Intent to Treat Analysis vs. Per Protocol Analysis

-Intent to treat: includes data from ALL PATIENTS (closer to real life)

-Per protocol: data from PATIENTS WHO COMPLETED the entire study (better to determine effectiveness)

Meta Analysis/Systematic Review

-Gathering data from a number of previous studies.

-end results of a systematic review are reported as odds ratio of each individual study with 95% CI and final composite odds ratio of all the studies reviewed

Null Hypothesis (H0)

No difference or association

Alternative Hypothesis (Ha)

The hypothesis that argues for the presence or a correlation between events or a difference between groups being tested

Type I error

-False rejection of the null hypothesis

-Probability of a type I error: α

-most set a=0.05, p-value <0.05 (statistical significance)

Type II error

-False acceptance of the null hypothesis

-Probability of a type II error: β

-most set B=0.20, power= 1-B, =0.8

p-value

-The probability of incorrectly finding an association or difference when it does not exist (type I error)

-p-value of <0.05 means a type I error will be made less than 5 times out of 100 times

-p-value <0.05 is generally considered to be statistically significant

-in a large sample size, use p-value

Statistical Significance vs Clinical significance

statistical significance - result has low probability of having occurred by chance alone (p = .05)

differs from clinical significance in that emphasizes kind of change and amount of change, concerned with patients quality of life and overall satisfaction

power

-power=1-B

-likelihood of not making a type II error

-Beta is set at 0.20 which makes power 0.8 (80%)

Power Increases when

1. Sample size increases

2. Strong association between 2

Confidence Interval (CI)

-Interval or Range that will include the true mean of your population 95 out of 100 times

-another way to determine statistical significance

Relative Risk (RR) with 95% Confidence Interval (CI)

RR < 1.0 - treatment reduces the event rate compared to control

RR > 1.0 - treatment increases the event rate compared to control

RR = 1.0 - no difference in the two groups (treatment has no effect on risk)

RR (95% CI)

-Statistically significant if it does not cross 1.0

RRR (95% CI)

Statistically significant if it does not cross zero

OR (95% CI)

Statistically significant if it does not cross 1.0

Incidence vs Prevalence

-Incidence is the rate of new individuals that develop an illness in a given time period (usually one year) divided by the number of individuals at risk during that time

-Prevalence: number of indviduals who have an illness dived by total population

Case report vs case series

case report: one case

case series: a few

Bias

If the person administering the test influences the results

single-blind

Subject does not know which group (control or experimental) they are in

double-blind

Neither experimenter nor subject knows if the subject is receiving placebo or experimental drug

Reliability

reproducibilty of the test when repeated

Validity

-whether a test is assessing what it is supposed to be assessing

-sensitivity and specificity

Sensitivity

-Measures how well a test identifies truly ill people

-Highly sensitive- negative result is used to rule out disease

Specificity

-Measures how well a test identifies or rules out truly well people (without the disease)

-Highly specific- a positive result is used to confirm the disease

Phase I clinical trial

-Determine toxicity profile of the drug in humans

Phase II trials

-Limited number of patients with the target disease

Phase III Trials

-Larger number of target patients are given the new drug

Phase IV

post marketing surveillance