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In the Name of God. Biostatistics in Obstetrics Mitra Ahmad Soltani 2008. Med-ed-online.org. References:. Ahmad Soltani M. Regression Analysis of Labor Duration. The Internet Journal of Gynecology and Obstetrics. Texas: Vol 5, No 2. 2006

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In the name of god l.jpg
In the Name of God

Biostatistics in Obstetrics

Mitra Ahmad Soltani

2008

Med-ed-online.org


References l.jpg
References:

  • Ahmad Soltani M. Regression Analysis of Labor Duration. The Internet Journal of Gynecology and Obstetrics. Texas: Vol 5, No 2. 2006

  • Clements JM. Synergy Medical Education Alliance Research Design Core Curriculum. Module2&3.2008

  • Kramer M et al. Prepregnancy Weight and the Risk of Adverse Pregnancy Outcomes. New England Journal of Medicine.1998 Vol:338, N3:147-152

  • Lyon D. Use of Vital Statistics in Obstetrics. emedicine. Dec 2007

  • Pritchard JA, MacDonald PC, Gant NF. Obstetrics in broad perspective. In: Williams Obstetrics. 22nd ed. New York, NY: McGraw-Hill; 2005


Birth rate l.jpg
Birth rate

number of births

1000 population

  • It includes men in the population.


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Fertility Rate

number of live births

1000 women aged 15-44 years

  • While a woman with 2 second-trimester miscarriages would be considered fertile, her deliveries would not be included in the fertility rate.


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Reproductive Mortality rate

contraceptive use plus direct maternal deaths

100000 women

  • This is  perhaps the most sensitive measure of a population's ability to provide safety for women.


Maternal mortality rate l.jpg
Maternal Mortality Rate

number of direct or indirect maternal deaths

100,000 live births

  • A condition in which both mother and fetus are lost would both increase the numerator (maternal death) and decrease the denominator (live birth).


Infant mortality rate l.jpg
Infant Mortality Rate

infants who die prior to their first birthday

1000 live Births

  • IMR is often one of the sentinel indicators used to evaluate a population's overall health and access to health care.


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Neonatal Mortality Rate

losses between 0-28 d of life (inclusive)

1000 live births

  • This rate is often divided into early (first 7 d) and late (8-28 d) rates, as etiologies within these 2 categories vary somewhat.


Fetal death rate stillbirth rate l.jpg
Fetal Death rate (stillbirth rate)

number of stillbirths

1000 infants (total Births)

  • Infants means “live and still” born.


Perinatal mortality rate l.jpg
Perinatal Mortality Rate

Fetal deaths+neonatal deaths

1000 total Births


Still birth l.jpg
Still birth

  • Delivery after 20 weeks' EGA (and more than 500 g birthweight) in which the infant displays no sign of life (gasping, muscular activity, cardiac activity) is considered a stillbirth.


Live birth l.jpg
Live Birth

  • Delivery after 20 weeks' EGA in which any activity is noted is classified as a live birth. This is a difficult definition, as the lower limit of reasonable viability currently remains around 23 weeks' EGA. Thus, a spontaneous delivery at 21 weeks' EGA with reflex motion but no ability to survive with or without intervention would nonetheless be considered a live birth.


Abortion l.jpg
Abortion

  • The most common definition of an abortion is any loss of a fetus that is less than 20 weeks' completed gestational age (since last menstrual period) or that weighs less than 500 grams.


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Preterm Infants

  • Preterm infant is another arbitrary definition because a subtle gradient of maturity exists. Most states define premature as a delivery before 37 completed weeks' gestational age, although the vast majority of babies born after 35 weeks‘ GA have uncomplicated perinatal courses.


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Postterm Infants

  • The generally accepted definition of a postterm pregnancy is one that progresses beyond 42 weeks' completed gestational age based on last menstrual period (LMP). In practice, many clinicians use a lower cutoff such as 41 weeks‘ GA when LMP is certain.


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Testing for statistical significance of the difference for nominal data

  • Small unmatched sample: Fisher’s exact test

  • Small matched sample: Sign test

  • Large unmatched sample: Chi-square, with Yates correction

  • Large matched sample:McNemar’s test


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Testing for statistical significance of the difference for ordinal data

  • One comparison(2 groups),unmatched sample: Mann-Whitney U

  • One comparison(2 groups)Matched sample:Wilcoxon matched pairs

  • More than 2 groups unmatched sample: Kruskal Wallis one-way ANOVA

  • More than 2 groups matched sample: Friedman 2-way ANOVA


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Testing for statistical significance of the difference for continuous data

  • One comparison(2 groups)unmatched sample: t-test

  • One comparison(2 groups)matched sample: matched t-test

  • More than two groups unmatched sample:F test for analysis of variance followed by pairwise comparisons

  • More than two groups matched sample: F test for analysis with blocking or analysis of covariance


Measure the size of difference l.jpg
Measure the size of difference continuous data

  • Nominal/ordinal data:

    differences in proportions or percentages in each category

  • Continuous data:

    Differences in mean values between the groups+ SD for each group


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Tests to Determine Association Between Groups Measure the degree of Association

  • Nominal data: odds Ratio/Relative Risk

  • Ordinal Data(nonlinear):Spearman’s rho/Kendall’s tau

  • Continuous Data: Pearson’s Correlation Coefficient ( r )


Tests to determine association between groups testing for statistical significance of association l.jpg
Tests to Determine Association Between Groups testing for statistical significance of association

  • Nominal Data: Statistical Significance of odd’s Ratio

  • Ordinal data(nonlinear): Statistical Significance of rho or tau

  • Continuous Data(linear):Statistical significance of Pearson’s r


Tests to determine association between groups extent association explains variation between groups l.jpg
Tests to Determine Association Between Groups- Extent Association Explains Variation Between Groups

  • Nominal data: Attributable Risk

  • Ordinal data(nonlinear):Spearman’s rho or Kendall’s tau

  • Continuous data(linear):Pearson’s coefficient of determination


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For describing one group Association Explains Variation Between Groups

  • Mean, SD for measurement of Parametric Distributions

  • Median, interquartile range for rank,score or measurement of non-parametric distributions

  • Proportion for Binominal (2 possible outcomes)


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Compare one group to a hypothetical value Association Explains Variation Between Groups

  • One sample t-test for measurement of Parametric Distributions

  • Wilcoxon test for rank,score or measurement of non-parametric distributions

  • Chi-square for Binominal (2 possible outcomes)


Compare two unpaired groups l.jpg
Compare two unpaired groups Association Explains Variation Between Groups

  • Unpaired t-test for measurement of Parametric Distributions

  • Mann-Whitney test for rank, score or measurement of non-parametric distributions

  • Fischer test(or chi-square for large samples) for Binominal (2 possible outcomes)


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Compare two paired groups Association Explains Variation Between Groups

  • Paired t-test for measurement of Parametric Distributions

  • Wilcoxon test for rank, score or measurement of non-parametric distributions

  • McNemar’s test for Binominal (2 possible outcomes)


Compare three or more unmatched groups l.jpg
Compare three or more unmatched groups Association Explains Variation Between Groups

  • One-way ANOVA for measurement of Parametric Distributions

  • Kruskal Wallis test for rank, score or measurement of non-parametric distributions

  • Chi-square for Binominal (2 possible outcomes)


Compare three or more matched groups l.jpg
Compare three or more matched groups Association Explains Variation Between Groups

  • Repeated measures ANOVA for measurement of Parametric Distributions

  • Friedman test for rank, score or measurement of non-parametric distributions

  • Cochrane Q for Binominal (2 possible outcomes)


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Quantify association between two variables Association Explains Variation Between Groups

  • Pearson Correlation for measurement of Parametric Distributions

  • Spearman Correlation for rank, score or measurement of non-parametric distributions

  • Contingency coefficients for Binominal (2 possible outcomes)


Predict value from another measured variable l.jpg
Predict value from another measured variable Association Explains Variation Between Groups

  • Simple linear regression or non-linear regression for measurement of Parametric Distributions

  • Non-parametric regression for rank, score or measurement of non-parametric distributions

  • Simple logistic regression for Binominal (2 possible outcomes)


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Predict value from several measured or binominal variables Association Explains Variation Between Groups

  • Multiple linear or nonlinear regression for measurement of Parametric Distributions

  • Multiple logistic regression for Binominal (2 possible outcomes)


Summary l.jpg
summary Association Explains Variation Between Groups


P parametric n nonparametric b binominal m matched u unmatched g group versus h hypothetical value l.jpg
P=parametric/N=nonparametric/B=binominal Association Explains Variation Between GroupsM=matched/ U=unmatched/G=group/~=versus/ H=Hypothetical value


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Statistics Related to Diagnostic Tests Association Explains Variation Between Groups

  • Sensitivity = True Positives/(True Positives + False Negatives)

  • Specificity = True Negatives/(False Positives + True Negatives)

  • Positive Predictive Value = True Positive/(True Positive + False Positive)

  • Negative Predictive Value = True Negative/(True Negative+False Negative)


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  • Likelihood Ratio Association Explains Variation Between Groups= compares the likelihood of a result in a patients with the disease to the likelihood of a result in patients without disease.

  • Positive LR = (a/a+c)/(b/b+d)

  • Negative LR = (c/a+c)/(d/b+d)


How much do lrs change disease likelihood l.jpg
How much do LRs change disease likelihood? Association Explains Variation Between Groups

  • – LRs>10 or <0.1 cause large changes in likelihood

  • – LRs 5-10 or 0.1-0.2 cause moderate changes

  • – LRs 2-5 or 0.2-0.5 cause small changes

  • – LRs between <2 and 0.5 cause little or no changes


Statistics to interpret importance precision of therapeutic results l.jpg
Statistics to Interpret Importance &Precision of Therapeutic Results

  • Control Event Rate (CER) = c/(c+d)

  • Experimental Event Rate (EER) = a/(a+b)

  • Relative Risk (RR) = EER/CER = (a/a+b)/(c/c+d)

  • Relative Risk Reduction (RRR) = CER-EER/CER

  • Absolute Risk Reduction (ARR) = CER-EER

  • Number Needed to Treat (NNT) = 1/ARR


Relative risk and odds ration l.jpg
Relative Risk and Odds ration Results

There is strong association of RR or OR>1

There is strong association if RR>3 or OR>4


Sample size l.jpg
Sample size Results

If dependent variable is nominal or ordinal:

  • n= p (1-p) /d²

    If dependent variable is continuous:

  • n=s²/d²


Regression analysis of labor duration a sample research l.jpg
Regression analysis of labor duration Results(A sample research)


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Introduction ResultsDetermining labor duration has been the focus of different researches . The main aim is to lower the rate of cesarean section and undue hospitalization. Friedman’s, Hendrick’s , and Philpott’s Partographs and Nesheim’s regression equation are the results of such efforts. The advantage of an equation over a partograph is its predictive value in determining obstructed labor in advance and on an individualized basis.



Slide48 l.jpg

Linear Regression Results

Estimates the coefficients of the linear equation, involving one or more independent variables, that best predict the value of the dependent variable.

The two-variable model

Y = A + B X



230 laboring women were interviewed and examined according to a checklist from april august 2004 l.jpg
230 Results Laboring women were interviewed and examined according to a checklist from April – August 2004 .


The inclusion criteria were l.jpg
The Resultsinclusion criteria were:

1-Singleton pregnancy 2- Vertex presentation 3- Gestational age 36-42 weeks 4- no medical or obstetric disease 5- Bishop score of 10-12 6- normal FHR 7- spontaneous initiation of labor 8- non elective cesarean section 9- no diagnosis of CPD


The independent variables were l.jpg

  • 1-mother’s height Results2- maternal age 3- prepregnancy weight 4- maternal BMI 5- drugs used except oxytocin 6- 9interventions ( amniotomy – c/s/vacuum/ enema or any other way of bowels preparation) 10- 12- Duration , intensity and frequency of labor pain (in the initial stages before oxcytocin administration)

The independent variables were:


The independent variables were53 l.jpg

  • 13-abnormal events like cord prolapse or fetal heart abnormality or occiput posterior delivery 14- occupation 15-31- lifestyle in terms of alcohol consumption, smoking, exercise, meals,

  • Consumption of grain , vegetables, fruit, dairy and type of dairy, meat ad meat products, fat and dressings , water, snacks , and score as the sum of items

The independent variables were:


Slide54 l.jpg

Framingham Health Assessment Questionnaire abnormality or occiput posterior delivery is presented (though in small font size) as a reference for a print. It can help provide an account of life style risk for health. Four items were changed based on Iranian pregnant women characteristics:Alcohol consumptionsmokingExercise and type of dairy products


Lifestyle items l.jpg

13.0 Consumption of alcohol abnormality or occiput posterior delivery

How often do you consume alcohol?

_____1) Never drink

_____2) 2 days or less per week

_____3) 3 days per week

_____4) 4 or more days per week

14.0 Number of alcoholic beverages

On the days you drink, on the average how many drinks do you have?

_____1) Never drink

_____2) 1 to 2 drinks

_____3) 3 to 4 drinks

_____4) 5 or more drinks

15.0 Caffeine

How often do you consume caffeine in your diet including coffee, tea, cola or chocolate?

_____1) Never

_____2) Occasionally but not every day

_____3) 1 to 3 servings daily

_____4) 3 to 5 servings daily

_____5) More than 5 servings daily

16.0 Smoking status

Indicate which of the following best represents your current status

NOTE: Check all that apply.

_____1) Have never smoked

_____2) Quit smoking less than 5 years ago

_____3) Quit smoking more than 5 years ago

_____4) Smoke pipe or cigar

_____5) Smoke less than 1 pack of cigarettes per day

_____6) Smoke more than 1 pack of cigarettes per day

LIFESTYLE ITEMS


Slide56 l.jpg

Exercise Program abnormality or occiput posterior delivery

18.0 Exercise Frequency

On the average, how many days per week do you exercise?

_____1) 3 or more days per week

_____2) Less than 3 days per week

_____3) No regular exercise program

19.0 Proper stretching

Do you perform stretching prior to exercise?

_____1) Always

_____2) Sometimes

_____3) Never

_____4) Currently not exercising

20.0 Warm-up and cool down

Do you warm-up and cool-down after exercising?

_____1) Always

_____2) Sometimes

_____3) Never

_____4) Currently not exercising

Section E

Nutrition Habits

21.0 Daily Meals

On the average how many meals do you consume per day?

_____1) 3 meals with "healthy" snacks

_____2) 3 meals

_____3) 2 meals or less

_____4) No regular eating pattern

22.0 Consumption of grain/bread products

On the average, indicate the type and amount of grain products you normally consume per day.

NOTE: A serving is 1 sl. bread, 1/3 cup beans / peas, 1/3 cup oatmeal, rice or other grain products.

_____1) Whole grains at least 6 to 11 servings per day

_____2) Whole grains 6 servings or fewer servings per day

_____3) Refined grains such as white bread/rolls/processed flour at least 6 to 11

servings per day

_____4) Refined grains such as white bread/rolls/processed flour 6 or less

servings per day

_____5) Rarely consume grain products


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23.0 Consumption of vegetables abnormality or occiput posterior delivery

On the average, how many servings of vegetables do you consume per day? Note: A serving is approximately 1 cup of raw or 1/2 cup of cooked.

_____1) At least 3 to 5 servings per day

_____2) Less than 3 servings per day

_____3) Rarely consume vegetables

24.0 Consumption of fruits

On the average, how many servings of fruit do you consume per day? Note: A serving is approximately 1 piece of fruit.

_____1) At least 2 to 4 servings per day

_____2) Less than 2 servings

_____3) Hardly ever consume fruit

25.0 Daily consumption of dairy products

On the average, how many servings of dairy products do you consume per day? Note: A serving is approximately 1 cup of milk or 1 oz. of cheese.

_____1) At least 2 servings per day

_____2) Less than 2 servings

_____3) Hardly ever consume dairy products

26.0 Type of Dairy products

Indicate the type of dairy products you consume.

_____1) Nonfat selections only

_____2) Both low fat and nonfat about the same

_____3) Low fat only

_____4) Usually high fat selections

_____5) Do not consume dairy products

27.0 Daily consumption of meats and meat products

Indicate the type of meat you normally consume.

_____1) Do not consume meat or meat products

_____2) Consume less than 6 oz. of poultry or fish per day

_____3) Consume more than 6 oz. of poultry or fish per day

_____4) Consume less than 6 oz. of red meat per day

_____5) Consume more than 6 oz. of red meat per day

28.0 Consumption of fats, dressings and spreads

Indicate the type and number of servings of fat, dressings and spreads you consume each day.

High fat examples: Butter, lard, and margarine

Low fat examples: Non-fat or Low-fat salad dressing-mayonnaise-cheese

_____1) Use low fat selections sparingly (less than 3 per day)

_____2) Use low fat selections frequently (3 or more per day)

_____3) Use both low fat and high fat about the same sparingly (3 or less)

_____4) Use high fat selections sparingly (less than 3 per day)

_____5) Use high fat selections (more than 3 per day)


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On the average, how many glasses of water do you consume per day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.

_____1) At least 8 glasses per day

_____2) About 4 to 8 glasses per day

_____3) Less than 4 glasses per day

_____4) Seldom consume water

30.0 Convenience and snack food consumption

On the average how many times per day do you eat convenience foods or forms of fast food?

_____1) Never

_____2) Less than 1 time per day

_____3) More than 1 time per day


The independent variables were59 l.jpg
The day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.independent variables were:

  • 32- Gravida **

  • 33- Para** 34-Last delivery**35-education,

  • 36- residency district

  • 37- maternal BG and Rh


The confounding variables were l.jpg
The day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.confounding variables were:

  • 38- newborn weight ( not known before delivery)

  • 39- newborn sex ( not known before delivery) 40- time of delivery:( 8 am – 8 pm is considered as day time) ( not known before delivery)

  • 41- parity( based on crosstabs testing)

  • 42-last delivery ( based on crosstabs testing)

  • 43- gravida ( based on crosstabs testing)


The dependent variables were l.jpg

44 day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.

-

labor

duration

active phase

45

-

labor

duration

4 cm- delivery

46

-

The dependent variables were:

rate


Slide62 l.jpg
Rate day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.

  • Rate of cervical dilation means cm dilation per hour. Compared to other dependent variable , RATE was more reliable for analysis.


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Assumptions day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.

1- First do no harm is the basic assumption of any medical intervention!

2- Obstructed labor should be defined by individual characteristics of women.


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Codes for nominal variables day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.They are arranged according to less high risk to more high risk states in terms of labor duration (based on review on related literature )

  • Disease:

  • no=1/yes=2

  • Hospital district :

  • Affluent districts=1

  • Non affluent districts=2

  • Time of delivery:

  • night=1/day=2

  • Sex of the newborn:

  • girl=1/boy=2


Slide65 l.jpg

Codes for nominal variables day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.They are arranged according to less high risk to more high risk states in terms of labor duration (based on review on related literature )

  • Interventions:

  • done=1/not done=2

  • Pain intensity:

  • good=1/not good=2

  • Blood group:

  • A=1/Non A=2

  • RH:

  • pos=1/neg=2


Slide66 l.jpg

Codes for nominal variables day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.They are arranged according to low risk to high risk states in terms of labor duration (based on review on related literature )

  • Occupation:

  • Non sedentary=1/Sedentary=2

  • Education:

  • educated=1/ illiterate=2


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Results day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.


Gravida and rate l.jpg
Gravida and rate day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.


Young child and rate l.jpg
Young Child and rate day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.


Para and rate l.jpg
Para and rate day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.


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  • To reduce the effect of Confounding Variables day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.

    (number of pregnancies (G), number of previous deliveries (P), and the years passed since last delivery( YC)), the stepwise regression computation was done for all independent variables and dependent variable (rate) only for those cases with previous deliveries not equal to zero (p#0).


Correlation coefficients of rate and rate predictors l.jpg

correlation coefficients of rate and rate predictors day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.


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Independent : BMI day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.

Dependent : rate

MTH:LIN

Rsquare =043

Df=146

F=6.60

Sig f =0.011

B0 =.5744

B1 = .0965


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Which means: day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.

Rate=0.57 +0.09 BMI

or


Conclusion l.jpg
Conclusion day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.

  • In this study, women of lower BMI had a longer labor course.

  • According to Kramer, in a developedcountry lean women are likely to have adequate nutritionalstores to meet the basic requirements of pregnancy. So a low BMI is accompanied by a lower pregnancy risk than a higher BMI. This must not be generalized to developing countries, particularlythose in which maternal undernutrition is highly prevalent.


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THE END day? Note: A serving is one 8-oz. glass of water only; do not include coffee, soda or other beverages.


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