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Background and Objective: To evaluate the effectiveness of Neonatal Intensive Cares Many different data banks have been developed. Furthermore, various scoring systems such as SNAP and CRIB have been validated to designate and compared differences among hospitalized patients in NICU. This study was done to determine mortality rate and prevalence of complications in neonates admitted to Taleghani and Dezyani NICU centers in Gorgan - Iran. Materials and Methods: In this discriptive study a questioniare including sex, birthweight, gestational age, duration of hospitalization, age at the time of discharge or death, complications and other information needed for CRIB scoring system, was completed for 46 neonates with gestational age of less than 37-week old and birth weight of less than 1500 grams. Results: Mortality rate was 37% (17 neonates) with the most common cause being respiratory failure. RDS was associated with a 101-fold increase for the chance of death (OR=1.1, CI=12.9-793.6). This probability was 4.7 fold for delivery-time asphyxia. The mean of birthweight, gestational age and CRIB in living and dead infants were 1201 and 934 grams, 30 and 28 weeks and 3.76 and 11.7, respectivly. Using a ROC curve, a cut off point of 7 was reached to predict neonatal outcome for CRIB scoring. Conclusion: This study showed that the mortality rate was higher than the rate in most centers of the world. The mortality rate was directly related with the increase of CRIB score,especially for scores more than 11.

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Background and Objective: Obesity and advancing age in men, in addition to numerous health problems, can negatively affect spermatogenesis and fertility potential. The present study aimed to determine the correlation of sperm parameters with age and body mass index (BMI) in infertile men.
Methods: In this descriptive-analytical study, semen parameters (concentration, motility, and morphology) of 7069 men referring to an infertility center in Isfahan were evaluated based on the 2010 World Health Organization (WHO) guidelines. BMI was calculated by dividing an individual’s weight (kg) by the square of their height (m).
Results: A weak positive correlation was observed between men’s BMI and age (P<0.001, r=0.07). Also semen volume (P<0.001, r=-0.02), sperm concentration (P<0.001, r=-0.02), and sperm count (P<0.001, r=-0.04) had a weak negative correlation with BMI. No statistically significant correlation was observed between sperm motility and BMI. Regarding men’s age, only a weak negative correlation was observed between this parameter and sperm motility (P<0.001, r=-0.04).
Conclusion: Increasing BMI and age in men may be associated with decreased sperm quality and fertility potential.