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Flow diagram to show the overall admission of <t>preterm</t> birth Felege Hiwot comprehensive specialized hospital, Northwest Ethiopia, 2016-2020.
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Flow diagram to show the overall admission of <t>preterm</t> birth Felege Hiwot comprehensive specialized hospital, Northwest Ethiopia, 2016-2020.
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Flow diagram to show the overall admission of <t>preterm</t> birth Felege Hiwot comprehensive specialized hospital, Northwest Ethiopia, 2016-2020.
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Image Search Results


Flow diagram to show the overall admission of preterm birth Felege Hiwot comprehensive specialized hospital, Northwest Ethiopia, 2016-2020.

Journal: Frontiers in Pediatrics

Article Title: Predictors of Survival Among Preterm Neonates Admitted to Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia

doi: 10.3389/fped.2022.800300

Figure Lengend Snippet: Flow diagram to show the overall admission of preterm birth Felege Hiwot comprehensive specialized hospital, Northwest Ethiopia, 2016-2020.

Article Snippet: A total sample size of 542 preterm neonates was obtained using STATA version 14 statistical software based on the cox-proportional hazard regression, taking a Crude Hazard Ratio (CHR) of different predictors such as home delivery (CHR = 2.14), hyaline membrane disease (CHR = 4.38), KMC (CHR = 0.41), crying immediately after birth (CHR = 0.25) and hypoglycemia (CHR = 2.1) as effect size , 5% marginal error, a standard error of 0.5, study power of 80% and a reasonable estimate for the proportion of preterm mortality from the prior study was 28.8% ( ).

Techniques:

Socio-demographic and clinical characteristics of  preterm neonates  at FHCSH, 2016-2020, ( n = 542).

Journal: Frontiers in Pediatrics

Article Title: Predictors of Survival Among Preterm Neonates Admitted to Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia

doi: 10.3389/fped.2022.800300

Figure Lengend Snippet: Socio-demographic and clinical characteristics of preterm neonates at FHCSH, 2016-2020, ( n = 542).

Article Snippet: A total sample size of 542 preterm neonates was obtained using STATA version 14 statistical software based on the cox-proportional hazard regression, taking a Crude Hazard Ratio (CHR) of different predictors such as home delivery (CHR = 2.14), hyaline membrane disease (CHR = 4.38), KMC (CHR = 0.41), crying immediately after birth (CHR = 0.25) and hypoglycemia (CHR = 2.1) as effect size , 5% marginal error, a standard error of 0.5, study power of 80% and a reasonable estimate for the proportion of preterm mortality from the prior study was 28.8% ( ).

Techniques:

Kaplan-Meier curve to estimate failure of preterm neonates admitted to NICU at FHCSH from 2016 to 2020 ( n = 542).

Journal: Frontiers in Pediatrics

Article Title: Predictors of Survival Among Preterm Neonates Admitted to Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia

doi: 10.3389/fped.2022.800300

Figure Lengend Snippet: Kaplan-Meier curve to estimate failure of preterm neonates admitted to NICU at FHCSH from 2016 to 2020 ( n = 542).

Article Snippet: A total sample size of 542 preterm neonates was obtained using STATA version 14 statistical software based on the cox-proportional hazard regression, taking a Crude Hazard Ratio (CHR) of different predictors such as home delivery (CHR = 2.14), hyaline membrane disease (CHR = 4.38), KMC (CHR = 0.41), crying immediately after birth (CHR = 0.25) and hypoglycemia (CHR = 2.1) as effect size , 5% marginal error, a standard error of 0.5, study power of 80% and a reasonable estimate for the proportion of preterm mortality from the prior study was 28.8% ( ).

Techniques:

(A) The Kaplan-Meier survival curves by time of initiation of breast feeding among preterm neonates admitted to NICU at FHCSH, 2016-2020 ( n = 542). (B) The Kaplan-Meier survival curves by KMC service among preterm neonates admitted to NICU at FHCSH, 2016-2020 ( n = 542). (C) The Kaplan-Meier survival curves by PNA among preterm neonates admitted to NICU at FHCSH, during 2016-2020 ( n = 542). (D) The Kaplan-Meier survival curves by admission weight among preterm neonates admitted to NICU at FHCSH, 2016-2020 ( n = 542).

Journal: Frontiers in Pediatrics

Article Title: Predictors of Survival Among Preterm Neonates Admitted to Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia

doi: 10.3389/fped.2022.800300

Figure Lengend Snippet: (A) The Kaplan-Meier survival curves by time of initiation of breast feeding among preterm neonates admitted to NICU at FHCSH, 2016-2020 ( n = 542). (B) The Kaplan-Meier survival curves by KMC service among preterm neonates admitted to NICU at FHCSH, 2016-2020 ( n = 542). (C) The Kaplan-Meier survival curves by PNA among preterm neonates admitted to NICU at FHCSH, during 2016-2020 ( n = 542). (D) The Kaplan-Meier survival curves by admission weight among preterm neonates admitted to NICU at FHCSH, 2016-2020 ( n = 542).

Article Snippet: A total sample size of 542 preterm neonates was obtained using STATA version 14 statistical software based on the cox-proportional hazard regression, taking a Crude Hazard Ratio (CHR) of different predictors such as home delivery (CHR = 2.14), hyaline membrane disease (CHR = 4.38), KMC (CHR = 0.41), crying immediately after birth (CHR = 0.25) and hypoglycemia (CHR = 2.1) as effect size , 5% marginal error, a standard error of 0.5, study power of 80% and a reasonable estimate for the proportion of preterm mortality from the prior study was 28.8% ( ).

Techniques:

Model fitness by using Cox-Snell residual test among preterm neonates admitted to NICU at FHCSH, during 2016-2020 ( n = 542).

Journal: Frontiers in Pediatrics

Article Title: Predictors of Survival Among Preterm Neonates Admitted to Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia

doi: 10.3389/fped.2022.800300

Figure Lengend Snippet: Model fitness by using Cox-Snell residual test among preterm neonates admitted to NICU at FHCSH, during 2016-2020 ( n = 542).

Article Snippet: A total sample size of 542 preterm neonates was obtained using STATA version 14 statistical software based on the cox-proportional hazard regression, taking a Crude Hazard Ratio (CHR) of different predictors such as home delivery (CHR = 2.14), hyaline membrane disease (CHR = 4.38), KMC (CHR = 0.41), crying immediately after birth (CHR = 0.25) and hypoglycemia (CHR = 2.1) as effect size , 5% marginal error, a standard error of 0.5, study power of 80% and a reasonable estimate for the proportion of preterm mortality from the prior study was 28.8% ( ).

Techniques:

Adjusting for sex, bi-variable and multivariable Cox regression analysis of predictors of incidence of mortality among  preterm neonates  admitted to NICU at FHCSH from 2016 to 2020 ( n = 542).

Journal: Frontiers in Pediatrics

Article Title: Predictors of Survival Among Preterm Neonates Admitted to Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia

doi: 10.3389/fped.2022.800300

Figure Lengend Snippet: Adjusting for sex, bi-variable and multivariable Cox regression analysis of predictors of incidence of mortality among preterm neonates admitted to NICU at FHCSH from 2016 to 2020 ( n = 542).

Article Snippet: A total sample size of 542 preterm neonates was obtained using STATA version 14 statistical software based on the cox-proportional hazard regression, taking a Crude Hazard Ratio (CHR) of different predictors such as home delivery (CHR = 2.14), hyaline membrane disease (CHR = 4.38), KMC (CHR = 0.41), crying immediately after birth (CHR = 0.25) and hypoglycemia (CHR = 2.1) as effect size , 5% marginal error, a standard error of 0.5, study power of 80% and a reasonable estimate for the proportion of preterm mortality from the prior study was 28.8% ( ).

Techniques: