scholarly journals “INTERGROWTH21st vs customized fetal growth curves in the assessment of the neonatal nutritional status: a retrospective cohort study of gestational diabetes”

2019 ◽  
Author(s):  
Juan Jesus Fernández Alba ◽  
Estefania Soto Pazos ◽  
Rocio Moreno Cortes ◽  
Angel Vilar Sanchez ◽  
Carmen Gonzalez Macias ◽  
...  
Keyword(s):  
Cohort Study ◽  
Gestational Diabetes ◽  
Nutritional Status ◽  
Positive Predictive Value ◽  
Pregnant Women ◽  
Fetal Growth ◽  
Retrospective Cohort Study ◽  
Predictive Value ◽  
Retrospective Cohort ◽  
Growth Curves

Abstract Background Gestational diabetes mellitus is associated with increased incidence of adverse perinatal outcomes including newborns large for gestational age, macrosomia, preeclampsia, polihydramnios, stillbirth, and neonatal morbidity. Thus, fetal growth should be monitored by ultrasound to limit fetal overnutrition, and thereby, its clinical consequence, macrosomia. However, it is not clear which reference curve to use to define the limits of normality. Our aim is to determine which method, INTERGROWTH21st or customized curves, better identifies the nutritional status of newborns of diabetic mothers.Methods This retrospective cohort study compared the risk of malnutrition in SGA newborns and the risk of overnutrition in LGA newborns using INTERGROWTH21st and customized birth weight references in gestational diabetes. Additionally, to determine the ability of both methods in the identification of neonatal malnutrition and overnutrition, we calculate sensitivity, specificity, positive predictive value, negative predictive value and likelihood ratios.Results 231 pregnant women with GDM were included in the study. The rate of SGA indentified by INTERGROWTH21st was 4.7% vs 10.7% identified by the customized curves. The rate of LGA identified by INTERGROWT21st was 25.6% vs 13.2% identified by the customized method. Newborns identified as SGA by the customized method showed a higher risk of malnutrition than those identified as SGA by INTERGROWTH21st.(RR 4.24 vs 2.5). LGA newborns according to the customized method also showed a higher risk of overnutrition than those classified as LGA according to INTERGROWTH21st. (RR 5.26 vs 3.57). In addition, the positive predictive value of the customized method was superior to that of INTERGROWTH21st in the identification of malnutrition (32% vs 27.27%), severe malnutrition (22.73% vs 20%), overnutrition (51.61% vs 32.20%) and severe overnutrition (28.57% vs 14.89%).Conclusions In pregnant women with GDM, the ability of customized fetal growth curves to identify the newborns with alterations in nutritional status exceeds that of INTERGROWTH21st.

scholarly journals INTERGROWTH21st vs customized fetal growth curves in the assessment of the neonatal nutritional status: a retrospective cohort study of gestational diabetes

2020 ◽  
Author(s):  
Juan Jesus Fernández Alba ◽  
Estefania Soto Pazos ◽  
Rocio Moreno Cortes ◽  
Angel Vilar Sanchez ◽  
Carmen Gonzalez Macias ◽  
...  
Keyword(s):  
Cohort Study ◽  
Gestational Diabetes ◽  
Nutritional Status ◽  
Positive Predictive Value ◽  
Pregnant Women ◽  
Fetal Growth ◽  
Retrospective Cohort Study ◽  
Predictive Value ◽  
Retrospective Cohort ◽  
Growth Curves

Abstract Background Gestational diabetes mellitus is associated with increased incidence of adverse perinatal outcomes including newborns large for gestational age, macrosomia, preeclampsia, polyhydramnios, stillbirth, and neonatal morbidity. Thus, fetal growth should be monitored by ultrasound to assess for fetal overnutrition, and thereby, its clinical consequence, macrosomia. However, it is not clear which reference curve to use to define the limits of normality. Our aim is to determine which method, INTERGROWTH21st or customized curves, better identifies the nutritional status of newborns of diabetic mothers. Methods This retrospective cohort study compared the risk of malnutrition in SGA newborns and the risk of overnutrition in LGA newborns using INTERGROWTH21st and customized birth weight references in gestational diabetes. The nutritional status of newborns was assessed using the ponderal index . Additionally, to determine the ability of both methods in the identification of neonatal malnutrition and overnutrition, we calculate sensitivity, specificity, positive predictive value, negative predictive value and likelihood ratios. Results 231 pregnant women with GDM were included in the study. The rate of SGA indentified by INTERGROWTH21st was 4.7% vs 10.7% identified by the customized curves. The rate of LGA identified by INTERGROWTH21st was 25.6% vs 13.2% identified by the customized method. Newborns identified as SGA by the customized method showed a higher risk of malnutrition than those identified as SGA by INTERGROWTH21st. (RR 4.24 vs 2.5). LGA newborns according to the customized method also showed a higher risk of overnutrition than those classified as LGA according to INTERGROWTH21st. (RR 5.26 vs 3.57). In addition, the positive predictive value of the customized method was superior to that of INTERGROWTH21st in the identification of malnutrition (32% vs 27.27%), severe malnutrition (22.73% vs 20%), overnutrition (51.61% vs 32.20%) and severe overnutrition (28.57% vs 14.89%). Conclusions In pregnant women with DMG, the ability of customized fetal growth curves to identify newborns with alterations in nutritional status appears to exceed that of INTERGROWTH21st

scholarly journals INTERGROWTH21st vs customized fetal growth curves in the assessment of the neonatal nutritional status: a retrospective cohort study of gestational diabetes

2020 ◽  
Author(s):  
Juan Jesus Fernández Alba ◽  
Estefania Soto Pazos ◽  
Rocio Moreno Cortes ◽  
Angel Vilar Sanchez ◽  
Carmen Gonzalez Macias ◽  
...  
Keyword(s):  
Cohort Study ◽  
Gestational Diabetes ◽  
Nutritional Status ◽  
Positive Predictive Value ◽  
Pregnant Women ◽  
Fetal Growth ◽  
Retrospective Cohort Study ◽  
Predictive Value ◽  
Retrospective Cohort ◽  
Growth Curves

Abstract Background Gestational diabetes mellitus is associated with increased incidence of adverse perinatal outcomes including newborns large for gestational age, macrosomia, preeclampsia, polyhydramnios, stillbirth, and neonatal morbidity. Thus, fetal growth should be monitored by ultrasound to assess for fetal overnutrition, and thereby, its clinical consequence, macrosomia. However, it is not clear which reference curve to use to define the limits of normality. Our aim is to determine which method, INTERGROWTH21st or customized curves, better identifies the nutritional status of newborns of diabetic mothers. Methods This retrospective cohort study compared the risk of malnutrition in SGA newborns and the risk of overnutrition in LGA newborns using INTERGROWTH21st and customized birth weight references in gestational diabetes. Additionally, to determine the ability of both methods in the identification of neonatal malnutrition and overnutrition, we calculate sensitivity, specificity, positive predictive value, negative predictive value and likelihood ratios. Results 231 pregnant women with GDM were included in the study. The rate of SGA indentified by INTERGROWTH21st was 4.7% vs 10.7% identified by the customized curves. The rate of LGA identified by INTERGROWTH21st was 25.6% vs 13.2% identified by the customized method. Newborns identified as SGA by the customized method showed a higher risk of malnutrition than those identified as SGA by INTERGROWTH21st. (RR 4.24 vs 2.5). LGA newborns according to the customized method also showed a higher risk of overnutrition than those classified as LGA according to INTERGROWTH21st. (RR 5.26 vs 3.57). In addition, the positive predictive value of the customized method was superior to that of INTERGROWTH21st in the identification of malnutrition (32% vs 27.27%), severe malnutrition (22.73% vs 20%), overnutrition (51.61% vs 32.20%) and severe overnutrition (28.57% vs 14.89%). Conclusions In pregnant women with DMG, the ability of personalized fetal growth curves to identify newborns with alterations in nutritional status could exceed that of INTERGROWTH21st.

scholarly journals “INTERGROWTH21st vs customized fetal growth curves in the assessment of the neonatal nutritional status: a retrospective cohort study of gestational diabetes”

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Juan Jesús Fernández-Alba ◽  
Estefanía Soto Pazos ◽  
Rocío Moreno Cortés ◽  
Ángel Vilar Sánchez ◽  
Carmen González Macías ◽  
...  
Keyword(s):  
Cohort Study ◽  
Gestational Diabetes ◽  
Nutritional Status ◽  
Fetal Growth ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Growth Curves

Association of Bacteria Species with Positive Predictive Value of Bacteria Isolated from Cerebrospinal Fluid Cultures: A Retrospective Cohort Study

2021 ◽  
Author(s):  
Yi Ye ◽  
Guanghui Zheng ◽  
Yueyue Kong ◽  
Jiawei Ma ◽  
Guojun Zhang ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Cohort Study ◽  
Positive Predictive Value ◽  
Retrospective Cohort Study ◽  
Predictive Value ◽  
Retrospective Cohort ◽  
Klebsiella Oxytoca ◽  
P Value ◽  
Coagulase Negative Staphylococci ◽  
Predictive Values

Abstract Background: Previous studies discuss the positive predictive value through whether the bacteria are coagulase-negative staphylococci. The view may need to be updated. The aim was to evaluate the positive predictive value of different bacteria species isolated from cerebrospinal fluid cultures and discuss the rationality to view coagulase-negative staphylococci as a group.Methods: This retrospective cohort study recruit all adults with positive cerebrospinal fluid cultures sampled by lumbar puncture 2012-2020 in the Department of Neurosurgery. The exposure was bacteria species, and the outcome was positive predictive value. An episode was defined as a patient with one bacteria. When episodes with a bacteria species reached five, the bacteria species was analyzed specifically. The positive predictive value was defined as the incidence of isolated-bacteria-related infected episodes. The isolated-bacteria-related infected episode was defined as the patient was with clinical features of bacterial meningitis, and the improvement was related to sensitive antibacterial agents. Then the differences of the positive predictive value of different bacteria in all specific bacteria species, coagulase-negative staphylococci, and non-coagulase-negative staphylococci bacteria were calculated, respectively. The results were statistically significant when P-value <.05.Results: 1180 episodes from 1133 patients with 79 bacteria were studied; the positive predictive value was 54.3%. The bacteria included 67 bacteria species, ten bacteria genus, viridans streptococci, and unclassified coagulase-negative staphylococci. Twenty-four specific bacteria species were analyzed. The range of positive predictive values of them was 29.4%-100.0% (P<.0001). The positive predictive value for Enterobacter aerogenes, Pseudomonas aeruginosa, Enterobacter cloacae, and Klebsiella oxytoca was the highest, while the positive predictive value for Staphylococcus cohnii was the lowest. Moreover, 767 (65.0%) were with coagulase-negative staphylococci, the positive predictive value was 46.4%, and the range was 29.4%-85.7% (P=.0020); 413 (35.0%) were with non-coagulase-negative staphylococci bacteria, the positive predictive value was 69.0%, and the range was 40.0%-100.0% (P<.0001).Conclusions: This study suggests that the positive predictive value of different bacteria species is different. It is more reasonable to discuss the positive predictive value of bacteria isolated from cerebrospinal fluid cultures through the bacteria species rather than whether they are coagulase-negative staphylococci.Trial registration: This is a retrospective study without interventions on participants.

scholarly journals Accuracy of Prenatal Ultrasound in Detecting Growth Abnormalities in Triplets: A Retrospective Cohort Study

2017 ◽  
Vol 20 (1) ◽  
pp. 84-89 ◽  
Author(s):  
Cameron Sklar ◽  
Maryna Yaskina ◽  
Sue Ross ◽  
Kentia Naud
Keyword(s):  
Cohort Study ◽  
Fetal Growth ◽  
Retrospective Cohort Study ◽  
Predictive Value ◽  
Retrospective Cohort ◽  
Prenatal Ultrasound ◽  
Growth Restriction ◽  
Fetal Weight ◽  
Growth Abnormalities ◽  
Estimated Fetal Weight

Significant management decisions in triplet pregnancies are made based mainly on ultrasound measurements of fetal growth, although there is a paucity of data examining the accuracy of fetal weight measurements in these gestations. To evaluate accuracy of prenatal ultrasound to diagnose growth abnormalities (intrauterine growth restriction, severe growth discordance) in triplet pregnancies, a retrospective cohort study of 78 triplet pregnancies (234 fetuses) delivered at a single tertiary hospital from January 2004 to May 2015 was performed. Growth percentiles from the last ultrasound were derived from estimated fetal weight using Hadlock's formula for each triplet. Growth discordance was calculated for each triplet set using the formula {(estimated fetal weight largest triplet - estimated fetal weight smallest)/estimated fetal weight largest}. These estimations were compared to birth weights. Sensitivity of ultrasound to predict ≥1 growth restricted fetus in a triplet set was 55.6% [95% CI 35.3, 74.5]; specificity was 100% [95% CI 93.0, 100]; positive predictive value (PPV) 100% [95% CI 74.7, 100]; negative predictive value (NPV) 81.0% [95% CI 73.2, 85.7%]. Sensitivity of ultrasound to detect fetal growth discordance >25% in a triplet set was 80.0% [95% CI 44.4, 97.5], specificity 94.1% [95% CI 85.6, 98.4]; PPV 66.7% [95% CI 42.4, 84.5]; NPV 97.0% [95% CI 90.2, 99.1]. Prenatal ultrasound currently remains the most reliable tool to screen for growth anomalies in triplet pregnancies; however, it appears to have less than ideal sensitivity, missing a number of cases of intra-uterine growth restriction and significant growth discordance.

Pre-operative prediction of cholesteatomas from radiology: retrospective cohort study of 106 cases

2019 ◽  
Vol 133 (06) ◽  
pp. 477-481 ◽  
Author(s):  
D Selwyn ◽  
J Howard ◽  
P Cuddihy
Keyword(s):  
Computed Tomography ◽  
Cohort Study ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Retrospective Cohort Study ◽  
Predictive Value ◽  
Retrospective Cohort ◽  
Anatomical Variation ◽  
Predictive Values ◽  
Mastoid Surgery

AbstractObjectivePre-operative imaging is often used to predict the extent of a cholesteatoma and anatomical variation to plan for surgery. This study aimed to measure the predictive accuracy of computed tomography findings.MethodsA retrospective cohort study was conducted of all patients in a district general hospital undergoing mastoid surgery within a consecutive 12-month period, in whom computed tomography had been performed prior to operative intervention. The study measured the key findings of pre-operative computed tomography imaging and compared them to the intra-operative findings.ResultsA total of 106 patients were included. The sensitivity and specificity for predicting cholesteatoma were 79 per cent and 81 per cent respectively. The positive predictive value was 90 per cent and the negative predictive value was 65 per cent. In predicting complications of cholesteatomas, the sensitivity was 70 per cent, whereas the specificity was 91 per cent. The positive predictive value was 88 per cent and the negative predictive value was 76 per cent.ConclusionPre-operative computed tomography conducted prior to mastoid surgery has high positive predictive values for both predicting cholesteatomas and complications (90 per cent and 88 per cent respectively).

scholarly journals Validation of billing code combinations to identify cardiovascular magnetic resonance imaging scans in Ontario, Canada: a retrospective cohort study

BMJ Open ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. e021370
Author(s):  
Idan Roifman ◽  
Feng Qiu ◽  
Kim A Connelly ◽  
Graham A Wright ◽  
Michael Farkouh ◽  
...  
Keyword(s):  
Cohort Study ◽  
Cardiovascular Magnetic Resonance ◽  
Magnetic Resonance ◽  
Positive Predictive Value ◽  
Retrospective Cohort Study ◽  
Predictive Value ◽  
Gold Standard ◽  
Retrospective Cohort ◽  
Health Sciences ◽  
Billing Code

ObjectivesCardiovascular magnetic resonance (CMR) imaging is the gold-standard test for the assessment of heart function. Despite its importance, many jurisdictions lack specific billing codes that can be used to identify patient receipt of CMR in administrative databases, limiting the ability to perform ‘big data’ CMR studies. Our objective was to identify the optimal billing code combination to identify patients who underwent CMR using administrative data in Ontario.DesignRetrospective cohort study.SettingQuaternary care academic referral centre in Ontario, Canada.ParticipantsWe tested all billing code combinations in order to identify the optimal one to determine receipt of CMR. The reference gold standard was a list of all cardiothoracic magnetic resonance scans performed at Sunnybrook Health Sciences Centre between 1 January 2014 and 31 December 2016, verified by chart audit. We assessed the diagnostic performance (accuracy, sensitivity, specificity, positive predictive value and negative predictive value) for all code combinations.ResultsOur gold-standard cohort consisted of 2339 thoracic MRIs that were performed at Sunnybrook Health Sciences Centre from 1 January 2014 to 31 December 2016. Of these, 2139 (91.5%) were CMRs and 200 (8.5%) were chest MRIs. We identified the most accurate billing combination for the determination of patient receipt of CMR. This combination resulted in an accuracy of 95.3% (95% CI 94.4% to 96.2%), sensitivity of 97.4% (95% CI 96.6% to 98.1%), specificity of 86.4% (95% CI 83.1% to 89.6%), positive predictive value of 96.9% (95% CI 96.1% to 97.6%) and negative predictive value of 88.4% (95% CI 85.4% to 91.5%).ConclusionsOur study is the first to verify the ability to accurately identify patient receipt of CMR using administrative data, facilitating more robust population-based CMR studies in the future.

scholarly journals Safe threshold of capillary blood glucose for predicting early future neonatal hypoglycaemia in babies born to mothers with gestational diabetes mellitus, an observational, retrospective cohort study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Esther H. G. Park ◽  
Frances O’Brien ◽  
Fiona Seabrook ◽  
Jane Elizabeth Hirst
Keyword(s):  
Diabetes Mellitus ◽  
Cohort Study ◽  
Blood Glucose ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Capillary Blood ◽  
Capillary Blood Glucose ◽  
Neonatal Hypoglycaemia

Abstract Background There is increasing pressure to get women and babies home rapidly after birth. Babies born to mothers with gestational diabetes mellitus (GDM) currently get 24-h inpatient monitoring. We investigated whether a low-risk group of babies born to mothers with GDM could be defined for shorter inpatient hypoglycaemia monitoring. Methods Observational, retrospective cohort study conducted in a tertiary maternity hospital in 2018. Singleton, term babies born to women with GDM and no other risk factors for hypoglycaemia, were included. Capillary blood glucose (BG) testing and clinical observations for signs of hypoglycaemia during the first 24-h after birth. BG was checked in all babies before the second feed. Subsequent testing occurred if the first result was < 2.0 mmol/L, or clinical suspicion developed for hypoglycaemia. Neonatal hypoglycaemia, defined as either capillary or venous glucose ≤ 2.0 mmol/L and/or clinical signs of neonatal hypoglycaemia requiring oral or intravenous dextrose (lethargy, abnormal feeding behaviour or seizures). Results Fifteen of 106 babies developed hypoglycaemia within the first 24-h. Maternal and neonatal characteristics were not predictive. All babies with hypoglycaemia had an initial capillary BG ≤ 2.6 mmol/L (Area under the ROC curve (AUC) 0.96, 95% Confidence Interval (CI) 0.91–1.0). This result was validated on a further 65 babies, of whom 10 developed hypoglycaemia, in the first 24-h of life. Conclusion Using the 2.6 mmol/L threshold, extended monitoring as an inpatient could have been avoided for 60% of babies in this study. Whilst prospective validation is needed, this approach could help tailor postnatal care plans for babies born to mothers with GDM.

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