Volume 200, Issue 5 , Pages e45-e51, May 2009
Neonatal hypoglycemia in term, nondiabetic pregnancies
Article Outline
Objective
To define the incidence of hypoglycemia and identify risk factors in neonates from term, singleton, nondiabetic pregnancies.
Study Design
We conducted a matched case-control study of term, singleton infants weighing more than 2500 g in nondiabetic pregnancies. Cases with hypoglycemia (glucose < 50 mg/dL) were identified by International Classification of Diseases, ninth revision, codes. Two controls per case were matched on race, maternal age, and birthweight. Conditional logistic regression analyses were performed.
Results
There were 116 cases and 232 controls studied. The incidence density of neonatal hypoglycemia was 24.7 per 1000 infant-days at risk. Hypoglycemia was less commonly associated with later gestational age (odds ratio [OR], 0.66; 95% confidence interval [CI], 0.53-0.85 per week of gestation). Maternal fever during labor was more common with hypoglycemia (OR, 4.08; 95% CI, 1.39-11.79). Public insurance was more than twice as common with hypoglycemia compared with those privately insured (OR, 2.31; 95% CI, 1.17-4.58).
Conclusion
Neonatal hypoglycemia was associated with earlier gestational age, intrapartum fever, and public insurance.
Key words: neonatal hypoglycemia, pregnancy, risk factors
Neonatal hypoglycemia is a common problem affecting 3% to 29% of pregnancies.1 It may lead to significant neurologic consequences, such as permanent brain damage or death, if not treated promptly.2 In addition, a significant amount of resources is allocated to care for the affected neonates. Although hypoglycemia may be asymptomatic, many infants will exhibit symptoms, such as jitteriness, hypotonia, lethargy, irritability, apnea, tachypnea, poor feeding, hypothermia, and seizures.3 Certain situations place infants at increased risk for hypoglycemia, including prematurity, macrosomia, intrauterine growth restriction, maternal diabetes mellitus, and sepsis.3 Additional risk factors include delivery by cesarean section and increased maternal weight gain during pregnancy.4, 5
Few studies have examined the incidence of hypoglycemia in term infants born to nondiabetic patients. The purpose of this study is to define the incidence of hypoglycemia and to identify antepartum, intrapartum, and neonatal factors that are associated with neonatal hypoglycemia in term, singleton, nondiabetic pregnancies.
Materials and Methods
This was a case-based, matched case-control study. The population from which eligible participants were identified consisted of all infants born at Lehigh Valley Hospital between July 1, 2005 and June 30, 2007 (n = 6416). Gestational age was determined by last menstrual period (LMP), dates confirmed by ultrasound, or earliest ultrasound if the LMP was unknown or unreliable. At our institution standard practice is to screen all pregnant women for gestational diabetes with a 1-hour 50-g glucose challenge test from 24-28 weeks. Those with values > 135 mg/dL are given a 100-g glucose tolerance test. Gestational diabetes was diagnosed with at least 2 abnormal values by using the Carpenter-Coustan criteria (fasting blood sugar ≥ 95 mg/dL, 1-hour ≥180 mg/dL, 2-hour ≥ 155 mg/dL, and 3-hour ≥ 140 mg/dL).6 The Figure describes the selection process. Infants born during this period were eligible for inclusion if they were singleton infants without known anomalies, born to a nondiabetic mother at 37 weeks of gestation or later, and weighed more than 2500 g at birth (n = 4892). A case was defined as an infant whose record contained the International Classification of Disease, ninth revision, (ICD-9) code 775.6 indicating hypoglycemia within the first 24 hours of life. Our institutional protocol defines infant hypoglycemia as < 50 mg/dL by heelstick. To be eligible for selection as a control, infants could not meet the case definition or have a recorded blood sugar of < 50 mg/dL within the first 24 hours of life. For each case, 2 controls were randomly selected from eligible noncases (euglycemic infants) matched on race, maternal age (± 5 years), and birthweight (± 500 g). A 2:1 control-to-case ratio was chosen to decrease the chance of a type 2 error. There were 116 infants in the study period who met the case definition with 232 matched controls, for a total sample size of 348. The study was reviewed and approved by the hospital's institutional review board.
FIGURE.
Study sample selection process
aDiabetic mother, < 37 weeks estimated gestational age, birthweight ≤ 2500 g, multiple gestations, fetal anomalies; bNondiabetic mother, ≥ 37 weeks estimated gestational age, birthweight > 2500 g, singleton gestation, no known fetal anomalies.
DePuy. Neonatal hypoglycemia in term, nondiabetic pregnancies. Am J Obstet Gynecol 2009.
All medical records for study infants and their mothers were reviewed by 1 study physician (A.M.D.). The outcome of interest was the presence or absence of neonatal hypoglycemia occurring within the first 24 hours. Factors explored for possible relationships with the outcome were collected in 3 different stages: antepartum, intrapartum, and postpartum periods.
Variables of interest in the antepartum stage included maternal gravidity, parity, prepregnancy body mass index (BMI), antepartum weight gain and BMI at delivery, level of education, medical history, substance use history, and type of insurance.
Intrapartum factors examined included cervical examination at the time of admission, medications administered during or just before labor, intravenous (IV) fluids used during labor, length of labor, time from last meal before admission to labor and delivery, mode of delivery (cesarean section with or without labor, spontaneous vaginal delivery, or operative vaginal delivery), indications for cesarean or operative vaginal delivery, and presence or absence of maternal fever during labor (≥ 100.4°F). Patients with intrapartum fever were initially treated with IV fluid boluses (nonglucose solutions) and acetaminophen. If clinical chorioamnionitis was suspected by the clinician, antibiotic therapy was initiated.
Neonatal data examined included gestational age at birth, sex, Apgar scores, umbilical artery pH when obtained, and blood sugars at 1 hour, as well as 2 hours and 4 hours if available after birth. Our institution's protocol for evaluating an infant for hypoglycemia includes monitoring blood glucose at 1 hour of age in all infants. Fetal size, maternal diabetes, neonatal symptoms, and blood sugar values < 50 mg/dL dictate whether further blood glucose tests are performed.
Variables thought to confound relationships between the covariates and the outcome were maternal age, race, and birthweight, which we attempted to control with the matching structure. Each of the matched variables was regressed on the outcome, both independently and in combination, to be certain that there were no induced biases as a result of the matching.
Statistical methods
Prevalence and incidence of early neonatal hypoglycemia were calculated by using the population of infants eligible for inclusion in the study as the study base. The incidence density method was used to calculate incidence. Time at risk was calculated by using time to diagnosis for each case and was equal for each control. Conditional logistic regression analyses were performed to accommodate the matched case-control design, using STATA 9.0 (Stata Corp LP, College Station, TX). Model selection was performed by using methods proposed by Hosmer and Lemeshow.7 Three separate models, based on the stages of pregnancy and delivery, were initially examined to account for relationships between possible explanatory variables and neonatal hypoglycemia. Univariable conditional logistic regression analyses were carried out for each possible explanatory variable, and those with a significance of P ≤ .20 were retained for inclusion in the saturated models. Saturated models were pared down by deleting the least significant variable (cutoff P < .05) 1 at a time, using a likelihood ratio test (P < .05) to examine whether removing the variable had an effect on the model. After all final models were selected for each of the antepartum, intrapartum, and neonatal periods, the significant explanatory variables from these models were combined into the final model. In addition, the data were examined for the potential of using the infants' blood sugar readings as a repeated-measures outcome, but the data recorded in the patients' charts were not complete enough to allow for reliable analyses.
Results
Over a 2-year period, there were 4892 term infants weighing > 2500 g born to nondiabetic mothers. One hundred sixteen infants had neonatal hypoglycemia within the first 24 hours of life identified by ICD-9 775.6. Of these, 69% were subsequently evaluated in a neonatal special care setting other than the standard newborn nursery. The mean (standard deviation [SD]) of the lowest glucoses in the first 24 hours (mg/dL) for cases was 38.0 mg/dL (11.2 mg/dL) and 63.6 mg/dL (11.8 mg/dL) for controls. The prevalence of neonatal hypoglycemia was 23.7 cases per 1000 infants, or 2.4%. The study measured cases more than 114,821 total infant-hours at risk, for an incidence density of 24.2 cases per 1000 infant-days at risk.
For each case, 2 controls were selected to bring the study sample size to 348 infants. Descriptive statistics for the sample are summarized in TABLE 1, TABLE 2. The majority of mothers in the sample were white (84%). The mean (SD) birthweight was 3516 g (569.9 g), and the overall gestational age between groups was not significantly different. Most of the infants had a 5-minute Apgar score of 8 or greater (98%). The majority of infants in the hypoglycemic group had at least 3 blood sugar measurements (n = 109). Six of the cases had 2 blood glucose values recorded and 1 case had 1 blood glucose value. Most of the control infants had only 1 blood glucose measurement (n = 125), although 98 controls had 2 blood glucose values and 9 had 3 blood glucose measurements. All cases and controls had at least 1 blood glucose measurement in the first 24 hours of life. The lowest blood glucose value for each infant was used for purposes of analysis. The mean maternal age was 28 years, and most mothers (89%) were at least high school graduates. Roughly half of the mothers in the sample had a normal prepregnancy BMI (18.5-24.9 kg/m2), and about 25% were overweight (25-29.9 kg/m2). Approximately 17% were obese (30-39.9 kg/m2), and there were about 5% in each of the extreme obesity (≥ 40 kg/m2) or underweight (< 18.5 kg/m2) categories.8 The average weight gain across the group was 35 lb. On average, only the mothers who were underweight at the beginning of their pregnancies followed the recommended guidelines for weight gain.9 Mean weight gain was 37.5 lb for underweight, 38.8 lb for normal weight, 36.1 lb for overweight, 29 lb for obese, and 20 lb for morbidly obese patients. These weight gains were similar for cases and controls (data not shown). The overall cesarean section rate was 39%, 63% of which were scheduled for nonlaboring patients.
TABLE 1. Maternal demographics
| Demographic | Cases (n = 116) | Controls (n = 232) | Total | |
|---|---|---|---|---|
| Mean (SD) | Mean (SD) | Mean (SD) | P value | |
| Maternal age (y)a | 28.0 (5.5) | 27.9(5.7) | 27.9(5.6) | .34 |
| Third-trimester glucola (mg/dL)b | 111.0(23.5) | 110.3(27.8) | 110.5(26.5) | .91 |
| Mean weight gain (lb) | 35.4(16.3) | 35.5(16.2) | 35.5(16.3) | .99 |
| BMI at delivery | 32.8(7.3) | 31.8(5.7) | 32.2(6.3) | .21 |
| Prepregnancy BMI | No.(%) | Meanweightgain(lb)(SD) | ||
| Underweight | 15(4.3) | 37.5(11.9) | ||
| Normal | 169(48.6) | 38.8(13.6) | ||
| Overweight | 84(24.1) | 36.1(15.6) | ||
| Obese | 60(17.2) | 29(18.6) | ||
| Morbidly obese | 20(5.8) | 20(24.2) | ||
| Total | 348 | 35.5(16.3) | ||
| Cases | Controls | Total | ||
|---|---|---|---|---|
| Demographic | No. (%) | No. (%) | No. (%) | P value |
| Racea | .69 | |||
| Asian | 1(0.9) | 2(0.9) | 3(0.9) | |
| African American | 5(4.3) | 10(4.3) | 15(4.0) | |
| Hispanic | 13(11.2) | 26(11.2) | 39(11.2) | |
| White | 97(83.6) | 194(83.6) | 291(83.6) | |
| Substance use during pregnancy | ||||
| Nicotine use | 15(12.9) | 32(13.8) | 47(13.5) | .82 |
| Alcohol use | 2(1.7) | 3(1.3) | 5(2.0) | .08 |
| Drug use | 7(6.0) | 5(2.2) | 12(4.8) | .75 |
| Medical history | ||||
| Asthma | 17(14.7) | 24(10.3) | 41(11.8) | .24 |
| Hypertension | 10(8.6) | 9(3.9) | 19(5.5) | .10 |
| Education: HS diploma or higher | 106(91.4) | 205(88.4) | 311(89.4) | .34 |
| Insurance: public (Medicare/Medicaid) | 40(34.5) | 54(19.4) | 94(27.5) | <.01 |
| Total | 116(33.3) | 232(66) | 348(100) | |
aMatching factor; |
bGlucola values were available for all 3 members of 98 groups (294 patients total). To maintain the integrity of the matching structure, summary estimates are made for whole groups. |
TABLE 2. Delivery and neonatal characteristics from pregnancies with and without neonatal hypoglycemia
| Characteristic | Cases | Controls | Total | |
|---|---|---|---|---|
| Mean (SD) | Mean (SD) | Mean (SD) | P value | |
| Birthweight (g)a | 3512.1(598.9) | 3517.6(556.1) | 3515.8(569.9) | .93 |
| Gestational age (wk) | 39.2(1.2) | 39.8(1.2) | 39.6(1.2) | <.001 |
| Duration of labor (h) | 9.0(6.2) | 7.6(4.7) | 8.1(5.3) | <.01 |
| Duration of 2nd stage of labor (min) | 63.9(64.4) | 56.0(57.3) | 58.6(59.7) | .35 |
| Characteristic | No. (%) | No. (%) | No. (%) | P value |
|---|---|---|---|---|
| Gestational age (wk) | ||||
| 37 | 10(8.6) | 7(3.0) | 17(4.9) | <.001 |
| 38 | 23(19.8) | 26(11.2) | 49(14.1) | |
| 39 | 37(31.9) | 59(25.4) | 96(27.6) | |
| 40 | 26(22.4) | 69(29.7) | 95(27.3) | |
| 41 | 17(14.7) | 59(25.4) | 76(21.8) | |
| 42 | 3(2.6) | 12(5.2) | 15(4.3) | |
| Mode of delivery | ||||
| Spontaneous vaginal delivery | 54(46.6) | 121(52.2) | 175(50.3) | .10 |
| Operative vaginal delivery | 18(15.5) | 20(8.6) | 38(10.9) | |
| Cesarean section | 44(37.9) | 91(39.2) | 135(38.8) | |
| Elective | 25(56.8) | 59(64.8) | 84(62.7) | .36 |
| Nonelective | 19(43.2) | 31(34.1) | 50(37.3) | |
| 5-min Apgar score | ||||
| ≥ 8 | 111(95.7) | 230(99.1) | 341(98.0) | |
| Male gender | 68(58.6) | 113(48.7) | 181(52.0) | .10 |
| Maternal fever during labor | 14(12.2) | 8(3.5) | 22(6.4) | <.001 |
| Epidural use | 75(64.7) | 147(63.4) | 222(63.8) | .82 |
| Terbutaline use in labor | 4(3.0) | 2(<1) | 6(1.7) | .11 |
| Antibiotics before delivery | 34(29.3) | 51(22.0) | 85(24.4) | .11 |
| Induced labor | 30(25.9) | 48(20.1) | 75(21.6) | .33 |
| Augmented labor | 39(33.6) | 95(40.9) | 134(38.5) | .16 |
| Total | 116(33.3) | 232(66) | 348(100) |
aMatching factor. |
Results of the univariable analyses used to select candidate variables to develop the saturated model for each stage are displayed in Table 3. On the basis of the cutoff of P ≤ .20, hypertension, insurance type, and history of drug use were the only variables entered into the antepartum model. Only insurance type was retained for inclusion in the final model (P < .01). Cervical station, antibiotic use during labor, terbutaline administration during labor, length of labor, delivery mode, and presence or absence of maternal fever met the criterion for inclusion in the saturated intrapartum model. Only 1 variable, maternal fever, retained significance during the selection process for the final model (P < .01). Gestational age, 5-minute Apgar score, and sex of the infant were the variables meeting criteria for inclusion in the saturated neonatal model, and only gestational age was found to be significant for the final neonatal model (P < .001).
TABLE 3. Results of univariable conditional logistic regression analyses for variables associated with neonatal hypoglycemia
| Variable | OR (95% CI) | P value |
|---|---|---|
| Antepartum model | ||
| Gravidity | 0.91(0.77-1.08) | .27 |
| Parity | 0.93(0.72-1.20) | .57 |
| Weight gain | 0.99(0.99-1.01) | .99 |
| BMI (prepregnancy) | 1.02(0.99-1.06) | .21 |
| Glucola | 1.00(0.99-1.01) | .91 |
| GTT fasting | 0.88(0.65-1.19) | .40 |
| Maternal demographics | ||
| Age (y)a | 1.10(0.91-1.32) | .34 |
| HS diploma or greater | 0.67(0.29-1.53) | .34 |
| Racea | 1.69(0.13-21.10) | .69 |
| Public insurance | 2.40(1.27-4.55) | .01b |
| Maternal medical history | ||
| Asthma | 1.49(0.76-2.92) | .24 |
| Hypertension | 2.15(0.87-5.30) | .10b |
| Nicotine use | 0.92(0.46-1.83) | .82 |
| Drug use | 2.80(0.89-8.82) | .08b |
| Alcohol use | 1.33(0.22-7.98) | .75 |
| Other medical history | 1.33(0.82-2.16) | .25 |
| Intrapartum model | ||
| BMI (at delivery) | 1.02(0.99-1.06) | .21 |
| Dilation | 0.97(0.87-1.08) | .56 |
| Effacement | 0.97(0.57-1.68) | .93 |
| Station | 3.33(0.80-13.90) | .10b |
| Labor augmentation | 0.72(0.46-1.14) | .16b |
| Labor induction | 1.31(0.76-2.25) | .33 |
| Epidural | 1.06(0.67-1.67) | .82 |
| Pitocin administration | 1.10(0.70-1.74) | .67 |
| Antibiotic administration | 1.55(0.91-2.62) | .11b |
| IV pain medication administration | 1.08(0.51-2.28) | .85 |
| Antihypertensive administration | 1.07(0.3-3.67) | .92 |
| Terbutaline administration | 4.00(0.73-21.80) | .11b |
| IV dextrose administration | 1.40(0.46-4.29) | .56 |
| Duration of labor | 1.07(1.01-1.13) | .01b |
| Time since last meal | 0.97(0.92-1.02) | .28 |
| Delivery mode | 1.32(0.95-1.84) | .10b |
| Elective vs nonelective cesarean section | 1.79(0.51-6.27) | .36 |
| Maternal fever | 4.22(1.61-11.10) | .00b |
| Neonatal model | ||
| Gestational age | 0.64(0.52-0.79) | .00b |
| 5-min Apgar | 0.40(0.25-0.65) | .00b |
| Birthweighta | 1.00(1.00-1.00) | .61 |
| Sex (female vs male) | 0.68(0.44-1.06) | .10b |
| Cord pH | 1.00(0.99-1.00) | .48 |
aMatching factor; |
bMeets criterion of P < .20 for inclusion in the applicable saturated model. |
The 3 variables retained during model selection were combined to make up the final model and remained independently associated with early neonatal hypoglycemia after Bonferroni adjustment at a level of α = .05 (Pα/3 < .017). Hypoglycemia was less commonly associated with later gestational age (odds ratio [OR], 0.66; 95% confidence interval [CI], 0.53-0.85 per week of gestation). Maternal fever during labor was more common with hypoglycemia (OR, 4.08; 95% CI, 1.39-11.79). Public insurance was more than twice as common with hypoglycemia compared with those privately insured (OR, 2.31; 95% CI, 1.17-4.58) (Table 4).
TABLE 4. Variables significantly associated with neonatal hypoglycemia in final regression model (ORs, 95% CIs, and P values for variables retained in the final regression model)
| Variable | OR (95% CI) | P value |
|---|---|---|
| Gestational age (wk)a | 0.66 (0.53-0.82) | .000 |
| Public insurancea | 2.31 (1.17-4.58) | .016 |
| Maternal fevera | 4.04 (1.39-11.69) | .010 |
aSatisfies Bonferroni correction criterion: P < .017. |
Maternal age, race, and birthweight were not significant alone, combined, or in any models with other variables, indicating that the matching structure did in fact control for these variables' anticipated confounding effects. There were no clinical hypotheses regarding possible interactions between the variables in any of the 3 stages or among the variables included in the final model. Therefore, interaction terms were not included in this analysis.
Comment
The definition of neonatal hypoglycemia has been an area of debate in the literature. Studies have been unable to define a precise blood glucose value at which clinical manifestations or long-term damage occurs.10 The glucose level below which there is an increased risk for long-term neurologic sequelae most likely varies, based on available substrates, cerebral blood flow, the presence of intrauterine growth restriction and the duration of hypoglycemia.1 Several different investigators have used a range of blood glucose values to define neonatal hypoglycemia in the first 24 hours of life.2, 3, 11 Historically, 40 mg/dL or less has been used as a standard definition of hypoglycemia.12 Our institutional protocol defines infant hypoglycemia as < 50 mg/dL, which is a comparatively conservative estimate. Defining hypoglycemia using the standard cutoff of ≤ 40 mg/dL reduces the prevalence in our sample population to 1.6% and the incidence density to 16.2 cases per 1000 infant-days.
Our institution's protocol of a routine blood sugar test in all neonates allowed us to precisely define the incidence of a potential adverse outcome in a population of infants that is otherwise considered to be at low risk for postnatal complications. In the literature, the incidence is not well established. Reports range from 3% to 29%, but these estimates include both term and preterm infants.1 Methods of incidence calculation are rarely reported, which raises a question as to the validity of the reported incidence figures.
The case-control design of our study allowed us to systematically examine many factors that could potentially influence the development of hypoglycemia while controlling for the effects of established confounding factors. We found in our population that advancing gestational age within the confines of a term pregnancy decreases the chance of having a neonate with hypoglycemia. It was somewhat surprising that the results held true even between 40 and 42 weeks, because the risk of many adverse pregnancy outcomes increases in the postterm pregnancy. It should be noted that few patients were delivered at or after 42 weeks (only 15/348), limiting the conclusions that can be drawn from this small number of patients. Public insurance coverage was found to increase the risk of neonatal hypoglycemia, a risk factor that had not been examined in prior studies. This may be due to economic factors leading to different nutritional intake during pregnancy or because it acts as a proxy for a complicated interplay between many factors, which examined alone, did not achieve significance (race, substance abuse, or weight gain during pregnancy). Fever was the most significant variable in the final model. This was not an unexpected result, because neonatal infection is a known risk factor for hypoglycemia. Although fever may be associated with intraamniotic infection or chorioamnionitis (known risk factors for hypoglycemia), intrapartum fever has also been linked to noninfectious causes, such as epidural anesthesia.13 Regardless of the cause, fever is associated with increased fetal heart rate, which may represent increased metabolism, which would predispose to a drop in blood glucose after delivery.
The results of our study did not show a statistically significant difference in some factors that prior studies have identified as predictors of risk, such as mode of delivery and weight gain. Cole and Peevy4 in 1994 performed a case-control study of 60 patients in which they examined the odds of developing hypoglycemia in vaginal deliveries vs elective cesarean sections. They found a higher incidence of neonatal hypoglycemia in cesarean sections, suggesting that hypoglycemia can be affected by either the mode of delivery or the process of labor itself. This is in contrast to our investigation, in which the mode of delivery did not seem to influence the odds of hypoglycemia, even when taking into account those delivered by cesarean section with or without labor. Hedderson et al5 in 2006 examined how weight gain in pregnancy affected the risk of neonatal hypoglycemia. They demonstrated a statistically significant increase in the risk of neonatal hypoglycemia when weight gain was above the recommendations by the Institute of Medicine. In their investigation, pregnancy weight gain was calculated by taking into account the infant birthweight and subtracting it from the weight noted at the last prenatal visit. We calculated weight gain by subtracting the prepregnancy weight from the patient's current weight on admission to labor and delivery. Because both of the numbers used in our study were self-reported, there could potentially be a reporting bias. An underestimation of the patient's weight gain in pregnancy may have masked an association that could be present if a more accurate assessment of the true weight gain were obtained.
Our study has several strengths. A protocol for universal glucose testing in neonates allowed more accurate assessment of rates, whereas limiting statistical bias. It encompassed a larger sample size than most articles published on the topic, allowing us to potentially find factors not associated in prior studies because of smaller sample sizes. In addition, our hospital uses an electronic medical record for all inpatients and in many of the outpatient practices, providing us with a large amount of accurately recorded data. We examined a population that has not been closely investigated in the literature—that is, infants not traditionally considered at high risk for neonatal hypoglycemia.
There are several weaknesses of the study. Cases were identified by ICD-9 codes, which may not have captured all infants with neonatal hypoglycemia. Because our study was retrospective in design, there were several pieces of data that were unable to be collected, such as the time after birth that the neonate was first fed, the type of feeding with the time relationship to the diagnosis of hypoglycemia, and what the mother ingested during labor. In addition, some of the data points collected were inconsistently recorded or self-reported, including the time of last meal before admission. This could result in either an over- or underestimation of the true associations. Last, prior studies have suggested that other factors around the time of delivery may influence the risk of neonatal hypoglycemia, such as regional anesthesia.4 The use of epidural anesthesia for labor in our study population was about 64% in both cases and controls. If the relationship between anesthesia and neonatal hypoglycemia is small, one would need a larger sample size that is not necessarily proportional between cases and controls to detect a difference.
In summary, neonatal hypoglycemia (glucose < 50 mg/dL) is associated with earlier gestational ages (even at term), intrapartum fever, and public insurance. These data may be helpful for targeting the higher-risk pregnancies for potential interventions to reduce the rate or severity of neonatal hypoglycemia.
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PII: S0002-9378(08)02028-0
doi:10.1016/j.ajog.2008.10.015
© 2009 Mosby, Inc. All rights reserved.
Volume 200, Issue 5 , Pages e45-e51, May 2009
