Abstract
Introduction
Umbilical cord blood measurement is the gold standard of evaluating neonatal metabolic status at birth. Dual sampling of cord blood vessels is clinical routine, yet the long-term value of venoarterial differences (ΔpH) is undetermined. The objective was to investigate the association of ΔpH, to long-term mortality and morbidity up to 20 years.
Material and methods
This was a retrospective cohort study with singleton births 1997–2012 at Skåne University hospital, Malmö, Sweden. Validated umbilical cord blood records were crosslinked to data from high quality national registers. Hazard ratios (HR) for diagnosis according to International Classification of Disease version 10 (00−99) during the follow-up period were calculated for the ≤ 10th/10th–90th/≥ 90th percentiles of ΔpH, adjusted for maternal age, smoking, body mass index, parity and gestational age.
Results
The study population was comprised of 35 171 births meeting the inclusion criteria after validation. Of the included births 4 956/14.1% had a small ΔpH (≤0.040), 26 690/75.9% normal ΔpH (0.041–0.150) and 3 525/10.0% large ΔpH (≥0.151). HR were statistically significant for small ΔpH for diseases of the eye and adnexa, crude HR:1.095 (95%CI:1.021–1.175), adjusted HR:1.081 (95%CI 1.007–1.160). No other organ system diseases were associated with small/large ΔpH.
Conclusion
ΔpH showed no strong long-term association of increased risk of organ-system related morbidity or mortality with twenty years of follow-up time. Multiple comparison may explain statistically significant finding of HR diseases of the eye and adnexa. Dual umbilical cord blood sampling remains vital clinically, ensuring correct sampling.
Keywords: Venoarterial differences, Long-term outcome, Morbidity, Mortality, Umbilical cord pH
Introduction
Measurement of umbilical cord blood gases is the most objective screening method of testing the metabolic state of the neonate [1], [2], [3]. A sustained lack of oxygen during birth can lead to metabolic acidemia, which can easily be tested by sampling the umbilical cord blood pH [2]. Before, umbilical cord arterial pH has been correlation to both short- and long-term adverse neonatal outcomes such as hypoxic ischemic injury and cerebral palsy [4], [5].
Both umbilical cord arterial pH and umbilical cord venous pH are typically sampled. The difference between the umbilical cord venous pH and the umbilical cord arterial pH, the venoarterial difference, is termed ΔpH. Physiologically, ΔpH reflects the function of the placenta during birth, in removing waste products and replenishing fetal blood during the intermittent disruption in oxygen delivery during birth [6].
Whilst ΔpH is largely recognized in clinical practice as a surrogate marker for placental function; its predictive value for adverse outcomes remains an area of ongoing investigation [5]. A large population-based study of Swedish neonates found that large venoarterial differences (large values of ΔpH) at birth were associated with a lower risk for perinatal morbidity including low 5-minute Apgar Score, the need for continuous positive airway pressure and neonatal intensive care admission when the overall umbilical cord arterial pH was above 7.15 [7]. Another study found correlation between ΔpH adverse neonatal outcomes, while another did not [8], [9]. This suggests that clinically, ΔpH may be a useful tool in the assessment of the neonate’s metabolic condition at birth.
Given its potential role in early recognition of neonatal acidemia, ΔpH warrants further research as a possible adjunct in perinatal monitoring and outcome prediction. Therefore, the objective of our study was to investigate if small and large venoarterial differences in cord blood, ΔpH, could correlate to long-term outcomes with up to twenty years of follow-up in survivors.
Material and methods
Study population and follow-up time
This was a retrospective cohort study including live-born, singleton births from Skåne University hospital in Malmö, Sweden between January 1st 1997 and May 8th 2012. Follow-up time was up to December 31st 2017, resulting in follow-up for a minimum of five years for the youngest participants in the cohort and up to 20 years for the oldest participants in the cohort.
Umbilical cord blood pH validation
At the hospital, umbilical cord blood sampling has routinely been performed since 1981. Staff are well-trained in the correct way of umbilical cord blood sampling. Only cases with both arterial and venous umbilical cord pH samples were included, following the standard in the field although research has shown physiological occurrence of small and negative ΔpH [10], [11]. If the difference between UVpH and UApH was less than 0.02 cases were excluded to avoid inclusion of single vessel samples. (Fig. 1).
Fig. 1.
Flow chart of inclusion into study on association of venoarterial differences in umbilical pH and long-term morbidity and mortality.
Delta pH
ΔpH was calculated using the following equation: ΔpH= UVpH – UApH
Cases were divided into three groups based on percentile values for ΔpH: small ΔpH corresponding to the lowest 10 %, normal ΔpH 10–90 % percentiles and large ΔpH corresponding to the 90 % percentile and above.
Data collection and databases
Birth data was retrieved from the maternal health records, including information about maternal personal identification number, date of birth and registered arterial and venous umbilical cord pH values and relevant obstetric and neonatal birth data. Each unique maternal personal identification number was cross-linked to the associated neonatal identification number. These were used to extract data from several high-quality national health registers. These included the national Swedish Patient Register, Swedish Medical Birth Register (SMBR) and Cause of Death Register [12], [13], [14]. Data from the Swedish Patient Register covers diagnose codes from both in-patient and out-patient care from the year 2000 [12]. SMBR is a high-quality national register in Sweden with prospectively collected data from the prenatal, intra-partum and post-partum period [13]. From the Cause of death register [14], data regarding cause of death was received.
Of note, at four years of age, all children in Sweden are invited to an extensive health check-up [15]. This is done to detect potential neuro-developmental disorders. The health check-up is standardized according to national guidelines to ensure good quality. Cognitive function is with children asked to perform different tasks such as drawing, sorting objects and performing tests during the visit. Language is tested via interplay and with use of visual aids for naming objects. Both gross and fine motor skills are tested via play. Hearing and sight are screened. Social skills are tested and evaluated throughout the visit. Any anomalies are reported in the Swedish Patient Register [12].
Covariates
Data on year of birth, maternal age, parity, smoking status, early-pregnancy body mass index (BMI), birth mode, gestational age, sex, birthweight, and 5-minute Apgar score were obtained from the SMBR [13].
Year of birth was categorized into three groups: individuals born between 1997–2002, with follow-up data available until ages 15–20; those born between 2003–2007, with follow-up until ages 10–15; and those born between 2008–2012, with follow-up until ages 5–10. Maternal BMI (kg/m²) in the first trimester was classified according to the World Health Organization (WHO) criteria: underweight (<18.5), normal weight (18.5–24.9), overweight (25.0–29.9), and obese (≥30.0). Mothers who reported daily smoking at their first antenatal visit and/or at 30–32 weeks of gestation were classified as smokers. Birthweight was classified into small for gestational age (SGA) (<10th percentile), appropriate for gestational age (AGA) (10th-90th percentile), and large for gestational age (LGA) (>90th percentile).
Birth mode was categorized as vaginal non-instrumental, vaginal instrumental, elective cesarean section (CS), or emergency CS.
International classification of diseases
We used the International Classification of Diseases (ICD) diagnose codes that have been registered in the national health registers, with all categories included. This study, spanning births between January 1st 1997 and May 8th 2012, included diagnose codes from both ICD-9 and ICD-10 [16].
Statistical analysis
ΔpH was divided into three categories according to percentiles. Small (ΔpH ≤0.04, <10th percentile), normal (ΔpH= 0.041–0.150, 10th-90th percentile) and large (ΔpH ≥0.151, >90th percentile). Maternal and neonatal descriptive data were reported for all percentile groups in the study as absolute numbers and percentages.
Cox regressions analysis was performed for whole organ system diagnoses defined by ICD codes 00–99 in order to study associations between risk for diagnosis of organ system related condition and exposure to small or large ΔpH compared to the normal ΔpH. Crude hazard ratios (HR) were reported with 95 % confidence intervals. After that, adjusted HR was calculated after adjusting for parity, age, BMI, smoking, and gestational age. A two-sided P-value of < 0.05 was considered significant. Statistical analyses were performed in SPSS version 29 (IBM Corp., Armonk, NY, USA).
Results
Of 59 140 neonates initially included in the study, after validation of cord blood pH, 35 171 individuals were included in the final study population (35 171/59 140 = 59.5 %).
Table 1 portrays the maternal and neonatal characteristics of the study population stratified by three groups based on ΔpH. Groups are largely similar in relation to maternal characteristics. For mode of birth, there were differences in small/normal/large ΔpH groups: elective CS (5.1 %/3.0 %/0.4 %), emergency CS (21.5 %/7.4 %/2.0 %) and VE/forceps (6.0 %/6.8 %/11.5 %). Number of gestational weeks had an impact on ΔpH, shown by ΔpH groups for 28–31 completed weeks (0.8 %/0.2 %/0.1 %), 32–36 completed weeks (6.5 %/3.5 %/2.8 %). At term, the groups had the following percentages (84.8 %/88.8 %/88.6 %). Birth weights corrected for gestational age showed SGA (4.9 %/2.9 %/1.3 %), AGA (90.5 %/92.3 %/91.1 %) and LGA (3.6 %/4.1 %/6.7 %) respectively. Of note, a higher percentage of SGA neonates had smaller ΔpH values.
Table 1.
Maternal and neonatal characteristics of the study population stratified in ΔpH percentile groups.
| ΔpHa≤ 0.040 N = 4 956 |
ΔpH 0.041–0.150 N = 26 690 |
ΔpH ≥ 0.151 N = 3 525 |
|||||
|---|---|---|---|---|---|---|---|
| n | (%) | n | (%) | n | (%) | ||
| Year of birth | |||||||
| 1997–2002 | 1608 | (32.4) | 8462 | (31.7) | 1421 | (40.3) | |
| 2003–2007 | 1720 | (34.7) | 8544 | (32.0) | 988 | (28.0) | |
| 2008–2012 | 1628 | (32.8) | 9684 | (36.3) | 1116 | (31.7) | |
| Maternal age (years) | |||||||
| < 20 | 194 | (3.9) | 991 | (3.7) | 112 | (3.2) | |
| 20–24 | 776 | (15.7) | 4154 | (15.6) | 475 | (13.5) | |
| 25–29 | 1435 | (29.0) | 7968 | (29.9) | 1063 | (30.2) | |
| 30–34 | 1608 | (32.4) | 8820 | (33.0) | 1185 | (33.6) | |
| 35–39 | 798 | (16.1) | 4049 | (15.2) | 571 | (16.2) | |
| 40 + | 145 | (2.9) | 708 | (2.7) | 119 | (3.4) | |
| Parity | |||||||
| Primipara | 2769 | (55.9) | 14646 | (54.9) | 1679 | (47.6) | |
| Multipara | 2187 | (44.1) | 12044 | (45.1) | 1846 | (52.4) | |
| Maternal smoking | |||||||
| Yes | 505 | (10.2) | 2608 | (9.8) | 342 | (9.7) | |
| No | 4238 | (85.5) | 23209 | (87.0) | 3028 | (85.9) | |
| Not known | 213 | (4.3) | 873 | (3.3) | 155 | (4.4) | |
| Maternal BMIb(kg/m2) | |||||||
| < 18.5 | 119 | (2.4) | 593 | (2.2) | 50 | (1.4) | |
| 18.5–24.9 | 2799 | (56.5) | 15361 | (57.6) | 1861 | (52.8) | |
| 25.0–29.9 | 1171 | (23.6) | 6171 | (23.1) | 849 | (24.1) | |
| 30 + | 459 | (9.3) | 2438 | (9.1) | 446 | (12.7) | |
| Not known | 408 | (8.2) | 2127 | (8.0) | 319 | (9.0) | |
| Mode of birth | |||||||
| Vaginal, non-instrumental | 3336 | (67.3) | 22113 | (82.9) | 3037 | (86.2) | |
| Elective CSc | 255 | (5.1) | 810 | (3.0) | 13 | (0.4) | |
| Emergency CS | 1068 | (21.5) | 1963 | (7.4) | 69 | (2.0) | |
| VE/Forceps | 297 | (6.0) | 1804 | (6.8) | 406 | (11.5) | |
| Gestational age (completed weeks) | |||||||
| < 28 | 6 | (0.1) | 9 | (0.0) | 2 | (0.1) | |
| 28–31 | 41 | (0.8) | 52 | (0.2) | 3 | (0.1) | |
| 32–36 | 321 | (6.5) | 946 | (3.5) | 100 | (2.8) | |
| 37–41 | 4204 | (84.8) | 23707 | (88.8) | 3124 | (88.6) | |
| 42 + | 384 | (7.7) | 1976 | (7.4) | 296 | (8.4) | |
| Sex | |||||||
| Male | 2614 | (52.7) | 13917 | (52.1) | 1888 | (53.6) | |
| Female | 2342 | (47.3) | 12773 | (47.9) | 1637 | (46.4) | |
| Birth weight for gestational age | |||||||
| SGAd | 243 | (4.9) | 762 | (2.9) | 46 | (1.3) | |
| AGAe | 4487 | (90.5) | 24637 | (92.3) | 3213 | (91.1) | |
| LGAf | 176 | (3.6) | 1093 | (4.1) | 237 | (6.7) | |
| Not known | 50 | (1.0) | 198 | (0.7) | 29 | (0.8) | |
| Apgar score at 5 min | |||||||
| < 7 | 81 | (1.6) | 184 | (0.7) | 55 | (1.6) | |
| 7–10 | 4870 | (98.3) | 26487 | (99.2) | 3468 | (98.4) | |
| Not known | 5 | (0.1) | 19 | (0.1) | 2 | (0.1) | |
| Survival | |||||||
| Death 0–4.9 years | 3 | (0.1) | 23 | (0.1) | 5 | (0.1) | |
| Death 5–9.9 years | 1 | (0.0) | 7 | (0.0) | 0 | (0.0) | |
| Death 10 + years | 1 | (0.0) | 7 | (0.0) | 3 | (0.1) | |
ΔpH: Venoarterial Difference
BMI: Body Mass Index
CS: Cesarean Section
SGA: Small for Gestational Age
AGA: Appropriate for Gestational Age
LGA: Large for Gestational Age
Distribution of morbidity is presented in Table 2 across various diagnoses according to the ICD. Categories are presented for the entire population, stratified into small, normal or large ΔpH. A higher prevalence of mental and behavioral disorders was noted for small and large ΔpH (3.1 and 4.2 %, vs 2.8 % for normal ΔpH). For sub-group diagnoses, motor disability accounted for a higher prevalence for both small ΔpH and large ΔpH (4.7 and 4.9 %, vs 4.0 % for normal ΔpH). Regarding only small ΔpH, diseases of the ear and mastoid were slightly more prevalent compared to normal ΔpH and large ΔpH (24.9 % vs 23.8 and 23.1 %).
Table 2.
Child morbidity in liveborn singleton neonates classified by organ system related diseases from the National Swedish Patient Register (1997–2012) divided by ΔpH percentile groups.
| ΔpHa ≤ 0.040 |
ΔpH 0.041–0.150 |
ΔpH ≥ 0.151 |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| All, without considering length of follow-up | Cases 0–5 years among all followed ≥ 5 years | Cases 0–10 years among all followed ≥ 10 years | Cases 0–15 years among all followed ≥ 15 years | All, without considering length of follow-up | Cases 0–5 years among all followed ≥ 5 years | Cases 0–10 years among all followed ≥ 10 years | Cases 0–15 years among all followed ≥ 15 years | All, without considering length of follow-up | Cases 0–5 years among all followed ≥ 5 years | Cases 0–10 years among all followed ≥ 10 years | Cases 0–15 years among all followed ≥ 15 years | |
| Background population (N) | 4 956 | 4 821 | 2 982 | 1 336 | 26 690 | 25 933 | 15 296 | 7 032 | 3 525 | 3 411 | 2 224 | 1 253 |
| % | % | % | % | % | % | % | % | % | % | % | % | |
| Infectious & parasitic diseases | 34.3 | 29.7 | 33.7 | 32.0 | 34.1 | 29.9 | 35.0 | 32.9 | 34.2 | 28.6 | 33.5 | 30.6 |
| Neoplasms | 4.6 | 2.1 | 4.0 | 6.5 | 4.4 | 2.1 | 3.5 | 5.4 | 5.4 | 2.2 | 3.6 | 6.1 |
| Diseases of the blood & blood-forming organs & immune disorders | 2.3 | 1.5 | 1.9 | 3.0 | 2.3 | 1.5 | 2.1 | 2.6 | 2.3 | 1.5 | 2.1 | 2.8 |
| Endocrine, nutritional & metabolic diseases | 8.6 | 3.8 | 6.6 | 9.4 | 7.8 | 3.3 | 6.0 | 9.7 | 8.3 | 2.9 | 5.8 | 8.9 |
| Mental and behavioral disorders | 3.1 | 0.2 | 0.7 | 3.9 | 2.8 | 0.2 | 0.7 | 3.8 | 4.2 | 0.3 | 0.7 | 4.7 |
| Intellectual disability | 1.0 | 0.4 | 1.1 | 1.5 | 0.9 | 0.3 | 0.8 | 1.1 | 0.8 | 0.3 | 1.0 | 1.5 |
| Speech disorders | 1.7 | 0.8 | 1.1 | 1.0 | 1.6 | 0.7 | 1.2 | 1.6 | 1.4 | 0.5 | 1.5 | 1.4 |
| Autism spectrum | 1.4 | 0.3 | 0.9 | 1.2 | 1.4 | 0.4 | 0.8 | 1.3 | 1.6 | 0.2 | 0.9 | 1.6 |
| Motor disability | 4.7 | 0.6 | 4.0 | 6.4 | 4.0 | 0.4 | 3.5 | 5.3 | 4.9 | 0.4 | 4.1 | 5.0 |
| Epilepsy | 0.9 | 0.4 | 0.8 | 1.2 | 0.9 | 0.5 | 0.9 | 1.2 | 1.0 | 0.4 | 1.1 | 1.7 |
| Cerebral palsy | 0.3 | 0.2 | 0.5 | 0.6 | 0.2 | 0.2 | 0.3 | 0.3 | 0.3 | 0.2 | 0.2 | 0.3 |
| Other | 3.7 | 1.6 | 3.0 | 5.1 | 3.6 | 1.3 | 3.0 | 5.1 | 3.8 | 1.3 | 2.7 | 5.4 |
| Diseases of the eye & adnexa | 18.9 | 10.3 | 18.1 | 23.4 | 17.1 | 9.4 | 18.1 | 20.5 | 18.4 | 8.9 | 17.9 | 21.3 |
| Diseases of the ear & mastoid | 24.9 | 22.0 | 26.6 | 25.5 | 23.8 | 20.9 | 25.6 | 23.8 | 23.1 | 19.4 | 23.7 | 21.2 |
| Diseases of the circulatory system | 1.7 | 0.6 | 1.2 | 2.3 | 1.9 | 0.8 | 1.5 | 2.2 | 2.1 | 0.5 | 1.5 | 2.7 |
| Diseases of the respiratory system | 46.1 | 40.4 | 47.4 | 45.7 | 45.7 | 39.9 | 47.1 | 45.7 | 47.9 | 39.6 | 45.7 | 46.4 |
| Diseases of the digestive system | 15.9 | 9.3 | 13.3 | 18.4 | 15.9 | 9.5 | 14.0 | 18.4 | 17.3 | 9.6 | 14.7 | 18.5 |
| Diseases of the skin & subcutaneous | 19.4 | 12.1 | 17.7 | 21.8 | 19.7 | 13.1 | 18.6 | 21.4 | 20.4 | 12.1 | 18.9 | 20.0 |
| Diseases of the musculoskeletal system & connective tissue | 11.7 | 4.3 | 7.8 | 16.4 | 11.4 | 3.9 | 8.5 | 16.1 | 13.1 | 4.1 | 8.8 | 13.6 |
| Diseases of the genitourinary system | 10.3 | 5.6 | 8.8 | 11.9 | 10.5 | 6.2 | 9.9 | 13.0 | 11.6 | 5.9 | 8.3 | 11.8 |
| Malformations | 12.0 | 8.9 | 10.3 | 12.1 | 10.8 | 8.0 | 9.8 | 10.5 | 11.3 | 8.6 | 9.7 | 11.9 |
| Symptoms, signs and abnormal clinical and laboratory findings | 38.1 | 25.2 | 35.4 | 39.1 | 37.9 | 24.8 | 35.8 | 42.1 | 39.3 | 23.2 | 33.7 | 39.1 |
| Injuries & poisoning | 47.6 | 25.8 | 39.9 | 53.6 | 46.5 | 26.0 | 40.5 | 54.0 | 48.1 | 25.5 | 39.0 | 52.3 |
ΔpH: Venoarterial Difference
Results for calculation of both crude and adjusted HR for small and large ΔpH for all studied whole organ systems diseases according to the ICD are shown in Table 3. Of those born with a small ΔpH, 18 % were diagnosed with an eye condition during the whole follow-up time, whereas 17 % of controls had a crude HR 1.095 (95 %CI 1.021–1.175) and adjusted HR 1.081 (95 %CI 1.007–1.160). Neonates born with a small ΔpH had a higher occurrence of motor disability at 4.7 % during the follow-up time, when 4 % were diagnosed in the control group. The crude HR 1.159 with 95 %CI 1.006–1.335, whereas the adjusted HR was 1.142 (95 %CI 0.991–1.316). No other conditions were significantly associated with a raised HR.
Table 3.
Child morbidity in liveborn singleton neonates classified by organ system related diseases from the National Swedish Patient Register (1997–2012) divided by ΔpH percentile groups.
|
Hazard Ratio (HR)a | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| ΔpH ≤ 0.040 vs ΔpH 0.041–0.150 |
ΔpH ≥ 0.151 vs ΔpH 0.041–0.150 |
|||||||||
| Crude HR |
Adjusted HR |
Crude HR |
Adjusted HR |
|||||||
| HR | 95 %CI | AHRb | 95 %CI | HR | 95 %CI | AHR | 95 %CI | |||
| Infectious & parasitic diseases | 1.002 | 0.951–1.055 | 0.99 | 0.940–1.043 | 0.976 | 0.919–1.036 | 0.979 | 9.22–1.040 | ||
| Neoplasms | 1.028 | 0.892–1.184 | 1.014 | 0.880–1.168 | 1.120 | 0.961–1.305 | 1.155 | 0.991–1.347 | ||
| Diseases of the blood & blood-forming organs & immune disorders | 0.957 | 0.783–1.170 | 0.943 | 0.771–1.154 | 0.940 | 0.746–1.183 | 0.921 | 0.731–1.160 | ||
| Endocrine, nutritional & metabolic diseases | 1.078 | 0.971–1.196 | 1.059 | 0.954–1.176 | 0.987 | 0.873–1.116 | 0.972 | 0.859–1.099 | ||
| Mental and behavioral disorders | 1.043 | 0.876–1.241 | 1.030 | 0.865–1.227 | 1.128 | 0.946–1.345 | 1.148 | 0.962–1.369 | ||
| Intellectual disability | 1.169 | 0.863–1.584 | 1.126 | 0.830–1.526 | 0.900 | 0.612–1.325 | 0.896 | 0.608–1.320 | ||
| Speech disorders | 1.060 | 0.840–1.339 | 1.017 | 0.805–1.284 | 0.833 | 0.621–1.117 | 0.839 | 0.625–1.126 | ||
| Autism spectrum | 0.981 | 0.759–1.269 | 0.956 | 0.739–1.237 | 1.007 | 0.759–1.338 | 1.030 | 0.774–1.369 | ||
| Motor disability | 1.159 | 1.006–1.335 | 1.142 | 0.991–1.316 | 1.101 | 0.937–1.294 | 1.107 | 0.941–1.301 | ||
| Epilepsy | 1.017 | 0.745–1.390 | 0.992 | 0.725–1.357 | 1.083 | 0.766–1.531 | 1.098 | 0.776–1.554 | ||
| Cerebral palsy | 1.392 | 0.816–2.374 | 1.321 | 0.773–2.258 | 1.023 | 0.509–2.053 | 1.015 | 0.504–2.043 | ||
| Diseases of the nervous system | 1.007 | 0.860–1.178 | 0.981 | 0.838–1.149 | 0.937 | 0.781–1.123 | 0.952 | 0.793–1.142 | ||
| Diseases of the eye & adnexa | 1.095 | 1.021–1.175 | 1.081 | 1.007–1.160 | 1.039 | 0.957–1.128 | 1.042 | 0.960–1.132 | ||
| Diseases of the ear & mastoid | 1.045 | 0.983–1.110 | 1.036 | 0.975–1.101 | N/Ac | N/A | N/A | N/A | ||
| Diseases of the circulatory system | 0.903 | 0.718–1.137 | 0.890 | 0.706–1.121 | 1.010 | 0.789–1.291 | 1.016 | 0.793–1.300 | ||
| Diseases of the respiratory system | 1.011 | 0.967–1.057 | 1.00 | 0.956–1.045 | N/A | N/A | N/A | N/A | ||
| Diseases of the digestive system | 0.981 | 0.909–1.058 | 0.963 | 0.892–1.039 | 1.024 | 0.941–1.115 | 1.042 | 0.957–1.135 | ||
| Diseases of the skin & subcutaneous | 0.968 | 0.904–1.037 | 0.960 | 0.896–1.028 | 0.977 | 0.904–1.057 | 0.981 | 0.908–1.061 | ||
| Diseases of the musculoskeletal system & connective tissue | 0.997 | 0.912–1.090 | 0.984 | 0.900–1.076 | 1.024 | 0.928–1.130 | 1.037 | 0.940–1.145 | ||
| Diseases of the genitourinary system | 0.959 | 0.873–1.054 | 0.950 | 0.865–1.045 | 1.032 | 0.930–1.145 | 1.043 | 0.940–1.157 | ||
| Malformations | 1.102 | 1.009–1.204 | 1.073 | 0.982–1.172 | 1.017 | 0.916–1.129 | 1.041 | 0.937–1.157 | ||
| Injury and poisoning | 1.008 | 0.946–1.044 | 1.009 | 0.965–1.054 | 0.971 | 0.923–1.021 | 0.968 | 0.920–1.019 | ||
| Symptoms, signs and abnormal clinical and laboratory findings | 0.994 | 0.946–1.044 | 0.980 | 0.933–1.030 | 0.973 | 0.920–1.030 | 0.988 | 0.933–1.045 | ||
HR: Hazard ratio obtained from Cox regression analyses
AHR: Adjusted Hazard Ratio for maternal age, parity, smoking, BMI, and gestational age.
N/A: Model with interaction, Cox regression was not performed.
Discussion
Main findings
In this large retrospective cohort study, small venoarterial differences in umbilical cord blood (ΔpH) were not shown to be independently associated with organ system related disease. A small increase in risk for diseases of the eye and adnexa was observed, but this may be attributed to chance from multiple comparisons. No other association with organ-related diagnoses in survivors up to 20 years of follow-up was found for small or large ΔpH. Our findings therefore suggest use of cord blood measurement of both arterial and venous umbilical cord blood is primarily important for internal sampling validation, to ensure correct blood vessel sampling, particularly for umbilical cord arterial pH.
In light of other evidence
While in clinical practice, the assessment of ΔpH is generally regarded as a valuable tool in identifying good placental function during birth [6], [17], there have been limited studies investigating the value of ΔpH, especially with regard to outcome data [2], [7], [8], [9], [18], [19]. Previous findings suggest that a large ΔpH suggest well-maintained placental function [7]. To the best of our knowledge, this is the first study on the long-term outcomes of a small or large ΔpH at birth. On the other hand, UApH has been well-studied previously, and has shown strong predictive value related to adverse outcomes [4], [5], [10], [20], [21].
We found that small ΔpH values were not strongly associated with whole organ system-related diagnoses. A correlation between attention deficit hyperactive disorder and birth asphyxia has been shown in previous studies, with various, but often small effect sizes, as reported by Danielsson et al. [22]. In our study there was a correlation for small ΔpH, that did not sustain after adjustment. No correlation was seen to any other neurodevelopmental disorder. In a recent study from the same cohort, our research group found that when examining the risk of organ system related diseases, acidemia defined as UApH < 7.05 was linked to increased risk of cerebral palsy and epilepsy, with an added increased risk of intellectual disability at UApH < 6.95 [5].
Different cell-types exhibit different sensitivity to hypoxia, with cerebral tissue at high risk of damage in the event of hypoxia and acidemia at birth. Cerebral tissue consists of many cell types, including neurons and different types of glial cells brain. It is well known that neonates born prematurely are at risk of developing an eye disease termed retinopathy of prematurity, a neurovascular condition potentially causing blindness [23]. In performing a literature search on the topic of hypoxia-related eye conditions reports on, eye conditions with relation to hypoxia were not found. Dammann et al. [23], provided a comprehensive review on eye pathology in prematurity, detailing its pathogenesis involving dysregulated angiogenesis due to oxygen fluctuations in preterm infants, along with risk factors such as low birth weight and supplemental oxygen therapy. Similarly, a study by Ianchulev et al. investigated optic nerve atrophy in neonates with propionic acidemia, a rare metabolic disorder leading to mitochondrial dysfunction and neurotoxicity [24]. They demonstrated how elevated propionic acid levels disrupted optic nerve integrity, through excitotoxicity and energy metabolism deficits. While these studies discuss the interplay between ocular pathologies and acidemia findings, our study does not present strong correlation that would correspond to pathophysiological mechanism from sustained lack of oxygenation and subsequent ocular damage.
Strengths and limitations
The large sample size was a major strength of this study. The use of strictly validated umbilical cord blood pH samples was another strength that ensured high-quality data for analysis. The umbilical cord blood pH validation process followed established standards in the field, enhancing the reliability of our findings [6], [25], [26]. Additionally, the sampling techniques employed by the hospital have been well-defined since 1981. This meant that samples were obtained by healthcare professionals that were routinely involved in sample procurement as cord blood sampling is performed routinely at birth in Skåne University Hospital. As previously mentioned, no other study in literature has investigated the long-term outcomes of ΔpH.
The study does have limitations. One notable limitation is the potential for selection bias due to the strict inclusion criteria for sample validation. This led to the exclusion of a sizable portion of the original study population, which limit the generalizability of our results. However, sample validation is mandatory for all cord blood pH studies, especially those investigating venoarterial differences as one must know which sample is from the UV and which is from the UA. Furthermore, some acute clinical situations may lead to single vessel sampling, where prioritizing immediate care over the collection of both samples could introduce a bias. Similarly, uncomplicated births may not have had umbilical cord blood samples taken, particularly when healthcare workers are managing high workloads or trying to reduce costs. Another potential limitation is an inclusion error, where the cut-off criteria for small and large ΔpH may have been too relaxed, potentially diluting the significance of the findings. A more stringent threshold might have led to more pronounced differences, but this would have also reduced the study's power. Statistical analysis of all whole system related diseases 0–99 meant performing statistical analyses several times. With increased number of analyses the risk of inadvertent false positive results arises. Considering this, the small statistical increase in the HR for diseases of the eye and adnexa, even if clinically possible, does not seem plausible, and is not strong enough to suggest a correlation.
Conclusion
In conclusion, this study found that small venoarterial pH differences (ΔpH) were not associated with increased risk of mortality or morbidity related to organ system diagnoses. These findings suggest that while dual sampling of umbilical cord blood pH can be valuable for sample identification, it may have limited utility in predicting long-term clinical outcomes. Further research should therefore be directed to explore alternative markers, including refined uses of the UApH, for assessing fetal health and long-term risks using cord blood gases.
CRediT authorship contribution statement
Zaigham Mehreen: Writing – review & editing, Writing – original draft, Supervision, Conceptualization. Karin Källén: Writing – review & editing, Writing – original draft, Validation, Formal analysis, Data curation. Tiia-Marie Sundberg: Writing – review & editing, Writing – original draft, Investigation, Formal analysis, Conceptualization.
Ethics statement
All methods were carried out in accordance with relevant guidelines and regulations or Declaration of Helsinki. The study was approved by the Regional Ethics Committee in Lund, Dnrs 2009/222, 2012/5 and Dnr 2023–00434–02. The requirement for informed consent was waived by Regional Ethics Committee in Lund since the study was retrospective and population-based by design.
Funding
The study was financed by grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (YF00033 M.Z.) and a doctoral student scholarship from the Southern Health care region (Liy110 T-M.S.). The grants applications were peer reviewed for scientific quality. The funding organization had no role in the design of the study; collection, management, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data availability
The data and materials are according to the Ethical approval from the Swedish Ethical Review Authority not publicly available, but the authors can upon request provide data and materials.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data and materials are according to the Ethical approval from the Swedish Ethical Review Authority not publicly available, but the authors can upon request provide data and materials.