Effect of blood sampling management on reducing blood transfusions in very preterm infants : Chinese Medical Journal

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Effect of blood sampling management on reducing blood transfusions in very preterm infants

Pei, Jingjun1; Tang, Jun1,2; Hu, Yanling1; Wan, Xingli1; Shi, Jing1; Wang, Hua1; Chen, Qiong1; Li, Xiaowen1; Chen, Jian3; Chen, Chao1; Chen, Hongju1; Ying, Junjie2; Mu, Dezhi1,2

Editor(s): Ni, Jing

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Chinese Medical Journal ():10.1097/CM9.0000000000002596, April 14, 2023. | DOI: 10.1097/CM9.0000000000002596

To the Editor: Unstable clinical conditions and complications make multiple laboratory tests and blood sampling inevitable in preterm infants, contributing to iatrogenic blood loss. Undoubtedly, iatrogenic blood loss is highly correlated with red blood cell transfusion (RBCT). A previous study on extremely low birth weight (BW) infants reported that the sampling blood loss was 30.0 mL/kg within the first week of life, leading to one or more RBCTs in 98% of patients.[1] RBCTs are increasingly reported to cause inflammatory responses and increase the incidence of preterm complications. Therefore, reducing iatrogenic blood loss could not only decrease the need for transfusions but also reduce the risk of neonatal mortality and morbidity.

However, clinicians are not sufficiently aware of the risks of frequent sampling. Few studies reported detailed information on sampling blood loss of premature infants during hospitalization and its correlation with gestational age (GA) in preterm infants. Existing measures to reduce sampling blood loss, including staff education, smaller sampling vessels, closed blood sampling devices, and point-of-care testing, have been applied to adults and children in intensive care units (ICUs).[2] However, these measures have not been widely implemented in neonatal ICUs (NICUs). Therefore, we conducted a prospective cohort study on the quality management of blood sampling with historical controls, to evaluate sampling blood loss during hospitalization and clarify whether blood sampling management is beneficial for reducing RBCT in preterm infants.

Infants with a GA < 32 weeks in the NICU of our institution were enrolled. All patients were admitted to the hospital within 24 h after birth. Neonates with cyanotic congenital heart disease, genetic and metabolic diseases, severe congenital malformations, treatment discontinuation, or lacking complete clinical data were excluded, as well as newborns who died or were transferred within 14 days of hospitalization. This study protocol was reviewed and approved by the Ethics Committee of West China Second Hospital of Sichuan University, approval number [2021088]. All study subjects had signed informed consent.

We carried out blood sampling management according to the steps of the Quality Control Circle. In addition, based on the current investigation, the following measures were implemented: (1) educational intervention for the medical staff, such as requiring attending physicians to master the indications of each sampling test and sampling technology training for nursing personnel; (2) starting a standardized sampling table and strictly controlling each sampling volume defined by the minimum volume for each test; (3) sampling from the umbilical cord at birth for partial examinations; (4) using micro-blood sampling technology and bedside biochemical tests; and (5) using one sample for multiple tests.

The sampling and RBCT volumes were expressed in mL/kg of the BW. All data analyses were descriptive and conducted using Excel (IBM, Inc., Chicago, IL, USA) and SPSS v24.0 (SPSS, Inc., Chicago, Illinois, USA). A P value of 0.05 was used to determine the statistical significance. The estimated sample size was 328 cases by using PASS 2021 software (NCSS, Kaysville, USA). Linear regression assessed the relationship between the sampling blood loss and cumulative RBCT volumes. In addition, we conducted a binary logistic regression analysis to explore the effect of sampling blood loss and the number of RBCTs on preterm complications, such as necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), and intra-ventricular hemorrhage (IVH).

A total of 560 preterm infants were enrolled in this study: 284 infants in the group before sampling management and 276 infants in the group after blood collection management. The clinical characteristics were similar before and after sampling management [Supplementary Table 1, https://links.lww.com/CM9/B429]. The mortality rate was also similar between the two groups (before:1.1% [3/284]; after: 0.7% [2/276]).

After starting sampling management, the number of samples and sampling blood loss volume were considerably reduced. The total sampling blood loss decreased by 35.3 mL/kg (before: 17.0 mL/kg; after 11.0 mL/kg; P < 0.001) in infants with a GA of ≥28 and <32 weeks and by 38.6 mL/kg (before: 53.9 mL/kg; after: 33.1 mL/kg; P < 0.001) in infants with a GA of <28 weeks[Table 1].

Table 1 - Change in blood sampling and RBCTs among very preterm infants before and after blood sampling management.
Blood sampling RBCT

GA Vairables Before management (n = 284) After management (n = 276) Z P value Before management (n = 284) After management (n = 276) Z/χ 2 P value
28–32 Times
 On average during hospitalization 23 (14–31) 12 (9–22) −7.134 <0.001 0 (0–2) 0 (0–1) −1.553 0.120
 On the first day 2 (2–3) 2 (1–2) −6.909 <0.001
 Within 7 days 9 (7–11) 6 (4–7) −9.959 <0.001 38 (15.4) 19 (8.1) 6.319 0.012
 Within 28 days 18 (13–25) 11 (8–17) −8.537 <0.001 103 (41.9) 80 (33.9) 3.250 0.071
Volume (mL/kg)
Total 17.0 (9.7–27.0) 11.0 (7.1–22.0) −4.061 <0.001 0 (0–41.7) 0 (0–30.7) −1.384 0.167
On the first day 2.8 (2.0–4.0) 1.9 (1.4–2.6) −7.334 <0.001
Within 7 days 6.4 (4.3–9.6) 4.6 (3.1–6.9) −5.415 <0.001 0 (0–0) 0 (0–0) −2.373 0.018
Within 28 days 14.0 (8.4–23.0) 9.5 (6.6–18.0) −4.817 <0.001 0 (0–24.1) 0 (0–23.1) −1.360 0.174
<28 Times
 On average during hospitaliztion 58 (42–71) 27 (19–35) −6.020 <0.001 3.6 ± 2.3 2.4 ± 1.6 −2.238 0.025
 On the first day 2 (2–3) 2 (2–2) −1.946 0.052
 Within 7 days 12 (9–14) 7 (5–9) −5.904 <0.001 16 (42.1) 13 (32.5) 0.770 0.380
 Within 28 days 32 (27–39) 16 (13–22) −6.367 <0.001 31 (81.6) 31 (77.5) 0.199 0.656
Volume (mL/kg)
 Total 53.9 (35.4–77.1) 33.1 (23.7–47.5) −3.779 <0.001 89.1 (51.7–138.2) 73.2 (26.9–95.0) −2.160 0.031
 On the first day 2.8 (2.3–5.3) 2.4 (1.9–3.9) −1.355 0.176
 Within 7 days 11.6 (7.9–15.9) 8.4 (6.0–10.9) −2.604 0.009 0 (0–20) 0 (0–19.1) −1.118 0.263
 Within 28 days 29.7 (22.0–38.9) 21.1 (16.4–25.0) −3.369 0.001 38.9 (20.7–57.8) 26.3 (17.5–43.1) −0.954 0.340
Data are shown as median (interquartile), n (%) or mean ± standard deviation. Volume units is mL/kg.
According to the GA, infants were divided into two groups, one was with a GA from ≥28 weeks to <32 weeks and the other was with a GA of <28 weeks. GA: Gestational age; RBCT: Red blood cell transfusion.

A positive linear correlation between the total RBCT and sampling blood loss volumes before and after blood sampling management was demonstrated (before: r = 0.813, P < 0.001; after: r = 0.802, P < 0.001). When the sampling blood loss volume was <10 mL/kg, the RBCT rate was 1.7% (3/172); yet when the sampling blood loss volume was ≥30 mL/kg, the RBCT rate was 98.6% (138/140) [Supplementary Table 2, https://links.lww.com/CM9/B429]. The higher the sampling blood loss volume, the higher the RBCT rate. The total RBCT rate, number, and volume trended downward after starting management [Table 1].

Among all infants, the grades 1–2 IVH, 3–4 IVH, and NEC incidences were 23.8% (133/560), 4.1% (23/560), and 3.9% (22/560), respectively. After sampling management, grades 1–2 and 3–4 IVH incidences trended downward but the differences were insignificant. The NEC incidence did not increase after sampling management [Supplementary Table 3, https://links.lww.com/CM9/B429].

In preterm infants with a GA from ≥28 to <32 weeks, 24.0% (59/246) developed ROP (i.e., stages 1–5) before sampling management, and 11.4% (27/236) developed ROP after management; the ROP development rate was significantly reduced (P < 0.001). In preterm infants with a GA of <28 weeks, the ROP development rate before and after sampling management were 78.9% (30/38) and 62.5% (25/40), respectively; the ROP development rate insignificantly decreased. Only 1.6% (9/560) developed ROP progression (i.e., stages 3–5), and there was no difference in the ROP progression rate before and after sampling management [Supplementary Table 3, https://links.lww.com/CM9/B429].

In the binary logistic regression analysis, we included GA, BW, invasive respiratory support, bleeding, and infection as confounding factors. After excluding confounding factors, before sampling management, sampling blood loss (≥10 mL/kg) was a risk factor for ROP development (Odd ratio [OR], 3.098; 95% confidence interval [CI], 1.140–8.416; P = 0.027) in the early neonatal period. During the entire neonatal period, sampling blood loss (20–30 mL/kg) was a risk factor for ROP development (OR, 6.191; 95% CI, 1.494–26.555; P = 0.012). After management, sampling blood loss did not affect ROP development. Sampling blood loss did not affect ROP progression and no correlation was found between the number of RBCTs and ROP development or ROP progression.

In the present study, we identified that blood sampling management markedly reduced the number of samples and the sampling blood loss in infants with a GA of <32 weeks and the RBCT volume in the early neonatal period.

Sampling management had different effects on the RBCT of preterm infants with different GAs. The RBCT need was lower in preterm infants (≥28 and <32 weeks) than in extremely preterm infants (<28 weeks). The anemia may be more severe before the physiological phase of anemia, due to sampling blood loss. Thus, sampling management might reduce the anemia degree caused by iatrogenic blood loss and reduce the RBCT requirement at the early neonatal stage. The best way to minimize the RBCT risk for preterm infants is to reduce transfusion needs and decreasing laboratory blood sampling could be vital and effective.

Sampling blood loss showed potential for modifying the ROP risk. The exact reason remains unclear, but we speculate that this might be due to the blood volume fluctuation caused by frequent and repeated sampling, which may lead to frequent oxygenation fluctuation and short-term hypoxia and increase the effect of oxidative stress, accelerating ROP.[2] After sampling management, the sampling blood loss volume decreased, and no adverse effects on ROP were observed, indicating that a specific sampling blood loss volume is required to affect ROP. Sampling management also markedly reduced the ROP incidences. Thus, reducing sampling may be a simple and effective way to minimize ROP.

A prospective multi-center study in Turkey found that RBCT in preterm infants with a BW of <1500 g had a strong impact on the ROP progression (OR 2.384, P = 0.002).[3] And no correlation between RBCT and ROP development has been found,[3] which was consistent with our results. But no correlation between the number of RBCTs and ROP progression in this study. The reasons maybe as follows: firstly, comparing with Turkey's studies, the number of cases of ROP progression in this study was too small (9/560 vs. 414/6115); secondly, we analyzed the correlation between ROP and RBCT in the early and entire neonatal period, but the correlation between ROP and the RBCT during entire hospitalization was analyzed in Turkey; finally, the multi-center study in Turkey did not clearly indicate the indication of RBCTs, so it is unknown whether those multiple centers follow the same RBCT standard. At the same time, the speculated mechanisms were the free radical oxidative damage caused by iron overload and the rapidly increasing oxygen supply of the retina after RBCT.[3] ROP was related to hypoxia and the fluctuation of oxygen saturation.[2] However, the degree to which RBCT improves oxygen saturation and oxygen-carrying capacity is unclear. Further studies are needed to clarify the effect of RBCT on ROP in preterm infants.

The decision to sample is the clinicians, based on the clinical condition of the preterm infant. Clinicians must be aware of the indications for each examination and plan the timing of sampling for preterm infants. Reducing the required blood volume per test is also an issue to address in the future.

This study had limitations. This was a single-center study with limited information available, especially regarding preterm infants with a GA of <28 weeks. And other confounding factors should be considered, such as respiratory support and oxygen-related injury duration and the interaction among various indications.

In conclusion, blood sampling management reduced the sampling blood loss and RBCT volumes and might be associated with preterm complications. Therefore, more attention should be paid to the current blood sampling protocols in the NICU, and more effective measures should be taken to reduce sampling blood loss.


The authors would like to thank Dr. Junjie Ying and Dr. Yang He from the Key Laboratory of Birth Defects and Related Diseases of Women and Children for their contributions to data analysis. At the same time, thank Professor Youping Li from the West China Evidence-Based Center for her guidance on quality management scheme design.


The study was supported by a grant from the National Natural Science Foundation of China (Nos. 82271749 and 82171710).

Conflicts of interest



1. Puia-Dumitrescu M, Tanaka DT, Spears TG, Daniel CJ, Kumar KR, Athavale K, et al. Patterns of phlebotomy blood loss and transfusions in extremely low birth weight infants. J Perinatol 2019;39:1670–1675. doi: 10.1038/s41372-019-0515-6.
2. Das A, Mhanna M, Sears J, Houdek JW, Kumar N, Gunzler D, et al. Effect of fluctuation of oxygenation and time spent in the target range on retinopathy of prematurity in extremely low birth weight infants. J Neonatal Perinatal Med 2018;11:257–263. doi: 10.3233/NPM-1757.
3. Bas AY, Demirel N, Koc E, Ulubas Isik D, Hirfanoglu İM, Tunc T, et al. Incidence, risk factors and severity of retinopathy of prematurity in Turkey (TR-ROP study): a prospective, multicentre study in 69 neonatal intensive care units. Br J Ophthalmol 2018;102:1711–1716. doi: 10.1136/bjophthalmol-2017-311789.

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