CONTEXT:

Probiotics have proven to be effective in promoting premature infants’ health, but the optimal usage is unknown.

OBJECTIVE:

To compare probiotic supplements for premature infants.

DATA SOURCES:

We searched PubMed, Embase, Cochrane, and ProQuest from inception of these databases to June 1, 2020.

STUDY SELECTION:

Randomized trials of probiotic supplement intervention for preterm infants were screened by 2 reviewers independently. The primary outcomes were mortality and the morbidity of necrotizing enterocolitis (NEC). Secondary outcomes were morbidity of sepsis, time to achieve full enteral feeding, and length of hospital stay.

DATA EXTRACTION:

The data of primary and secondary outcomes were extracted by 2 reviewers and pooled with a random-effects model.

RESULTS:

The meta-analysis included 45 trials with 12 320 participants. Bifidobacterium plus Lactobacillus was associated with lower rates of mortality (risk ratio 0.56; 95% credible interval 0.34–0.84) and NEC morbidity (0.47; 0.27–0.79) in comparison to the placebo; Lactobacillus plus prebiotic was associated with lower rates of NEC morbidity (0.06; 0.01–0.41) in comparison to the placebo; Bifidobacterium plus prebiotic had the highest probability of having the lowest rate of mortality (surface under the cumulative ranking curve 83.94%); and Lactobacillus plus prebiotic had the highest probability of having the lowest rate of NEC (surface under the cumulative ranking curve 95.62%).

LIMITATIONS:

In few studies did authors report the data of infants with a lower birth weight or gestational age.

CONCLUSIONS:

The efficacy of single probiotic supplements is limited, compared to combined use of probiotics. To achieve optimal effect on premature infant health, combined use of prebiotic and probiotic, especially Lactobacillus or Bifidobacterium, is recommended.

Despite improvements in gestation management and health care, preterm birth remains a common but serious pregnancy outcome.1  Partly because of environmental factors and increasing in vitro fertilization in recent years, the prevalence of preterm birth ranges from 5% to 18% across 184 countries,2  and an estimated 15 million infants are born preterm globally.3  These infants with an immature immune system and gastrointestinal tract are at risk for complications of premature birth, which is the leading cause of neonatal death.4 

Recent studies suggest that the composition of infants’ gut microbiota is affected by birth weight and gestational age.5  Altered gut microbiota has proven to be an important factor putting infants at high risk of developing necrotizing enterocolitis (NEC) and sepsis, which may lead to death and lifelong physical impairment.6,7  It is evident that early probiotic supplementation may benefit premature infants by improving their gastrointestinal tolerance against potential pathogens and regulating the altered gut microbiota to resemble that of a term healthy infant.8,9 

Probiotic with or without prebiotic supplementation is a practicable method among nutrition interventions and may support gut microbiota colonization,10  growth, and long-term neurologic development in premature infants.11,12  Probiotic supplements in formula may regulate the stability and composition of premature infants’ gut microbiota.9  Recent studies13,14  and meta-analyses15,16  suggest that probiotic intervention has beneficial effects in premature infants, especially in reducing the mortality and morbidity of NEC and sepsis. Deshpande et al17  showed that probiotics could reduce the risk of late-onset sepsis and NEC when Bifidobacterium or Lactobacillus was part of the supplementation through a subgroup analysis in pairwise meta-analysis, but the result was restricted to low- and middle-income countries. However, previous pairwise meta-analysis only focused on efficacy but could not find the most effective intervention method. It is suggested that there are different effects when different strains or combinations are used.18  As numerous strains and preparations, including multistrains without given reasons, have been used in relevant trials, probiotic usage in infants needs to be regulated by more evidence. Previously published network meta-analyses in which authors compare the effect of different strains also have several shortcomings in their methodology or design. Because of the robust methodology in the systemic study search, in our study, we aimed to include a larger number of articles compared to another study that has similar scope and inclusion criteria.19  In addition, in our present network analysis, we tried to rank the efficacy of strains used by each intervention, which in a previous study, the authors failed to conduct the ranking and draw a clear conclusion.20  Thus, the authors of these studies did not point out which strain is an optimum option for infants’ health and failed to provide powerful evidence for clinical use of probiotics. In the current study, we examined the effect of probiotics in premature infants and figured out the optimal intervention through a network meta-analysis approach based on direct and indirect evidence from randomized controlled trials (RCTs).

This systematic review and Bayesian network meta-analysis was performed according to the guidelines from the Cochrane Neonatal Review Group (http://neonatal.cochrane.org/resources-review-authors) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statements.21,22  The protocol of this study was created and registered in the International Prospective Register of Systematic Reviews database, with registration CRD42016033063.

We searched for randomized trials in the Cochrane Collaboration Central Register of Controlled Trials, Medline/PubMed, and Embase using a combination of Medical Subject Headings (MeSH) and free text, from inception of these databases to June 1, 2020, with no language restrictions. To identify any unpublished studies, we searched degree theses in the ProQuest database. We also hand searched references of all included studies to identify review articles and related meta-analyses. Studies were identified with the following terms and their combinations: premature infant, low birth weight infant, probiotics, synbiotics (both as MeSH and free-text terms), and names of common probiotics (as free-text terms). Two researchers independently conducted the literature search and reviewed the titles, abstracts, and full-text articles to determine if they met the inclusion criteria. Any conflicts were resolved through discussion with a third author.

The population of interest was premature infants who were born with a birth weight of <2500 g or a gestational age <37 weeks. Probiotics or placebo was supplied to different groups allocated by randomization. Outcome variables included incidence of death, NEC, sepsis, time to achieve full enteral feeding, and length of hospital stay. Only RCTs in which authors compared at least two interventions or one intervention with placebo matched the eligible trial design. In addition, studies were included if the authors compared probiotic interventions with nystatin, which could act as an intermediate variable in further indirect comparisons.

Our primary outcomes were all-cause mortality and the morbidity of NEC, which was defined as cases that had reached Bell stage 2 or higher, thereby excluding mild and doubtful cases. Secondary outcomes were morbidity of sepsis, time to achieve full enteral feeding, and length of hospital stay. If a single trial included multiarms, the data of each arm were extracted and included in further analysis. Data were extracted directly from the articles by two independent authors using a standardized form. Disagreements were resolved by consensus, if needed, with a third author.

First, we performed pairwise meta-analyses with R software (version 3.5.1). We conducted random-effects model meta-analyses to obtain effect sizes for primary and secondary outcomes and presented dichotomous outcomes as risk ratio (RR) and continuous outcomes as standardized mean difference with 95% confidence interval (CI) separately.

Second, we performed random-effects network meta-analyses of dichotomous outcomes, including mortality, morbidity of NEC, and sepsis, using a Bayesian framework with Markov chain Monte Carlo methods in Just Another Gibbs Sampler (version 4.3.0) and R software. Trials in which authors used the same intervention were merged into nodes weighted by participants, and the edges between nodes represented the direct comparison between the two interventions. The network meta-analysis of the continuous outcome, namely, time to full enteral feeding, was also performed in a Bayesian framework by using Generate Mixed Treatment Comparisons (version 0.14.3). All analyses were run on four chains with 20 000 iterations per chain, including a burn-in period of 1000 runs. We used surface under the cumulative ranking curve (SUCRA) probabilities to rank the interventions for an outcome. The SUCRA probability of each intervention was expressed as a percentage of the efficacy of the intervention relative to an imaginary intervention that always turned out to be the best method.23  The larger the surface under the curve, the better the rank of the intervention. We used principal coordinate analysis (PCoA) based on SUCRA values to display the overall ranking distribution across the five parameters via dimension reduction. Inconsistency between direct and indirect evidence, which could lead to inconsistency of the model, was assessed by the node splitting method and inconsistency plot performed with Stata (Stata Corp, College Station, TX).24  The Cochrane risk-of-bias tool for RCTs25  was used to assess the risk of bias of the studies. Additionally, funnel plots were used to investigate signs of publication bias. A two-sided P value of <0.05 was regarded as statistically significant.

The initial search yielded 574 articles, and 113 potentially eligible articles were retrieved in full text and 45 eligible articles were included in the final analysis (Fig 1). These 45 RCTs were performed between 2002 and 2018 and compared 14 different interventions or placebo. In total, 12 320 participants were included in these trials and randomly allocated into intervention groups (n = 6577) and a placebo group (n = 5743). Samples were drawn from 19 different locations including America,2632  Asia,3346  Europe,8,4766  Africa,67  and Australia.68,69  Most RCTs included a comparison of 2 arms (n = 41), but some included 3 (n = 3) or 4 (n = 1) arms. The duration of treatment varied from 2 to 9 weeks or covered the infant’s hospitalization. Baseline parameters, including gestational age, birth weight, sex, and sample size, were similar across all the arms of the same study (Table 1).

FIGURE 1

Flowchart. Flowchart of study selection.

FIGURE 1

Flowchart. Flowchart of study selection.

Close modal
TABLE 1

Characteristics of Included Studies

Study (y)No. ParticipantsDesignLocationInclusion CriterionOutcomesArms, nTreatmentNo. RandomizedGestational Age, Mean (SD)Birth Wt, Mean (SD)Male, nTreatment Duration, wkDosage, CFUTimes per d
Al-Hosni et al26  (2012) 101 SB United States LBW 1,2,3 Placebo 51 25.7 (1.4) 779 (126) 22 5 × 109 
       Lactobacillus 50 25.7 (1.4) 778 (138) 28 5 × 109 
Bin-Nun et al47  (2005) 145 DB Israel LBW 1,2,3,4 Placebo 73 29.3 (4.3) 1111 (278) 37 1.1 × 109 
       BST 72 29.8 (2.6) 1152 (262) 44 1.1 × 109 
Braga et al27  (2011) 231 DB Brazil LBW 1,2,3,4 Placebo 112 29.5 (2.5) 1151 (225) 55 3.5 × 109 
       BL 119 29.2 (2.6) 1195 (206) 58 3.5 × 109 
Chowdhury et al33  (2016) 102 DB Bangladesh LBW, PTB 2,4 Placebo 50 31.68 (0.84) 1338 (98) 36 3 × 109 
       BLP 52 31.38 (0.93) 1312 (110) 33 3 × 109 
Costalos et al48  (2003) 87 DB Greece PTB 2,3 Placebo 36 31.8 (2.7) 1644 (378) 23 Until discharge 1 × 109 
       Saccharomyces 51 31.1 (2.5) 1651 (470) 24 Until discharge 1 × 109 
Costeloe et al8  (2016) 1310 DB England PTB 1,2,3,4,5 Placebo 660 28 (2.59) 1043 (317) 374 Until discharge 8.5 × 108 
       Bifidobacterium 650 28 (2.44) 1039 (312) 370 Until discharge 8.5 × 108 
Dani et al49  (2002) 385 SB Italy LBW, PTB 2,3 Placebo 290 30.7 (2.3) 1345 (384) 151 6 × 109 
       Lactobacillus 295 30.8 (2.4) 1325 (361) 135 6 × 109 
Demirel et al50  (2013) 181 SB Turkey LBW, PTB 1,2 Nystatin 90 28.4 (2.6) 1057 (290) 50 Until discharge 5 × 1010 
       Saccharomyces 91 29 (2.7) 1135 (253) 45 Until discharge 5 × 1010 
Demirel et al51  (2013) 271 DB Turkey LBW, PTB 1,2,3,4,5 Placebo 136 29.2 (2.5) 1131 (284) 66 Until discharge 5 × 109 
       Saccharomyces 135 29.4 (2.3) 1164 (261) 69 Until discharge 5 × 109 
Dilli et al52  (2015) 300 DB Turkey LBW, PTB 1,2,3,4,5 Placebo 100 28.2 (2.2) 1147 (271) 58 Until discharge 5 × 109 
       BP 100 28.9 (1.9) 1205 (240) 57 Until discharge 5 × 109 
       Bifidobacterium 100 28.2 (2.2) 1147 (271) 58 Until discharge 5 × 109 
Dutta et al34  (2015) 149 DB India PTB 1,2,3 Placebo 35 30.82 (1.72) 1252 (309) 23 1 × 1010 
       BLSA 114 30.87 (1.73) 1345 (284) 68 1 × 1010 
Fernández-Carrocera et al28  (2013) 150 DB Mexico PTB 1,2,4,5 Placebo 75 31 (1.5) 1170 (159) — 2 × 109 
       BLST 75 35.2 (0.9) 1090 (153) — 2 × 109 
Güney-Varal et al64  (2017) 110 SB Turkey LBW, PTB 1,2,3,4 Placebo 40 29.3 (1.7) 1228 (249) 19 Until discharge 2 × 109 
       BL 70 29.7 (1.9) 1729 (257) 45 Until discharge 2 × 109 
Havranek et al29  (2013) 31 DB United States PTB 3,4 Placebo 16 25.9 (1.5) 789 (129) 10 Until discharge 1 × 1010 
       BL 15 25.9 (1.3) 856 (105) Until discharge 1×1010 
Hays et al,53 B. lactis (2016) 102 DB France LBW, PTB 1,2 Placebo 52 29.4 (2) 1170 (233) 35 4–6 1 × 109 
       Bifidobacterium 50 29 (1.5) 1170 (237) 23 4–6 1 × 109 
Hays et al,53 B. longum (2016) 100 DB France LBW, PTB 1,2 Placebo 52 29.4 (2) 1170 (233) 35 4–6 1 × 109 
       Bifidobacterium 48 29 (1.5) 1170 (237) 22 4–6 1 × 109 
Hays et al,53 B. lactis and B. longum (2016) 99 DB France LBW, PTB 1,2 Placebo 52 29.4 (2) 1170 (233) 35 4–6 1 × 109 
       Bifidobacterium 47 29 (1.5) 1170 (237) 22 4–6 1 × 109 
Indrio et al65  (2017) 60 DB Italy PTB 3,4,5 Placebo 30 30.1 (1.2) 1407 (536) 16 1 × 108 
       Lactobacillus 30 30.2 (1.2) 1472 (455) 15 1 × 108 
Jacobs et al68  (2013) 1099 DB Australia LBW, PTB 1,2,3,4,5 Placebo 551 27.8 (2) 1048 (260) 300 Until discharge 1 × 109 
       BST 548 27.9 (2) 1063 (259) 272 Until discharge 1 × 109 
Kanic et al54  (2015) 80 SB Slovenia LBW 1,2,3,5 Placebo 40 29 (2.82) 1024 (250) 27 Until discharge 1.2 × 107 
       BLE 40 28 (2.22) 1104 (233) 22 Until discharge 1.2 × 107 
Lin et al35  (2008) 434 DB China LBW, PTB 1,2,3,5 Placebo 217 — 1077 (214) 115 2 × 109 
       BL 217 — 1029 (246) 122 2 × 109 
Lin et al36  (2005) 367 DB China LBW 1,2,3,5 Placebo 187 28.2 (2.5) 1071 (243) 100 Until discharge 2 × 109 
       BL 180 28.5 (2.5) 1104 (242) 84 Until discharge 2 × 109 
Manzoni et al55  (2006) 80 DB Italy LBW 1,2,3,4,5 Placebo 41 29.3 (4) 1174 (340) 21 6 × 109 
       Lactobacillus 39 29.6 (5) 1212 (290) 20 6 × 109 
Manzoni et al56  (2009) 358 DB Italy LBW 1,2,3,4 Placebo 168 29.8 (2.8) 1109 (269) 86 Until discharge 6 × 109 
       Lactobacillus 39 29.6 (5) 1212 (290) 20 Until discharge 6 × 109 
       LP 151 29.5 (3.2) 1138 (253) 72 Until discharge 6 × 109 
Mihatsch et al57  (2010) 180 DB Germany PTB 2,3,4 Placebo 89 26.7 (1.7) 871 (287) 47 Until discharge 2 × 1010 
       Bifidobacterium 91 26.6 (1.8) 856 (251) 55 Until discharge 2 × 1010 
Nandhini et al37  (2016) 218 SB India LBW, PTB 1,2,3,5 Placebo 110 31.4 (1.4) 1444 (217) — Until discharge 3 × 109 
       BLP 108 31.6 (1.4) 1430 (209) — Until discharge 3 × 109 
Oncel et al58  (2015) 300 DB Turkey LBW, PTB 1,2,3,4,5 Nystatin 150 27.7 (2.5) 1051 (320) 75 Until discharge 1 × 108 
       Lactobacillus 150 28.1 (2.4) 1058 (270) 82 Until discharge 1 × 108 
Oncel et al59  (2014) 400 DB Turkey LBW, PTB 1,2,3,5 Placebo 200 27.9 (2.5) 1048 (298) 98 Until discharge 1 × 108 
       Lactobacillus 200 28.2 (2.4) 1071 (274) 108 Until discharge 1 × 108 
Patole et al69  (2014) 153 DB Australia LBW, PTB 2,3,4,5 Placebo 76 28 (1.67) 1025 (215) 41 3 × 109 
       Bifidobacterium 77 29 (1.5) 1090 (227) 41 3 × 109 
Qiao et al38  (2017) 60 DB China PTB 1,2,3 Placebo 30 32.1 (1.9) 1532 (412) 16 Until discharge 1.5 × 108 
       BLE 30 32.4 (1.6) 1653 (476) 17 Until discharge 1.5 × 108 
Rojas et al32  (2012) 750 DB Colombia LBW 1,2,3,5 Placebo 378 32 (2.96) 1516 (460) 185 Until discharge 1 × 108 
       Lactobacillus 372 32 (2.22) 1530 (368) 186 Until discharge 1 × 108 
Rougé et al66  (2009) 94 DB France LBW, PTB 1,2,3,5 Placebo 49 28.1 (1.8) 1057 (260) 26 Until discharge 1 × 108 
       BL 45 28.1 (1.9) 1115 (251) 28 Until discharge 1 × 108 
Roy et al39  (2014) 112 DB India LBW, PTB 1,2,3,4,5 Placebo 56 32.2 (2) 1069 (365) 16 Until discharge 6 × 109 
       BL 56 32 (2) 1192 (341) 14 Until discharge 6 × 109 
Saengtawesin et al40  (2014) 60 SB Thailand LBW, PTB 1,2,3,4,5 Placebo 29 30.59 (1.76) 1208 (199) 11 2 × 109 
       BL 31 31 (1.82) 1250 (179) 19 2 × 109 
Samanta et al41  (2009) 186 DB India LBW, PTB 1,2,3,4,5 Placebo 95 30.14 (1.59) 1210 (143) — Until discharge 2.5 × 109 
       BL 91 30.12 (1.63) 1172 (143) — Until discharge 2.5 × 109 
Sari et al60  (2011) 221 DB Turkey LBW, PTB 1,2,3,4,5 Placebo 111 29.7 (2.4) 1278 (282) 62 Until discharge 3.5 × 108 
       Lactobacillus 110 29.5 (2.4) 1231 (262) 60 Until discharge 3.5 × 108 
Serce et al61  (2013) 208 DB Turkey LBW, PTB 1,2,3,4,5 Placebo 104 28.7 (2.1) 1162 (216) 56 Until discharge 5 × 108 
       Saccharomyces 104 28.8 (2.2) 1126 (232) 51 Until discharge 5 × 108 
Shashidhar et al45  (2017) 104 DB India LBW 1,2,4,5 Placebo 52 31 (2.1) 1190 (208) 20 Until discharge 1.3 × 109 
       BLSA 52 31.2 (2.1) 1256 (185) 27 Until discharge 1.3 × 109 
Sinha et al46  (2015) 1340 DB India LBW 1,3 Placebo 672 — 2263 (179) 320 1 × 1011 
       BLST 668 — 2261 (179) 319 1 × 1011 
Stratiki et al62  (2007) 75 DB Greece PTB 2,3,4 Placebo 34 30.5 (8.15) 1500 (889) 17 Until discharge 2 × 107 12 
       Bifidobacterium 41 31 (7.41) 1500 (652) 23 Until discharge 2 × 107 12 
Tewari et al42  (2015) 244 DB India PTB 1,2,3,5 Placebo 121 30 (3) 1322 (398) 58 Until discharge 2 × 109 
       Bacillus 123 30 (3) 1313 (414) 62 Until discharge 2 × 109 
Totsu et al43  (2014) 283 DB Japan LBW 1,2,3,5 Placebo 130 28.5 (3.3) 998 (281) 71 Reach 2000 g 2.5 × 109 
       Bifidobacterium 153 28.6 (2.9) 1016 (289) 87 Reach 2000 g 2.5 × 109 
Underwood et al31  (2009) 89 SB United States LBW, PTB 2,4 Placebo 29 29.3 (2.6) 1363 (363) 19 5 × 108 
       LP 30 29.5 (2.6) 1394 (365) 21 5 × 108 
       BLP 30 29.5 (2.6) 1394 (365) 21 5 × 108 
Van Niekerk et al67  (2015) 110 DB South Africa LBW 2,3,4 Placebo 56 29 (3) 1215 (189) 24 3.5 × 108 
       BL 54 29 (4) 1258 (201) 29 3.5 × 108 
Wejryd et al63  (2018) 134 DB Sweden LBW, PTB 1,2,3,4 Placebo 66 25.5 (1.3) 740 (148) 42 Reach 2000 g 1.3 × 108 
       Lactobacillus 68 25.5 (1.2) 731 (129) 32 Reach 2000 g 1.3 × 108 
Xu et al44  (2016) 125 SB China LBW, PTB 3,5 Placebo 63 33 (1.41) 1957 (51) 24 1 × 109 
       Saccharomyces 62 33 (0.72) 1947 (54) 27 1 × 109 
Study (y)No. ParticipantsDesignLocationInclusion CriterionOutcomesArms, nTreatmentNo. RandomizedGestational Age, Mean (SD)Birth Wt, Mean (SD)Male, nTreatment Duration, wkDosage, CFUTimes per d
Al-Hosni et al26  (2012) 101 SB United States LBW 1,2,3 Placebo 51 25.7 (1.4) 779 (126) 22 5 × 109 
       Lactobacillus 50 25.7 (1.4) 778 (138) 28 5 × 109 
Bin-Nun et al47  (2005) 145 DB Israel LBW 1,2,3,4 Placebo 73 29.3 (4.3) 1111 (278) 37 1.1 × 109 
       BST 72 29.8 (2.6) 1152 (262) 44 1.1 × 109 
Braga et al27  (2011) 231 DB Brazil LBW 1,2,3,4 Placebo 112 29.5 (2.5) 1151 (225) 55 3.5 × 109 
       BL 119 29.2 (2.6) 1195 (206) 58 3.5 × 109 
Chowdhury et al33  (2016) 102 DB Bangladesh LBW, PTB 2,4 Placebo 50 31.68 (0.84) 1338 (98) 36 3 × 109 
       BLP 52 31.38 (0.93) 1312 (110) 33 3 × 109 
Costalos et al48  (2003) 87 DB Greece PTB 2,3 Placebo 36 31.8 (2.7) 1644 (378) 23 Until discharge 1 × 109 
       Saccharomyces 51 31.1 (2.5) 1651 (470) 24 Until discharge 1 × 109 
Costeloe et al8  (2016) 1310 DB England PTB 1,2,3,4,5 Placebo 660 28 (2.59) 1043 (317) 374 Until discharge 8.5 × 108 
       Bifidobacterium 650 28 (2.44) 1039 (312) 370 Until discharge 8.5 × 108 
Dani et al49  (2002) 385 SB Italy LBW, PTB 2,3 Placebo 290 30.7 (2.3) 1345 (384) 151 6 × 109 
       Lactobacillus 295 30.8 (2.4) 1325 (361) 135 6 × 109 
Demirel et al50  (2013) 181 SB Turkey LBW, PTB 1,2 Nystatin 90 28.4 (2.6) 1057 (290) 50 Until discharge 5 × 1010 
       Saccharomyces 91 29 (2.7) 1135 (253) 45 Until discharge 5 × 1010 
Demirel et al51  (2013) 271 DB Turkey LBW, PTB 1,2,3,4,5 Placebo 136 29.2 (2.5) 1131 (284) 66 Until discharge 5 × 109 
       Saccharomyces 135 29.4 (2.3) 1164 (261) 69 Until discharge 5 × 109 
Dilli et al52  (2015) 300 DB Turkey LBW, PTB 1,2,3,4,5 Placebo 100 28.2 (2.2) 1147 (271) 58 Until discharge 5 × 109 
       BP 100 28.9 (1.9) 1205 (240) 57 Until discharge 5 × 109 
       Bifidobacterium 100 28.2 (2.2) 1147 (271) 58 Until discharge 5 × 109 
Dutta et al34  (2015) 149 DB India PTB 1,2,3 Placebo 35 30.82 (1.72) 1252 (309) 23 1 × 1010 
       BLSA 114 30.87 (1.73) 1345 (284) 68 1 × 1010 
Fernández-Carrocera et al28  (2013) 150 DB Mexico PTB 1,2,4,5 Placebo 75 31 (1.5) 1170 (159) — 2 × 109 
       BLST 75 35.2 (0.9) 1090 (153) — 2 × 109 
Güney-Varal et al64  (2017) 110 SB Turkey LBW, PTB 1,2,3,4 Placebo 40 29.3 (1.7) 1228 (249) 19 Until discharge 2 × 109 
       BL 70 29.7 (1.9) 1729 (257) 45 Until discharge 2 × 109 
Havranek et al29  (2013) 31 DB United States PTB 3,4 Placebo 16 25.9 (1.5) 789 (129) 10 Until discharge 1 × 1010 
       BL 15 25.9 (1.3) 856 (105) Until discharge 1×1010 
Hays et al,53 B. lactis (2016) 102 DB France LBW, PTB 1,2 Placebo 52 29.4 (2) 1170 (233) 35 4–6 1 × 109 
       Bifidobacterium 50 29 (1.5) 1170 (237) 23 4–6 1 × 109 
Hays et al,53 B. longum (2016) 100 DB France LBW, PTB 1,2 Placebo 52 29.4 (2) 1170 (233) 35 4–6 1 × 109 
       Bifidobacterium 48 29 (1.5) 1170 (237) 22 4–6 1 × 109 
Hays et al,53 B. lactis and B. longum (2016) 99 DB France LBW, PTB 1,2 Placebo 52 29.4 (2) 1170 (233) 35 4–6 1 × 109 
       Bifidobacterium 47 29 (1.5) 1170 (237) 22 4–6 1 × 109 
Indrio et al65  (2017) 60 DB Italy PTB 3,4,5 Placebo 30 30.1 (1.2) 1407 (536) 16 1 × 108 
       Lactobacillus 30 30.2 (1.2) 1472 (455) 15 1 × 108 
Jacobs et al68  (2013) 1099 DB Australia LBW, PTB 1,2,3,4,5 Placebo 551 27.8 (2) 1048 (260) 300 Until discharge 1 × 109 
       BST 548 27.9 (2) 1063 (259) 272 Until discharge 1 × 109 
Kanic et al54  (2015) 80 SB Slovenia LBW 1,2,3,5 Placebo 40 29 (2.82) 1024 (250) 27 Until discharge 1.2 × 107 
       BLE 40 28 (2.22) 1104 (233) 22 Until discharge 1.2 × 107 
Lin et al35  (2008) 434 DB China LBW, PTB 1,2,3,5 Placebo 217 — 1077 (214) 115 2 × 109 
       BL 217 — 1029 (246) 122 2 × 109 
Lin et al36  (2005) 367 DB China LBW 1,2,3,5 Placebo 187 28.2 (2.5) 1071 (243) 100 Until discharge 2 × 109 
       BL 180 28.5 (2.5) 1104 (242) 84 Until discharge 2 × 109 
Manzoni et al55  (2006) 80 DB Italy LBW 1,2,3,4,5 Placebo 41 29.3 (4) 1174 (340) 21 6 × 109 
       Lactobacillus 39 29.6 (5) 1212 (290) 20 6 × 109 
Manzoni et al56  (2009) 358 DB Italy LBW 1,2,3,4 Placebo 168 29.8 (2.8) 1109 (269) 86 Until discharge 6 × 109 
       Lactobacillus 39 29.6 (5) 1212 (290) 20 Until discharge 6 × 109 
       LP 151 29.5 (3.2) 1138 (253) 72 Until discharge 6 × 109 
Mihatsch et al57  (2010) 180 DB Germany PTB 2,3,4 Placebo 89 26.7 (1.7) 871 (287) 47 Until discharge 2 × 1010 
       Bifidobacterium 91 26.6 (1.8) 856 (251) 55 Until discharge 2 × 1010 
Nandhini et al37  (2016) 218 SB India LBW, PTB 1,2,3,5 Placebo 110 31.4 (1.4) 1444 (217) — Until discharge 3 × 109 
       BLP 108 31.6 (1.4) 1430 (209) — Until discharge 3 × 109 
Oncel et al58  (2015) 300 DB Turkey LBW, PTB 1,2,3,4,5 Nystatin 150 27.7 (2.5) 1051 (320) 75 Until discharge 1 × 108 
       Lactobacillus 150 28.1 (2.4) 1058 (270) 82 Until discharge 1 × 108 
Oncel et al59  (2014) 400 DB Turkey LBW, PTB 1,2,3,5 Placebo 200 27.9 (2.5) 1048 (298) 98 Until discharge 1 × 108 
       Lactobacillus 200 28.2 (2.4) 1071 (274) 108 Until discharge 1 × 108 
Patole et al69  (2014) 153 DB Australia LBW, PTB 2,3,4,5 Placebo 76 28 (1.67) 1025 (215) 41 3 × 109 
       Bifidobacterium 77 29 (1.5) 1090 (227) 41 3 × 109 
Qiao et al38  (2017) 60 DB China PTB 1,2,3 Placebo 30 32.1 (1.9) 1532 (412) 16 Until discharge 1.5 × 108 
       BLE 30 32.4 (1.6) 1653 (476) 17 Until discharge 1.5 × 108 
Rojas et al32  (2012) 750 DB Colombia LBW 1,2,3,5 Placebo 378 32 (2.96) 1516 (460) 185 Until discharge 1 × 108 
       Lactobacillus 372 32 (2.22) 1530 (368) 186 Until discharge 1 × 108 
Rougé et al66  (2009) 94 DB France LBW, PTB 1,2,3,5 Placebo 49 28.1 (1.8) 1057 (260) 26 Until discharge 1 × 108 
       BL 45 28.1 (1.9) 1115 (251) 28 Until discharge 1 × 108 
Roy et al39  (2014) 112 DB India LBW, PTB 1,2,3,4,5 Placebo 56 32.2 (2) 1069 (365) 16 Until discharge 6 × 109 
       BL 56 32 (2) 1192 (341) 14 Until discharge 6 × 109 
Saengtawesin et al40  (2014) 60 SB Thailand LBW, PTB 1,2,3,4,5 Placebo 29 30.59 (1.76) 1208 (199) 11 2 × 109 
       BL 31 31 (1.82) 1250 (179) 19 2 × 109 
Samanta et al41  (2009) 186 DB India LBW, PTB 1,2,3,4,5 Placebo 95 30.14 (1.59) 1210 (143) — Until discharge 2.5 × 109 
       BL 91 30.12 (1.63) 1172 (143) — Until discharge 2.5 × 109 
Sari et al60  (2011) 221 DB Turkey LBW, PTB 1,2,3,4,5 Placebo 111 29.7 (2.4) 1278 (282) 62 Until discharge 3.5 × 108 
       Lactobacillus 110 29.5 (2.4) 1231 (262) 60 Until discharge 3.5 × 108 
Serce et al61  (2013) 208 DB Turkey LBW, PTB 1,2,3,4,5 Placebo 104 28.7 (2.1) 1162 (216) 56 Until discharge 5 × 108 
       Saccharomyces 104 28.8 (2.2) 1126 (232) 51 Until discharge 5 × 108 
Shashidhar et al45  (2017) 104 DB India LBW 1,2,4,5 Placebo 52 31 (2.1) 1190 (208) 20 Until discharge 1.3 × 109 
       BLSA 52 31.2 (2.1) 1256 (185) 27 Until discharge 1.3 × 109 
Sinha et al46  (2015) 1340 DB India LBW 1,3 Placebo 672 — 2263 (179) 320 1 × 1011 
       BLST 668 — 2261 (179) 319 1 × 1011 
Stratiki et al62  (2007) 75 DB Greece PTB 2,3,4 Placebo 34 30.5 (8.15) 1500 (889) 17 Until discharge 2 × 107 12 
       Bifidobacterium 41 31 (7.41) 1500 (652) 23 Until discharge 2 × 107 12 
Tewari et al42  (2015) 244 DB India PTB 1,2,3,5 Placebo 121 30 (3) 1322 (398) 58 Until discharge 2 × 109 
       Bacillus 123 30 (3) 1313 (414) 62 Until discharge 2 × 109 
Totsu et al43  (2014) 283 DB Japan LBW 1,2,3,5 Placebo 130 28.5 (3.3) 998 (281) 71 Reach 2000 g 2.5 × 109 
       Bifidobacterium 153 28.6 (2.9) 1016 (289) 87 Reach 2000 g 2.5 × 109 
Underwood et al31  (2009) 89 SB United States LBW, PTB 2,4 Placebo 29 29.3 (2.6) 1363 (363) 19 5 × 108 
       LP 30 29.5 (2.6) 1394 (365) 21 5 × 108 
       BLP 30 29.5 (2.6) 1394 (365) 21 5 × 108 
Van Niekerk et al67  (2015) 110 DB South Africa LBW 2,3,4 Placebo 56 29 (3) 1215 (189) 24 3.5 × 108 
       BL 54 29 (4) 1258 (201) 29 3.5 × 108 
Wejryd et al63  (2018) 134 DB Sweden LBW, PTB 1,2,3,4 Placebo 66 25.5 (1.3) 740 (148) 42 Reach 2000 g 1.3 × 108 
       Lactobacillus 68 25.5 (1.2) 731 (129) 32 Reach 2000 g 1.3 × 108 
Xu et al44  (2016) 125 SB China LBW, PTB 3,5 Placebo 63 33 (1.41) 1957 (51) 24 1 × 109 
       Saccharomyces 62 33 (0.72) 1947 (54) 27 1 × 109 

Continuous variables were represented as mean (SD). BL, Bifidobacterium + Lactobacillus; BLE, Bifidobacterium + Lactobacillus + Enterococcus; BLP, Bifidobacterium + Lactobacillus + prebiotic; BLSA, Bifidobacterium + Lactobacillus + Saccharomyces; BLST, Bifidobacterium + Lactobacillus + Streptococcus; BP, Bifidobacterium + prebiotic; BST, Bifidobacterium + Streptococcus; CFU, colony-forming unit; DB, double-blind; LBW, low birth weight; LP, Lactobacillus + prebiotic; PTB, preterm birth; SB, single-blind; 1, mortality; 2, NEC morbidity; 3, sepsis morbidity; 4, time to full enteral feeding; 5, length of hospital stay; —, not applicable.

In pairwise comparisons for the primary outcomes and secondary outcomes (Supplemental Fig 6), no evidence of statistical heterogeneity was seen in general. The pairwise meta-analysis revealed that Lactobacillus plus prebiotic, Bifidobacterium plus prebiotic, and Bifidobacterium plus Lactobacillus were associated with lower rates in comparison to the placebo for mortality and NEC morbidity. Lactobacillus plus prebiotic was superior to placebo in sepsis morbidity; Bifidobacterium plus prebiotic and Bifidobacterium plus Lactobacillus were superior to placebo in the time to full enteral feeding and length of hospital stay.

The networks of eligible comparisons for primary outcomes, including mortality and NEC morbidity, are shown in Fig 2. The network plots of secondary outcomes, including sepsis morbidity, time to full enteral feeding, and length of hospital stay, are provided in Supplemental Fig 7. These five network plots indicate that all the interventions (except nystatin) had at least one direct comparison with the placebo. The weight of each direct comparison, depending on the variance of observed effect and network structure, is presented in the contribution plots (Supplemental Fig 8).

FIGURE 2

Network graphs. Network of eligible comparisons for mortality (A) and NEC morbidity (B). The width of lines is proportional to the number of studies comparing every pair of interventions. The size of nodes is proportional to the number of participants assigned to receive the intervention.

FIGURE 2

Network graphs. Network of eligible comparisons for mortality (A) and NEC morbidity (B). The width of lines is proportional to the number of studies comparing every pair of interventions. The size of nodes is proportional to the number of participants assigned to receive the intervention.

Close modal

The results of each intervention compared to the placebo in the network meta-analysis are shown in Fig 3. In terms of primary outcomes, Bifidobacterium plus Lactobacillus was associated with lower rates of mortality (RR 0.56; 95% CI 0.34–0.84) and NEC morbidity (RR 0.47; 95% CI 0.27–0.79) than those of the placebo, and Lactobacillus plus prebiotic was associated with lower rates of NEC morbidity (RR 0.06; 95% CI 0.01–0.41) than those of the placebo. In terms of secondary outcomes, Lactobacillus plus prebiotic was associated with lower rates of sepsis morbidity (RR 0.18; 95% CI 0.06–0.44) than those of the placebo, and Bifidobacterium plus Lactobacillus led to a reduction of time to full enteral feeding (RR 3.97; 95% CI 1.65–5.74) and length of hospital stay (RR 7.30; 95% CI 0.99–14.13) compared to the placebo.

FIGURE 3

Forest plots. Shown are forest plots of network meta-analysis of all studies for mortality, NEC morbidity, sepsis morbidity, time to full enteral feeding, and length of hospital stay. Other interventions were compared to the placebo, which was the reference intervention. The circle in blue indicates significantly in favor of the comparator. BL, Bifidobacterium + Lactobacillus; BLE, Bifidobacterium + Lactobacillus + Enterococcus; BLP, Bifidobacterium + Lactobacillus + prebiotic; BLSA, Bifidobacterium + Lactobacillus + Saccharomyces; BLST, Bifidobacterium + Lactobacillus + Streptococcus; BP, Bifidobacterium + prebiotic; BST, Bifidobacterium + Streptococcus; CrI, credible interval; LP, Lactobacillus + prebiotic; MD, mean difference.

FIGURE 3

Forest plots. Shown are forest plots of network meta-analysis of all studies for mortality, NEC morbidity, sepsis morbidity, time to full enteral feeding, and length of hospital stay. Other interventions were compared to the placebo, which was the reference intervention. The circle in blue indicates significantly in favor of the comparator. BL, Bifidobacterium + Lactobacillus; BLE, Bifidobacterium + Lactobacillus + Enterococcus; BLP, Bifidobacterium + Lactobacillus + prebiotic; BLSA, Bifidobacterium + Lactobacillus + Saccharomyces; BLST, Bifidobacterium + Lactobacillus + Streptococcus; BP, Bifidobacterium + prebiotic; BST, Bifidobacterium + Streptococcus; CrI, credible interval; LP, Lactobacillus + prebiotic; MD, mean difference.

Close modal

Overall results of the network meta-analysis including pairwise comparisons of primary (Fig 4) and secondary (Supplemental Fig 9) outcomes between different interventions are presented in the league table. Lactobacillus plus prebiotic was associated with lower rates of NEC morbidity (RR 0.13; 95% CI 0.01–0.90) and sepsis morbidity (RR 0.21; 95% CI 0.07–0.53) than the rates associated with Bifidobacterium plus Lactobacillus. In terms of time to full enteral feeding, Lactobacillus plus prebiotic was superior to Bifidobacterium plus Lactobacillus (RR 4.84; 95% CI 1.90–13.63).

FIGURE 4

Efficacy of primary outcomes. Efficacy of interventions are displayed in a league table. Interventions are reported in alphabetical order. For the lower triangle (mortality) and upper triangle (NEC morbidity), results are the RRs (with 95% CI) in the column-defining treatment compared to the row-defining treatment. Significant results are shaded in a dark color. BL, Bifidobacterium + Lactobacillus; BLE, Bifidobacterium + Lactobacillus + Enterococcus; BLP, Bifidobacterium + Lactobacillus + prebiotic; BLSA, Bifidobacterium + Lactobacillus + Saccharomyces; BLST, Bifidobacterium + Lactobacillus + Streptococcus; BP, Bifidobacterium + prebiotic; BST, Bifidobacterium + Streptococcus; LP, Lactobacillus + prebiotic.

FIGURE 4

Efficacy of primary outcomes. Efficacy of interventions are displayed in a league table. Interventions are reported in alphabetical order. For the lower triangle (mortality) and upper triangle (NEC morbidity), results are the RRs (with 95% CI) in the column-defining treatment compared to the row-defining treatment. Significant results are shaded in a dark color. BL, Bifidobacterium + Lactobacillus; BLE, Bifidobacterium + Lactobacillus + Enterococcus; BLP, Bifidobacterium + Lactobacillus + prebiotic; BLSA, Bifidobacterium + Lactobacillus + Saccharomyces; BLST, Bifidobacterium + Lactobacillus + Streptococcus; BP, Bifidobacterium + prebiotic; BST, Bifidobacterium + Streptococcus; LP, Lactobacillus + prebiotic.

Close modal

Bayesian Markov chain Monte Carlo modeling revealed that Bifidobacterium plus prebiotic had the highest probability of having the lowest rate of mortality (SUCRA 83.94%; Fig 5A), followed by Lactobacillus plus prebiotic (SUCRA 79.69%) and Bifidobacterium plus Lactobacillus (SUCRA 73.81%). Lactobacillus plus prebiotic had the highest probability of having the lowest rates of NEC and sepsis (SUCRA 95.62% and 98.85%, respectively; Fig 5 B and C). Bifidobacterium plus Lactobacillus had the highest probability of being the most effective intervention in reducing the time to full enteral feeding (SUCRA 89.41%; Fig 5D) and the length of hospital stay (SUCRA 82.13%; Fig 5E). The five-dimensional graph containing all five parameters was dimension-reduced to a two-dimensional graph by using the PCoA method. This graph was generated to show the efficacy of different interventions of probiotics in alleviating the mortality, NEC morbidity, and sepsis morbidity, as well as reducing the time to full enteral feeding and length of hospital stay (Fig 5F). In this cluster rank plot, the placebo is located in the bottom right, whereas the 3 interventions are located in the top left, including Bifidobacterium plus Lactobacillus, Bifidobacterium plus prebiotic, and Lactobacillus plus prebiotic; these turned out to be the most effective probiotic interventions when considering all five parameters. It is notable that Lactobacillus and Bifidobacterium supplements alone are located in the middle of the plot, which meant that their efficacies turned out to be normal compared to other strains and worse than combination interventions, such as Lactobacillus plus prebiotic and Bifidobacterium plus Lactobacillus.

FIGURE 5

SUCRA and PCoA plot. Cumulative probability indicates the ranking of efficacy on the following: A, Mortality; B, NEC morbidity; C, Sepsis morbidity; D, Time to full enteral feeding; E, Length of hospital stay. The larger the surface under the curve, the better the rank of the intervention being the stipulation. F, The overall rank distribution of these terms is shown by a dimension reduction method of PCoA plot. The top two principal coordinates (“PCoA1” and “PCoA2”) represent the maximum amount of variation presented in the data set. BL, Bifidobacterium + Lactobacillus; BLE, Bifidobacterium + Lactobacillus + Enterococcus; BLP, Bifidobacterium + Lactobacillus + prebiotic; BLSA, Bifidobacterium + Lactobacillus + Saccharomyces; BLST, Bifidobacterium + Lactobacillus + Streptococcus; BP, Bifidobacterium + prebiotic; BST, Bifidobacterium + Streptococcus; LP, Lactobacillus + prebiotic.

FIGURE 5

SUCRA and PCoA plot. Cumulative probability indicates the ranking of efficacy on the following: A, Mortality; B, NEC morbidity; C, Sepsis morbidity; D, Time to full enteral feeding; E, Length of hospital stay. The larger the surface under the curve, the better the rank of the intervention being the stipulation. F, The overall rank distribution of these terms is shown by a dimension reduction method of PCoA plot. The top two principal coordinates (“PCoA1” and “PCoA2”) represent the maximum amount of variation presented in the data set. BL, Bifidobacterium + Lactobacillus; BLE, Bifidobacterium + Lactobacillus + Enterococcus; BLP, Bifidobacterium + Lactobacillus + prebiotic; BLSA, Bifidobacterium + Lactobacillus + Saccharomyces; BLST, Bifidobacterium + Lactobacillus + Streptococcus; BP, Bifidobacterium + prebiotic; BST, Bifidobacterium + Streptococcus; LP, Lactobacillus + prebiotic.

Close modal

Inspection of the funnel plot (Supplemental Fig 10) did not reveal significant asymmetry, which suggests low risk of publication bias with each outcome selected and revealed that no small-study effects existed. The result of the inconsistency test is presented in Supplemental Fig 11. There was no significant difference between direct and indirect estimates in closed loops, which ensured the assessment of network coherence for each comparison for all five parameters. We performed bias assessment for each RCT and generated a summarized graph (Supplemental Figs 1214). Although some studies were considered high risk because of blinding of outcome assessment and incomplete outcome data, most of the included studies were at low risk of bias in all components. The overall quality of evidence contributing to network meta-analysis (Supplemental Fig 15) was assessed with the Grading of Recommendations Assessment, Development and Evaluation profiler70  software (version 3.6).

In this study, we included 45 studies to investigate which probiotic strain has the best effect on the health of premature infants. To our knowledge, this is the first network meta-analysis comparing efficacy of different probiotic supplements in premature infants’ health. The results suggest that the rates of mortality, NEC morbidity, and sepsis morbidity, as well as the time to full enteral feeding and length of hospital stay, may be reduced by combined use of any two of Lactobacillus, Bifidobacterium, and prebiotic.

Intestinal mucosa is a natural barrier for migration of bacteria as well as their products. This barrier may also exclude potential pathogens competitively, modify the host response to endotoxin, inhibit the colonization of pathogens, and upregulate the immune responses.71  It is acknowledged that premature infants are less developed in their immune system and intestinal mucosa barrier and have a distinct gut microbiota.72  These physical characteristics put them at risk for death and morbidity of infectious diseases, especially NEC and sepsis.73,74  Undoubtedly, breast milk is the best nutrition for newborn infants.75  However, some mothers cannot provide enough breast milk to their preterm infants.76  Beyond breast milk, these infants need to intake formula or other preparations as a nutrition supplement, in which probiotic intervention could play an important role in promoting health of premature infants.

With our results, we performed indirect comparisons between different strains and placebo, suggesting that the use of Bifidobacterium and Lactobacillus is effective in all the primary and secondary outcomes, which is consistent with the results of direct comparisons from previous pairwise meta-analysis.17  Authors of the included RCTs estimated the effect of six different probiotic strains (Bifidobacterium, Lactobacillus, Enterococcus, Saccharomyces, Streptococcus, and Bacillus) and their combinations on the health parameters of premature infants. Notwithstanding the attempts of trials using other strains, our results revealed that interventions involving Bifidobacterium and Lactobacillus have more beneficial effects in each health parameter. AlFaleh and Anabrees15  suggested that probiotic preparations containing either Lactobacillus alone or in combination with Bifidobacterium are effective in infants at risk for NEC, which is consistent with our results. In general, Bifidobacterium and Lactobacillus are more effective than other probiotic strains.

In addition, our results revealed that combined use of probiotics may have better efficacy in premature infants than the single strain. As shown in Fig 5, combined use of probiotics ranks higher than single use both in each parameter and in general. This is consistent with Guthmann et al,77  who reported that two or more probiotic strains or a combination of Bifidobacterium and Lactobacillus achieves the best results in preterm infants. Thus, in further design of trials and clinical use, combination of probiotics and their synergistic effect should be taken into account.

In addition, our results revealed that the combined use of prebiotic with Bifidobacterium or Lactobacillus was more effective in preterm infants. Previously, we conducted a pairwise meta-analysis78  revealing that prebiotic treatments may reduce the rate of mortality but have little benefit in the morbidity of NEC. Premature infants, especially those at high risk, usually receive excessive antibiotic treatment, which may dramatically affect the composition of their gut microbiota. This imbalance of gut microecology cannot be addressed by single use of probiotic or prebiotic. Previous RCTs31,33,37,52,56  and meta-analyses78,79  suggested this problem could be solved by the combined use of probiotic and prebiotic, which is also mentioned as synbiotic supplementation. The synbiotic might contribute to colonization of the probiotic. This has been proven by stool cultures after 7 to 14 days of intervention. Manzoni et al56  and Underwood et al31  compared the stool microbiota in two groups of premature infants receiving Lactobacillus alone or combined use of Lactobacillus and prebiotic and found that the group receiving synbiotic supplementation exhibited augmented Lactobacillus colonization. Similarly, the same acceleration effect of prebiotic on Bifidobacterium colonization in low birth weight infants’ intestinal tract was found by Dilli et al52  and Chi et al.9  Prebiotic interacts with the probiotic, leading to a synergistic effect to boost the antibacterial defense of infants’ immature intestinal tract barrier.80  In addition, prebiotic supplements have been proven to accelerate intestinal maturation in preterm infants.81  According to the RCTs31,33,37,52,56  and Cochrane reviews,15,82  combined use of probiotic and prebiotic was described to be well tolerated and safe in infants. In addition, the dosage and course of treatment should be individualized according to the birth weight or gestational age of each infant. Infants weighing <1500 g need a higher dosage and longer course to ensure the effect of prebiotic usage.56 

The effect of Lactobacillus plus Bifidobacterium plus prebiotic on all five parameters was not distinguishable from those of all 14 interventions. Because the combined use of any two of Lactobacillus, Bifidobacterium, and prebiotic achieved a remarkable effect, the combined use of all three should have presented a cumulative effect. It is possible that Lactobacillus and Bifidobacterium target the same mechanism(s) in infants’ intestinal tract, thus excluding the cumulative effect. Alternatively, this may be attributed to the limited sample size and dosage used in relevant studies. In further study, more RCTs using Lactobacillus plus Bifidobacterium plus prebiotic should be performed and the optimal dosage determined in consideration of both safety and efficacy. Another limitation of this study is insufficient data in extremely low birth weight infants. Only authors of two RCTs set their inclusion criteria as infants with a birth weight of <1000 g. According to the results of Al-Hosni et al26  and Wejryd et al,63  probiotic supplementation is safe in infants with a birth weight <1000 g. Nevertheless, there is always a hypothetical risk of sepsis infection caused by probiotic intervention, especially in extremely low birth weight infants whose immune system may be significantly immature. In addition, previous guidelines83  listed extremely low birth weight as one of the contraindications. Thus, in premature infants with a gestational age <27 weeks or a birth weight <1000 g, more evidence and studies are needed to prove the safety of probiotic supplementation.

To our knowledge, this is the first network meta-analysis used to ascertain the rankings of common probiotics use and the optimal strains for premature infants, whereas most previous pairwise meta-analysis are focused on whether probiotics are effective or not. Thus, this study may provide new evidence for researchers to choose strains and methods when designing studies to give premature infants nutritional intervention individually and precisely.

In this network meta-analysis, we found that the efficacy of single probiotic supplements is limited. Notably, the risk of death was the lowest in premature infants who received Bifidobacterium plus prebiotic supplements. In addition, Lactobacillus plus prebiotic has the highest probability of being the optimal intervention for reducing NEC morbidity. To achieve optimal effects on premature infants’ health, combined use of prebiotic and probiotic, especially Lactobacillus or Bifidobacterium, is recommended in further study design.

Profs Yin and Sun conceptualized and designed the study and edited, reviewed, and revised the manuscript; Dr Chi designed the study, selected the articles, extracted and analyzed the data, and drafted the initial manuscript; Ms Li and Dr Wang selected the articles, extracted the data, and analyzed the data; Prof Buys supervised data collection and critically edited the final manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

CI

confidence interval

MeSH

Medical Subject Headings

NEC

necrotizing enterocolitis

PCoA

principal coordinate analysis

RCT

randomized controlled trial

RR

risk ratio

SUCRA

surface under the cumulative ranking curve

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data