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Platelet indices as a predictive marker in neonates with respiratory distress



The neonatal intensive care unit (NICU) frequently gets admissions due to respiratory distress (RD). Platelet indices are a beneficial biomarker in order to gauge the severity of neonatal RD. We aimed to assess platelet indices as a potential predictor in neonates with RD.


This prospective research involved 120 neonates who had been admitted to the NICU with evidence of RD. On admission and after respiratory support was reduced; a complete blood count (CBC) was performed to determine platelet count (PC), mean platelet volume (MPV), plateletcrit (PCT), platelet distribution width (PDW), platelet mass index (PMI), and platelet large cell ratio (PLCR).


MPV and PDW were significantly higher after respiratory support reduction. PC and PMI were significantly higher in neonates exhibiting moderate and severe distress. PC of 276.5*109/L had the highest degree of predictability of RD severity (area under curve (AUC) 0.762, sensitivity 81.5%, specificity 64.3%), 95% confidence interval (0.7–0.9), while PMI of 2473.5 fL/nL was the best cut-off point to predict severity of RD (AUC 0.663, sensitivity 63%, specificity 57.1%) 95% confidence interval (0.6–0.8). There was a significant difference in the average PC between different oxygen modes.


Higher PMI and PC are associated with moderate and severe RD and can be used to predict the severity of neonatal RD.


In both term and preterm newborns, respiratory illnesses are the most prevalent causes of entrance to the neonatal intensive care unit (NICU) [1]. One of the most frequent neonatal conditions is respiratory distress (RD) which can affect as many as 7% of all term infants and is on the rise among prematures [2].

According to research conducted by Cairo University on newborn mortality in the intensive care unit of a children’s hospital in Egypt, neonatal mortality from RD accounts for 26.7% of all neonatal fatalities and the primary reason for all NICU admissions [3].

Lungs and platelets (PLTs) have an intimate relationship. Megakaryocytes are found in mammalian lungs which is considered a site of thrombopoiesis. In the recuperation process of the lungs, PLTs presumably perform specific functions. In pulmonary defenses and integrity, platelets play a fundamental role [4]. Maintaining endothelial integrity and barrier function requires the presence of PLTs [5].

Platelet (PLT) indices are used to assess their function. Plateletcrit (PCT) is a measure of the quantity of PLTs and their proportion in whole blood [6, 7]. The average PLT size is quantified by mean platelet volume (MPV), while the variation of PLT size is demonstrated by platelet distribution width (PDW). Typically, the PLT count has an inverse relationship with MPV and PDW [8].

PLT function alterations can be detected by changes in platelet volume indices (PVI). These metrics assess PLT size, which is correlated with PLT activity [9].

This study aimed to assess PLT indices (MPV, PDW, platelet large cell ratio (PLCR), platelet mass index (PMI), and PCT) as a predictive marker in neonates with RD.


This study was prospective, and it continued to follow up until the need for respiratory support was reduced. At El-Gamaaya El-Sharaya Hospital, 6 October city, Egypt, it was carried out on 120 neonates having RD who were receiving care in the NICU. Ethics committee approval was obtained by research ethical committee October 6 University, Egypt. Prior to enrolment, patients’ guardians granted informed consent after being apprised of the study’s purpose. Participants had the privilege to continue participating in the research at any time and maintain their confidentiality about all study data.

Inclusion criteria

Neonates who exhibited signs of RD after birth (such as tachypnea, chest retractions, or grunting) which necessitated respiratory assistance in the form of mechanical ventilation or bubble continuous positive airway pressure (CPAP) or head box or nasal O2 therapy and hemodynamically stable.

Utilizing the Silverman Andersen respiratory severity score for newborns, respiratory impairment was reviewed. It considers five aspects of respiratory exertion and offers an ultimate score, score 0= no RD, 1–3= mild RD, 4–6 = moderate RD, >6 = impending respiratory failure and score 10= severe RD (Fig. 1) [10,11,12].

Fig. 1
figure 1

The Silverman Andersen Respiratory Severity Score (RSS) evaluates five parameters of work of breathing and assigns an overall score with a patient breathing comfortably a “0” and a patient in severe respiratory distress a “10”

Exclusion criteria

Any neonate with congenital heart disease (ECHO cardiography was done for all our patients to exclude patent ductus arteriosus), congenital anomalies, hemolytic disorders. Neonates with early onset sepsis either clinically or proved by positive blood culture, positive C reactive protein, leucopenia or leucocytosis with shift to the left or bandemia. Thrombocytopenia is a work of sepsis and none of our cases had thrombocytopenia.

The following was implemented to all participants: collecting a comprehensive medical history with an emphasis on gestational age (GA), gender, mode of delivery, birth weight, family history, consanguinity. Clinical examination including grading of RD, demand for oxygen supplementation, and length of hospital stay was collected for all patients.

Based on evidence from previous similar studies, we used epi-calculator 2000 to calculate the sample size of this comparative study. Assuming 80% power and 0.05 level of significance, a total sample size of 120 participants was calculated.

Laboratory investigations

All participants’ blood samples were drawn for a complete blood count (CBC); platelet indices were examined upon entrance to the NICU, and subsequently verified after reduction of respiratory support.

Applying the following equation, PMI was calculated: (PMI = [Platelet counts] × [mean platelet volume/103]) (fL/nL) [13].

Sample collection

Venipuncture was performed to obtain 2 ml of venous blood, which was then placed in tubes containing tripotassium-ethylenediaminetetraacetic acid (EDTA) to avoid coagulation. Within 30 min of being collected, samples were swiftly shipped to the lab for processing. The automated cell counter (Sysmex KX-21N) was used to analyze the obtained EDTA samples in order to get all PLT indices: MPV expressed in femtolitre (fl), PCT expressed in percentage (%), platelet count (PC) calculated in cubic millimeter (*1000/mm3), PDW and PLCR measured in percentage (%).

Statistical methods

Version 28 of SPSS’ statistical software program was used to examine the data. Utilizing the Kolmogorov-Smirnov single-sample test, the data’s normalization was evaluated. Numbers and percentages are used to represent qualitative data. Mean and standard deviation were used to depict quantitative parameters. The comparison between results before applying respiratory support and after elimination was done using Wilcoxon test. The Mann-Whitney test was used to contrast the two sets of numerical data, and the Kruskal-Wallis test by post hock test will be employed for pairwise comparison when considering more than two participants. Spearman correlation was used to correlate continuous data. To identify the ideal cut-off value, receiver operator characteristic (ROC) curves were applied. Significance was defined as (p ≤ 0.05).


There were 120 participants in our research, with 55.8% males and 44.2% females. Participants’ average ages were 6±4.7 days and weights were 2.7±0.6 kg on average. The mean GA of the patients was 36.5 ± 1.8 weeks, 73% of them were delivered via cesarean section. Twenty-nine (24.1%) patients were diagnosed as respiratory distress syndrome (RDS) and 91 (75.8%) were diagnosed as transient tachypnea of newborn (TTN). Half of the participants used nasal CPAP, 31.7 % of the patients were mechanically ventilated, and 18.3 % received low flow nasal oxygen. The average duration of hospitalization was 4.8±2.1 days, while the average time to reduce respiratory support was 2.7 ±1.1 days. Consanguinity and family history were evident in 6.7% and 5% respectively. Approximately 76.6% of the subjects had RD grades III and IV (Table 1).

Table 1 Sociodemographic characteristics of the participants

After receiving oxygen treatment, there was a statistically significant increase in the average MPV (8.9±1.1 versus 8.7±1.2, p-value=0.016) as well as the mean PDW (15.5±2.6 versus 14.9±2.5, p-value=0.010); nevertheless, there was statistically insignificant change regarding the results of PC, PCT, PMI, and PLCR before and following treatment (Table 2).

Table 2 Comparison of platelets indices before and after respiratory support reduction

Neonates presented with moderate and severe distress had significantly higher PC than those with mild distress (317.9 76.6 versus 264.2 37.9, p-value 0.001), and these patients also had a higher average PMI (p-value.009) as shown in Table 3.

Table 3 Relation between platelet indices and respiratory distress

The best cut-off points for PC on the ROC curve analysis to anticipate the severity of RD were 276.5 (*1000/mm3); the area under the curve (AUC) was 0.762; the 95% confidence interval (CI) was (0.7–0.9); and the sensitivity and specificity were 81.5% and 64.3%, respectively (Fig. 2). With a sensitivity of 63% and specificity of 57.1%, the best cut-off point for PMI was 2473.5 fL/nL, with an AUC of 0.663 and a 95% CI (0.6–0.8) (Fig. 3, Table 4).

Fig. 2
figure 2

ROC curve to assess the diagnostic accuracy of platelets in predicting the severity of reparatory distress

Fig. 3
figure 3

ROC curve to assess the diagnostic accuracy of PMI in predicting the severity of reparatory distress

Table 4 The diagnostic accuracy of platelet and PMI, and in predicting the severity of respiratory distress

There was a significant difference in the average PC between different oxygen modes after doing a pairwise comparison, the significant difference between nasal CPAP and low-flow nasal oxygen (adjusted p-value 0.007), and mechanical ventilation and low-low nasal oxygen (adjusted p-value < 0.001) (Table 5).

Table 5 Relation between platelet indices and oxygen mode

Table 6 shows multivariate analysis of factors associated with respiratory distress and revealed that platelet number was the factor independently affecting depression; neonates with platelet ≥276.5 had a 7.9 odds ratio to get severe respiratory distress.

Table 6 Multivariate analysis of factors associated with respiratory distress

As a consequence of our research, the period of respiratory support and PCT were shown to be statistically significantly positively correlated. It was also shown that PDW and the duration of respiratory support had insignificant negative correlation. It was statistically significant that PCT, PDW, and PLCR all had a negative correlation with GA.


Involved in the biogenesis of PLTs, the lungs could generate 10 million PLTs every hour, or around 50% of all PLTs [14]. Human lungs operate as PLT reservoirs, releasing them in reaction to specific triggers [4].

In our investigation, we discovered that, with the exception of MPV and PDW, which exhibited a significant increase, all PLT indices (PC, PCT, PMI, PLCR) showed an insignificant increase in mean value after acquiring respiratory support. This is consistent with findings of El Mashad et al. [15] and Sweet et al. [16], who reported that there was a non-significant difference regarding platelet and that MPV was significantly higher in preterms with respiratory distress syndrome (RDS). In a study conducted by Mishra et al. [17], it was discovered that the levels of platelet indices (MPV and PCT) were significantly higher in the group of those who diagnosed as RD (p-value 0.003). MPV was considered to be a measure of platelet generation and consumption, and it can also be correlated with the severity of various disorders [16]. In a study conducted by Go et al. [18], the bronchopulmonary dysplasia (BPD) group did not show an increase in the PC and PCT with increasing age and remained at a low level. BPD microvascular dysplasia and halted pulmonary development can both interfere with the process of biosynthesis and discharge of PLTs, since the pulmonary capillary bed is contracted or morphologically modified which disturbs the pulmonary megakaryocyte fragmentation or spatial arrangement [19]. Such outcomes may suggest that the improvement of lung disease and lung development have an impact on PLT manufacture. A future study including assessment of PLT indices with longer-term follow-up could help clarify the risk of development of BPD in neonates with RD especially premature infants.

PC and PMI were significantly higher in neonates presented with moderate and severe distress compared with those presented with mild distress (p-value < 0.001 and 0.009 respectively). This is consistent with a study done by Franciuc et al. [20] who compared RDS group and non-RDS group and found that PC (320.16 ± 115.89 versus 358.50 ± 283.47, p-value 0.696) and PMI (3701.90 ±1240.91 versus 3862.45 ±3142.11, p-value 0.881) showed higher levels in RDS group. PLTs participate in maintaining the barrier function of the endothelium: the discharge of soluble compounds that preserve the barrier sturdiness via endothelial cell signals; physical blocking of endothelial barrier gaps; preservation of vital endothelial cell structure necessary for barrier integrity; promoting or expediting endothelial cell proliferation [21]. There’s substantial confirmation that PLTs can improve function of endothelium and lower its permeability, and that adequate levels of circulated PLTs could be crucial in maintaining the integrity of the alveolar capillaries’ barrier and other capillary beds [22]. When compared to platelet count alone, platelet mass provides a more accurate reflection of platelet function [23]. Mangalpally et al. [24] and Gerday et al. [13] stated that due to bigger platelets’ higher enzymatic activity compared to smaller platelets, PMI is correlated with platelet functionality. Recent research showed that platelet mass index, rather than PC, should be employed as a marker for platelet transfusion [25]. Gerday et al. [13] revealed that employing platelet mass lessens the necessity for platelet transfusions.

We observed a significant difference in the average PC between different oxygen modes. PC was significantly higher in patients that require mechanical ventilation (p-value < 0.001). Increased demand for oxygen and mechanical ventilation drives inflammatory cells to gather in pulmonary tissue [26]. As a major inflammatory cells, PLTs have functions which encompass the immunological continuum [27]. Lung defense is strengthened by the inflammatory functions of platelets [28].

Our study’s strength is that platelet function is determined by platelet indices such as MPV, PCT, PDW, and PLCR, which can be promptly and readily measured by a routine CBC. These standards are affordable and accessible to all institutions, including developing countries.

Since we investigated treatment results that emerged in the early stage, our study had certain limitations. Longer follow-up periods are recommended; our advice is to expand the term of monitoring to include the entire neonates’ whole hospital experience and to detect BPD cases and its relationship with changes in PLT parameters.


Higher PMI and PC are associated with moderate and severe respiratory distress which may allow clinicians to predict the severity of neonatal respiratory distress. PC is significantly higher in mechanically ventilated patients.



Area under curve


Bronchopulmonary dysplasia


Complete blood count


Confidence interval


Continuous positive airway pressure


Ethylenediaminetetraacetic acid


Gestational age


Platelet count




Platelet distribution width


Platelet mass index


Platelet large cell ratio






Platelet volume indices


Mean platelet volume


Neonatal intensive care unit


Respiratory distress


Respiratory distress syndrome


Receiver operating characteristic


  1. Pramanik AK, Rangaswamy N, Gates T (2015) Neonatal respiratory distress a practical approach to its diagnosis and management. Pediatr Clin N Am 62:453–469

    Article  Google Scholar 

  2. Mo E, Sj K, Kotecha S (2013) Respiratory distress of the term newborn infant. Paediatr Respir Rev 14(1):29–36

    Article  Google Scholar 

  3. Zaman S, Goheer L, Riaz H (2013) Prevalence and etiology of respiratory distress in newborns. Pak Armed Forces Med J 63(1):22–25

    Google Scholar 

  4. Weyrich AS, Zimmerman GA (2013) Platelets in lung biology. Annu Rev Physiol 75:569–623

    Article  CAS  PubMed  Google Scholar 

  5. Vieira-de-Abreu A, Campbell RA, Weyrich AS, Zimmerman GA (2012) Platelets: versatile effector cells in hemostasis, inflammation, and the immune continuum. Semin Immunopathol 34:5–30

    Article  CAS  PubMed  Google Scholar 

  6. Henry BM, Benoit SW, de Oliveira MHS (2020) Laboratory abnormalities in children with mild and severe coronavirus disease 2019 (COVID-19): a pooled analysis and review. Clin Biochem 81:1–8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Koupenova M, Corkrey HA, Vitseva O (2021) SARS-CoV-2 initiates programmed cell death in platelets. Circ Res 129(6):631–646

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Ahmad MS, Waheed A (2014) Platelet counts, MPV and PDW in culture proven and probable neonatal sepsis and association of platelet counts with mortality rate. J Coll Physicians Surg Pak 24:340–344

    PubMed  Google Scholar 

  9. Leader A, Pereg D, Lishner M (2012) Are platelet volume indices of clinical use? A multidisciplinary review. Ann Med 44(8):805–816

    Article  PubMed  Google Scholar 

  10. Hedstrom AB, Gove NE, Mayock DE, Batra M (2018) Performance of the Silverman Andersen Respiratory Severity Score in predicting PCO2 and respiratory support in newborns: a prospective cohort study. J Perinatol 38:505–511

    Article  PubMed  PubMed Central  Google Scholar 

  11. Silverman WA, Andersen DH (1956) A controlled clinical trial of effects of water mist on obstructive respiratory signs, death rate and necropsy findings among premature infants. Pediatrics. 17:1–10

    CAS  PubMed  Google Scholar 

  12. McAdams RM, Hedstrom AB, DiBlasi RM, Mant JE, Nyo-nyintono J, Otai CD (2015) Implementation of bubble CPAP in a rural Ugandan neonatal ICU. Respir Care 60:437–445

    Article  PubMed  Google Scholar 

  13. Gerday E, Baer VL, Lambert DK (2009) Testing platelet mass versus platelet count to guide platelet transfusions in the neonatal intensive care unit. Transfusion. 49:2034–2039

    Article  PubMed  Google Scholar 

  14. Lefrançais E, Ortiz-Muñoz G, Caudrillier A, Mallavia B, Liu F, Sayah DM (2017) The lung is a site of platelet biogenesis and a reservoir for haematopoietic progenitors. Nature. 544:105–110

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  15. El Mashad GM, El Saieda HM, Alib GS (2021) Mean platelet volume as a prognostic factor in neonatal respiratory distress. Menoufia Med J 34:187–191

    Article  Google Scholar 

  16. Sweet DG, Carnielli V, Greisen G, Hallman M, Ozek E, Plavka R (2010) European consensus guidelines on the management of neonatal respiratory distress syndrome in preterm infants – 2010 update. Neonatology 97:402–417

    Article  PubMed  Google Scholar 

  17. Mishra S, Jaiswar S, Saad S, Tripathi S, Singh N, Deo S, Agarwal M, Mishra N (2021) Platelet indices as a predictive marker in neonatal sepsis and respiratory distress in preterm prelabor rupture of membranes. Int J Hematol 113:199–206

    Article  CAS  PubMed  Google Scholar 

  18. Go H, Ohto H, Nollet KE, Takano S, Kashiwabara N, Chishiki M (2020) Using platelet parameters to anticipate morbidity and mortality among preterm neonates: a retrospective study. Front Pediatr 8:90

    Article  PubMed  PubMed Central  Google Scholar 

  19. XiaoYang DWM, Yang J, Hon KL, Fok FT (2006) Lung damage may induce thrombocytopenia. Platelets. 17:347–349

    Article  Google Scholar 

  20. Franciuc I, Matei E, Aschie M, Mitroi A, Chisoi A, Poinareanu I, Dobrin N, Georgiana Stoica A, Surdu T, Manea M, Topliceanu S, Cozaru G (2022) Changes in platelet function in preterm newborns with prematurity related morbidities. Children 9:791

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ho-Tin-Noe B, Demers M, Wagner DD (2011) How platelets safeguard vascular integrity. J Thromb Haemost 9:56–65

    Article  PubMed  PubMed Central  Google Scholar 

  22. Zarbock A, Ley K (2009) The role of platelets in acute lung injury (ALI). Front Biosci 14:150–158

    Article  CAS  PubMed Central  Google Scholar 

  23. Christensen RD (2011) Platelet transfusion in the neonatal intensive care unit: benefits, risks, alternatives. Neonatology. 100:311–318

    Article  PubMed  Google Scholar 

  24. Mangalpally KK, Siqueiros-Garcia A, Vaduganathan M, DongJF KNS, Guthikonda S (2010) Platelet activation patterns in platelet size sub-populations: differential responses to aspirin in vitro. J Thromb 30:251e62

    Google Scholar 

  25. Zisk JL, Mackley A, Clearly G, Chang E, Christensen RD, Paul DA (2014) Transfusing neonates based on platelet count vs. platelet mass: a randomized feasibility-pilot study. Platelets. 25:513–516

    Article  CAS  PubMed  Google Scholar 

  26. Cekmez F, Tanju IA, Canpolat FE, Aydinoz S, Aydemir G, Karademir F (2013) Mean platelet volume in very preterm infants: a predictor of morbidities? Eur Rev Med Pharmacol Sci 17:134–137

    CAS  PubMed  Google Scholar 

  27. Semple JW, Italiano JE Jr, Freedman J (2011) Platelets and the immune continuum. Nat Rev Immunol 11:264–274

    Article  CAS  PubMed  Google Scholar 

  28. Bozza FA, Shah AM, Weyrich AS, Zimmerman GA (2009) Amicus or adversary: platelets in lung biology, acute injury, and inflammation. Am J Respir Cell Mol Biol 40:123–134

    Article  CAS  PubMed  Google Scholar 

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The authors are grateful to the patients and their parents.

Availability of data and material

The datasets analyzed in this study are available from the corresponding author upon reasonable request.


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Authors and Affiliations



Manar Aref and Sarah Abdelrashid were involved with study concept and design. Manar Aref was involved with patients’ inclusion and data collection. Sarah Abdelrashid analyzed the data and performed data interpretation and tables’ design. Sarah Abdelrashid wrote the manuscript. Manar Aref revised the manuscript. All authors reviewed and took full responsibility for the final version of the manuscript.

Corresponding author

Correspondence to Sarah Abdelrashid.

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Ethics approval and consent to participate

This study was approved by research ethical committee October 6 University (REC-O6U), Egypt. Prior to enrolment, patients’ guardians granted informed consent after being apprised of the study’s purpose.

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The authors declare no competing interests.

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Abdelrashid, S., Aref, M. Platelet indices as a predictive marker in neonates with respiratory distress. Egypt Pediatric Association Gaz 72, 21 (2024).

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