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Predicting bleeding in thrombocytopenic neonates
Table 3. The dynamic prediction model.
Covariates with time-constant effects
Gestational age (days)
Postnatal age (days)
Mechanical ventilation
NEC/sepsis
Platelet transfusion
Interaction term log10 platelet count
and platelet transfusion
Covariates with time-varying effects
LM (2-hour intervals)
LM2 (2-hour intervals)
IUGR constant
IUGR time-varying: LM
IUGR time-varying: LM2
Log10 platelet count constant
Log10 platelet count time-varying LM Log10 platelet count time-varying: LM2
Hazard ratio
1.00
0.88 5.08 0.85 1.06 1.23
2.30
0.85 0.51
0.31
1.22
1.74
0.35
1.12
95% CI
0.98 – 1.02
0.83 – 0.94* 2.03 – 10.65* 0.43 – 1.58 0.38 – 2.95 0.63 – 2.38
0.89 – 5.94 0.74 – 0.98* 0.17 – 1.59 0.09 – 1.14 1.04 – 1.44* 0.72 – 4.24 0.19 – 0.63* 1.03 – 1.21*
Table 4. Risk predictions for different clinical scenarios.
Patient’s characteristics: GA 28 weeks, platelet count 10x109/L at day 3 of
life (first time <50x109/L), no transfusion.
NEC/sepsis; IUGR
No NEC/sepsis No; IUGR NEC/sepsis No; IUGR No NEC/sepsis; IUGR
Ventilation No ventilation
8% 2%
17% 3% 14% 3% 9% 2%
Patient’s characteristics: GA 28 weeks, platelet count 50x109/L at day3of life (first time <50x109/L) , no transfusion.
NEC/sepsis; IUGR
No NEC/sepsis No; IUGR
NEC/sepsis No; IUGR
No NEC/sepsis; IUGR
Ventilation No ventilation
11% 2%
24% 5%
20% 4%
13% 3%
A hazard ratio >1 indicates that an increase of the risk factor is associated with a high- er risk of bleeding. For example, a mechanically ventilated neonate has a 5.08 times higher risk of bleeding than a neonate who is not mechanically ventilated. If both boundaries of the confidence interval are either higher than 1 or lower than 1, the variable is a statistically significant predictor,indicated by *.LM:landmark time,linear interaction. LM2: landmark time, quadratic interaction. LM or landmark time refers to time since onset of severe thrombocytopenia (time-dependent variable), in 2-hour time intervals.Postnatal age refers to the postnatal age at the onset of severe thrombo- cytopenia (baseline variables).Time-varying covariates should not be confused with time-dependent covariates,such as platelet count or platelet transfusion,for which the value of the variable is not fixed (it is not a baseline variable) but can change over time. In time-varying covariates, the effect of the covariate can change over time, for example, the strength and direction of a potential association of intrauterine growth retardation with bleeding could be different immediately after the onset of thrombo- cytopenia compared to a few days after the onset of thrombocytopenia, due to inter- actions with other risk factors and changes in the clinical situation of the neonate. NEC: necrotizing enterocolitis; IUGR: intrauterine growth retardation. 95% CI:. 95% con- fidence interval.
comes were expected. The model should thus be applied with caution in neonates with a gestational age of less than 26 weeks.
Strengths of our study are the size of the cohort and the fact that we selected the predictors prior to data analysis rather than performing a stepwise selection. In addition, our data collection was meticulous and we performed multiple additional sensitivity analyses to confirm the robustness of our model. Our model is easy to apply,
GA: gestational age; NEC: necrotizing enterocolitis. IUGR: intrauterine growth retarda- tion.
because we have used clear and simple definitions of the covariates. Once the model has been externally validated, we will develop an online calculator, with which it should only take a few minutes to enter the variables and calcu- late absolute risk of bleeding.
In short, this dynamic prediction model allows clini- cians to quantify bleeding risk and adjust it as the clinical situation of the neonate changes. Risk can be predicted at any time-point during the first week after the onset of severe thrombocytopenia. This is a promising model that should be explored in future studies, as it is a first step towards individualized platelet transfusion guidelines.
Acknowledgments
This research was supported by grant PPOC-12-012027 from Sanquin Research, Amsterdam, the Netherlands. The spon- sor of this study is a nonprofit organization that supports science in general. It had no role in gathering, analyzing, or interpreting the data. SFFG is a PhD candidate at the University of Amsterdam. This work has been submitted in partial fulfillment of the requirement for the PhD. We thank Sahile Makineli and Nick van Hijum, both medical students at the time of this study, for their contribution to data collection and data analysis. We also thank Yavanna Oostveen, data manager, for her contribution to the data management.
References
1. Baer VL, Lambert DK, Henry E, Christensen RD. Severe thrombocytopenia in the NICU. Pediatrics. 2009;124(6):e1095-100.
2. von Lindern JS, van den Bruele T, Lopriore E, Walther FJ. Thrombocytopenia in neonates and the risk of intraventricular hemorrhage: a retrospective cohort study. BMC Pediatr. 2011;11(1):16.
3. Fustolo-Gunnink SF, Huijssen-Huisman EJ, van der Bom JG, et al. Are thrombocytope- nia and platelet transfusions associated with major bleeding in preterm neonates? A sys-
tematic review. Blood Rev. 2019;36:1-9.
4. Stanworth SJ, Clarke P, Watts T, et al. Prospective, observational study of out-
comes in neonates with severe thrombocy- 8.
topenia. Pediatrics. 2009;124(5):e826-34.
5. von Lindern JS, van den Bruele T, Lopriore E, Walther FJ. Thrombocytopenia in neonates and the risk of intraventricular hemorrhage:
a retrospective cohort study. BMC Pediatr. 9.
2011;11(1):16.
6. Curley A, Stanworth SJ, Willoughby K, et al.
Randomized trial of platelet-transfusion thresholds in neonates. N Engl J Med. 2018;380(3):242-251. 10.
7. New H V., Berryman J, Bolton-Maggs PHB,
et al. Guidelines on transfusion for fetuses, neonates and older children. Br J Haematol. 2016;175(5):784-828.
Luque MJ, Tapia JL, Villarroel L, et al. A risk prediction model for severe intraventricular hemorrhage in very low birth weight infants and the effect of prophylactic indomethacin. J Perinatol. 2014;34(1):43-48.
van de Bor M, Verloove-Vanhorick SP, Brand R, Keirse MJ, Ruys JH. Incidence and predic- tion of periventricular-intraventricular hem- orrhage in very preterm infants. J Perinat Med. 1987;15(4):333-339.
Heuchan AM, Evans N, Henderson Smart DJ, Simpson JM. Perinatal risk factors for
haematologica | 2019; 104(11)
2305