Birth weight-specific mortality for extremely low birth weight infants vanishes by four days of life: epidemiology and ethics in the neonatal intensive care unit.
BACKGROUND
The persistent differences between those who question the appropriateness of aggressive resuscitative measures for many extremely low birth weight (ELBW) infants (birth weight < 1001 g) and those who generally initiate such treatment has been a source of ongoing tension for physicians, parents, judges, and policymakers. We believe that much of this tension may be a result of the way the issue is framed. We began this study with the intuition that although many ELBW infants die, most succumb quickly. Were this true, discussions that considered only survival rates might miss the point. A more relevant statistic might be the degree to which interventions prolong dying, extend suffering, or use resources for infants who will eventually die.


METHODS
We determined the survival and nonsurvival for 429 ELBW infants admitted to our neonatal intensive care unit (NICU) for 3 years. We noted particularly the relationship between birth weight, illness severity (fraction of inspired oxygen [Fio2] requirement for infants requiring mechanical ventilation), and the time course of mortality for nonsurvivors. We next calculated a resource utilization index (NICU bed days occupied by survivors and nonsurvivors) for each patient and for the population as a whole. Finally, we determined how NICU resources were distributed among infants who eventually died and those who survived.


RESULTS
Of the 429 ELBW infants alive on day of life (DOL) 1,202 (47%) survived to be discharged. on DOL 1, both birth weight and illness severity independently predicted likelihood of survival. Approximately 80% of ELBW deaths occurred in the first 3 days of life-- consequently, once an infant had survived to DOL 4, the likelihood of survival was dramatically enhanced (81% for the 249 patients alive on DOL 4). In addition, although survival for DOL 4 infants continued to depend on illness severity, survival no longer depended on birth weight. These observations on DOL 4 were confirmed in the subpopulation of 212 infants whose birth weight was < 750 g. Overall, although 53% of ELBW babies admitted died, only approximately 13% of all NICU bed-days (a proxy for resource allocation) were devoted to infants who did not survive. This figure did not vary as a function of birth weight.


CONCLUSIONS
Generally, when we talk of survival rates to parents, ethics committees, or policy makers, we base our predictions largely on birth weight. The data presented here suggest that predictions should be corrected by including DOL and that, when this is done, the prognostic value of birth weight rapidly diminishes. In addition, birth weight-specific mortality and day of death for nonsurvivors correlated inversely; that is more of the smaller infants died, but the doomed ones died more quickly. Consequently, medical resources allocated to nonsurvivors remained low, and independent of birth weight. This formulation lends weight both to the reasonableness of physicians in offering NICU care to ELBW infants, with unlikely prospects for survival, and of parents and surrogate decision-makers in requesting/ assenting to it.
Meadow
W
W
Department of Pediatrics, University of Chicago, IL 60637, USA.
Reimshisel
T
T
Lantos
J
J
D001509:Bed Occupancy / Q000706:statistics & numerical data; D001724:Birth Weight; D002641:Chicago / Q000453:epidemiology; D003657:Decision Making; D004812:Epidemiologic Methods; D004992:Ethics, Medical; D005544:Forecasting; D015276:Health Care Rationing; D006801:Humans; D007226:Infant Mortality; D007231:Infant, Newborn; D019102:Infant, Very Low Birth Weight; D007363:Intensive Care Units, Neonatal / Q000706:statistics & numerical data*; D015931:Intensive Care, Neonatal / Q000706:statistics & numerical data; D007902:Length of Stay / Q000706:statistics & numerical data; D010101:Oxygen Consumption; D010290:Parents; D010351:Patient Discharge / Q000706:statistics & numerical data; D018579:Patient Selection; D010820:Physicians; D011050:Policy Making; D011336:Probability; D040841:Resource Allocation; D012121:Respiration, Artificial; D015996:Survival Rate; D013997:Time Factors; D035501:Uncertainty