TY - JOUR
T1 - Neonatal near-misses in Ghana
T2 - A prospective, observational, multi-center study
AU - Bakari, Ashura
AU - Bell, April J.
AU - Oppong, Samuel A.
AU - Bockarie, Yemah
AU - Wobil, Priscilla
AU - Plange-Rhule, Gyikua
AU - Goka, Bamenla Q.
AU - Engmann, Cyril M.
AU - Adanu, Richard M.
AU - Moyer, Cheryl A.
N1 - Publisher Copyright:
© 2019 The Author(s).
PY - 2019/12/23
Y1 - 2019/12/23
N2 - Background: For every newborn who dies within the first month, as many as eight more suffer life-threatening complications but survive (termed 'neonatal near-misses' (NNM)). However, there is no universally agreed-upon definition or assessment tool for NNM. This study sought to describe the development of the Neonatal Near-Miss Assessment Tool (NNMAT) for low-resource settings, as well as findings when implemented in Ghana. Methods: This prospective, observational study was conducted at two tertiary care hospitals in southern Ghana from April-July 2015. Newborns with evidence of complications and those admitted to the NICUs were screened for inclusion using the NNMAT. Incidence of suspected NNM at enrollment and confirmed near-miss (surviving to 28 days) was determined and compared against institutional neonatal mortality rates. Suspected NNM cases were compared with newborns not classified as a suspected near-miss, and all were followed to 28 days to determine odds of survival. Confirmed near-misses were those identified as suspected near-misses at enrollment who survived to 28 days. The main outcome measures were incidence of NNM, NNM:mortality ratio, and factors associated with NNM classification. Results: Out of 394 newborns with complications, 341 (86.5%) were initially classified as suspected near-misses at enrollment using the NNMAT, with 53 (13.4%) being classified as a non-near-miss. At 28-day follow-up, 68 (17%) had died, 52 (13%) were classified as a non-near-miss, and 274 were considered confirmed near-misses. Those newborns with complications who were classified as suspected near-misses using the NNMAT at enrollment had 12 times the odds of dying before 28 days than those classified as non-near-misses. While most confirmed near-misses qualified as NNM via intervention-based criteria, nearly two-thirds qualified based on two or more of the four NNMAT categories. When disaggregated, the most predictive elements of the NNMAT were gestational age < 33 weeks, neurologic dysfunction, respiratory dysfunction, and hemoglobin < 10 gd/dl. The ratio of near-misses to deaths was 0.55: 1, yet this varied across the study sites. Conclusions: This research suggests that the NNMAT is an effective tool for assessing neonatal near-misses in low-resource settings. We believe this approach has significant systems-level, continuous quality improvement, clinical and policy-level implications.
AB - Background: For every newborn who dies within the first month, as many as eight more suffer life-threatening complications but survive (termed 'neonatal near-misses' (NNM)). However, there is no universally agreed-upon definition or assessment tool for NNM. This study sought to describe the development of the Neonatal Near-Miss Assessment Tool (NNMAT) for low-resource settings, as well as findings when implemented in Ghana. Methods: This prospective, observational study was conducted at two tertiary care hospitals in southern Ghana from April-July 2015. Newborns with evidence of complications and those admitted to the NICUs were screened for inclusion using the NNMAT. Incidence of suspected NNM at enrollment and confirmed near-miss (surviving to 28 days) was determined and compared against institutional neonatal mortality rates. Suspected NNM cases were compared with newborns not classified as a suspected near-miss, and all were followed to 28 days to determine odds of survival. Confirmed near-misses were those identified as suspected near-misses at enrollment who survived to 28 days. The main outcome measures were incidence of NNM, NNM:mortality ratio, and factors associated with NNM classification. Results: Out of 394 newborns with complications, 341 (86.5%) were initially classified as suspected near-misses at enrollment using the NNMAT, with 53 (13.4%) being classified as a non-near-miss. At 28-day follow-up, 68 (17%) had died, 52 (13%) were classified as a non-near-miss, and 274 were considered confirmed near-misses. Those newborns with complications who were classified as suspected near-misses using the NNMAT at enrollment had 12 times the odds of dying before 28 days than those classified as non-near-misses. While most confirmed near-misses qualified as NNM via intervention-based criteria, nearly two-thirds qualified based on two or more of the four NNMAT categories. When disaggregated, the most predictive elements of the NNMAT were gestational age < 33 weeks, neurologic dysfunction, respiratory dysfunction, and hemoglobin < 10 gd/dl. The ratio of near-misses to deaths was 0.55: 1, yet this varied across the study sites. Conclusions: This research suggests that the NNMAT is an effective tool for assessing neonatal near-misses in low-resource settings. We believe this approach has significant systems-level, continuous quality improvement, clinical and policy-level implications.
KW - Neonatal morbidity
KW - Neonatal mortality
KW - Neonatal near-miss indicators
UR - http://www.scopus.com/inward/record.url?scp=85077094920&partnerID=8YFLogxK
U2 - 10.1186/s12887-019-1883-y
DO - 10.1186/s12887-019-1883-y
M3 - Article
C2 - 31870340
AN - SCOPUS:85077094920
SN - 1471-2431
VL - 19
JO - BMC Pediatrics
JF - BMC Pediatrics
IS - 1
M1 - 509
ER -