Hundalani Shilpa G, Richards-Kortum Rebecca, Oden Maria, Kawaza Kondwani, Gest Alfred, Molyneux Elizabeth
Department of Pediatrics, Queen Elizabeth Central Hospital, Blantyre, Malawi Department of Bioengineering, Rice University, Houston, Texas, USA.
Department of Bioengineering, Rice University, Houston, Texas, USA.
Arch Dis Child Fetal Neonatal Ed. 2015 Jul;100(4):F332-6. doi: 10.1136/archdischild-2014-308082. Epub 2015 Apr 15.
Low-cost bubble continuous positive airway pressure (bCPAP) systems have been shown to improve survival in neonates with respiratory distress, in developing countries including Malawi. District hospitals in Malawi implementing CPAP requested simple and reliable guidelines to enable healthcare workers with basic skills and minimal training to determine when treatment with CPAP is necessary. We developed and validated TRY (T: Tone is good, R: Respiratory Distress and Y=Yes) CPAP, a simple algorithm to identify neonates with respiratory distress who would benefit from CPAP.
To validate the TRY CPAP algorithm for neonates with respiratory distress in a low-resource setting.
We constructed an algorithm using a combination of vital signs, tone and birth weight to determine the need for CPAP in neonates with respiratory distress. Neonates admitted to the neonatal ward of Queen Elizabeth Central Hospital, in Blantyre, Malawi, were assessed in a prospective, cross-sectional study. Nurses and paediatricians-in-training assessed neonates to determine whether they required CPAP using the TRY CPAP algorithm. To establish the accuracy of the TRY CPAP algorithm in evaluating the need for CPAP, their assessment was compared with the decision of a neonatologist blinded to the TRY CPAP algorithm findings.
325 neonates were evaluated over a 2-month period; 13% were deemed to require CPAP by the neonatologist. The inter-rater reliability with the algorithm was 0.90 for nurses and 0.97 for paediatricians-in-training using the neonatologist's assessment as the reference standard.
The TRY CPAP algorithm has the potential to be a simple and reliable tool to assist nurses and clinicians in identifying neonates who require treatment with CPAP in low-resource settings.
在包括马拉维在内的发展中国家，低成本的气泡式持续气道正压通气（bCPAP）系统已被证明可提高呼吸窘迫新生儿的存活率。马拉维实施CPAP的地区医院要求提供简单可靠的指南，以使具备基本技能且接受过最少培训的医护人员能够确定何时有必要使用CPAP进行治疗。我们开发并验证了TRY（T：肌张力良好，R：呼吸窘迫，Y = 是）CPAP，这是一种用于识别可从CPAP中受益的呼吸窘迫新生儿的简单算法。
在资源匮乏的环境中验证TRY CPAP算法用于呼吸窘迫新生儿的有效性。
我们构建了一种算法，结合生命体征、肌张力和出生体重来确定呼吸窘迫新生儿是否需要CPAP。在一项前瞻性横断面研究中，对马拉维布兰太尔伊丽莎白女王中央医院新生儿病房收治的新生儿进行了评估。护士和儿科实习医生使用TRY CPAP算法评估新生儿，以确定他们是否需要CPAP。为了确定TRY CPAP算法在评估CPAP需求方面的准确性，将他们的评估结果与一位对TRY CPAP算法结果不知情的新生儿科医生的判断进行了比较。
在2个月的时间里对325名新生儿进行了评估；新生儿科医生认为13%的新生儿需要CPAP。以新生儿科医生的评估为参考标准，使用该算法时，护士的评分者间信度为0.90，儿科实习医生的评分者间信度为0.97。
TRY CPAP算法有可能成为一种简单可靠的工具，帮助护士和临床医生在资源匮乏的环境中识别需要使用CPAP治疗的新生儿。
