Калькулятор риска развития раннего сепсиса и назначение антибактериальной терапии у новорожденных.
В мета-анализе, опубликованном в JAMA Pediatrics, исследователи изучали, снижается ли вероятность назначения эмпирической антибактериальной терапии у новорожденных с подозрением на сепсис при использовании калькулятора риска развития раннего сепсиса.
Калькулятор риска развития раннего сепсиса у новорождённых (The neonatal early-onset sepsis (EOS) calculator) представляет собой инструмент стратификации клинического риска, который все чаще используется как руководство к эмпирическому назначению антибиотиков у новорожденных, родившихся в срок ≥ 34 недель беременности.
EOS калькулятор был разработан учёными неонатологического отделения Brigham and Women's Hospital в Бостоне в 2011 году. Он включает в основном материнские факторы, такие как срок беременности, температура матери в родах, результаты посева на стрептококк из влагалища. Существует его интернет версия: https://neonatalsepsiscalculator.kaiserpermanente.org/#
Было проанализировано 13 соответствующих исследований, включавших в общей сложности 175 752 историй болезни новорожденных из баз данных MEDLINE, Embase, Web of Science и Google Scholar в период с 2011 года до 31 января 2019 года.
Все исследования подтвердили значительно более низкий процент назначения эмпирической антибактериальной терапии в случаях использовании калькулятора EOS у новорождённых c подозрением на сепсис, в среднем на 56%.
Исследователи также ставили целью оценить безопасность использования калькулятора. Связанные с безопасностью результаты включали пропущенные случаи раннего сепсиса, повторные поступления в стационар, задержку лечения, заболеваемость и смертность. Доказательства по безопасности были ограничены, но доли пропущенных случаев сепсиса были сопоставимы в случае использования калькулятора (5 из 18 или 28%) и среди новорождённых, в ведении которых калькулятор не применялся (8 из 28 или 29%).
Источники: https://jamanetwork.com/journals/jamapediatrics/article-abstract/2748691
Association of Use of the Neonatal Early-Onset Sepsis Calculator With Reduction in Antibiotic Therapy and Safety: A Systematic Review and Meta-analysis.
Achten NB et al
IMPORTANCE:
The neonatal early-onset sepsis (EOS) calculator is a clinical risk stratification tool increasingly used to guide the use of empirical antibiotics for newborns. Evidence on the effectiveness and safety of the EOS calculator is essential to inform clinicians considering implementation.
OBJECTIVE:
To assess the association between management of neonatal EOS guided by the neonatal EOS calculator (compared with conventional management strategies) and reduction in antibiotic therapy for newborns.
DATA SOURCES:
Electronic searches in MEDLINE, Embase, Web of Science, and Google Scholar were conducted from 2011 (introduction of the EOS calculator model) through January 31, 2019.
STUDY SELECTION:
All studies with original data that compared management guided by the EOS calculator with conventional management strategies for allocating antibiotic therapy to newborns suspected to have EOS were included.
DATA EXTRACTION AND SYNTHESIS:
Following PRISMA-P guidelines, relevant data were extracted from full-text articles and supplements. CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies) and GRADE (Grades of Recommendation, Assessment, Development and Evaluation) tools were used to assess the risk of bias and quality of evidence. Meta-analysis using a random-effects model was conducted for studies with separate cohorts for EOS calculator and conventional management strategies.
MAIN OUTCOMES AND MEASURES:
The difference in percentage of newborns treated with empirical antibiotics for suspected or proven EOS between management guided by the EOS calculator and conventional management strategies. Safety-related outcomes involved missed cases of EOS, readmissions, treatment delay, morbidity, and mortality.
RESULTS:
Thirteen relevant studies analyzing a total of 175 752 newborns were included. All studies found a substantially lower relative risk (range, 3%-60%) for empirical antibiotic therapy, favoring the EOS calculator. Meta-analysis revealed a relative risk of antibiotic use of 56% (95% CI, 53%-59%) in before-after studies including newborns regardless of exposure to chorioamnionitis. Evidence on safety was limited, but proportions of missed cases of EOS were comparable between management guided by the EOS calculator (5 of 18 [28%]) and conventional management strategies (8 of 28 [29%]) (pooled odds ratio, 0.96; 95% CI, 0.26-3.52; P = .95).
CONCLUSIONS AND RELEVANCE:
Use of the neonatal EOS calculator is associated with a substantial reduction in the use of empirical antibiotics for suspected EOS. Available evidence regarding safety of the use of the EOS calculator is limited, but shows no indication of inferiority compared with conventional management strategies.
Estimating the probability of neonatal early-onset infection on the basis of maternal risk factors.
Puopolo KM et al
OBJECTIVE:
To develop a quantitative model to estimate the probability of neonatal early-onset bacterial infection on the basis of maternal intrapartum risk factors.
METHODS:
This was a nested case-control study of infants born at ≥34 weeks' gestation at 14 California and Massachusetts hospitals from 1993 to 2007. Case-subjects had culture-confirmed bacterial infection at <72 hours; controls were randomly selected, frequency-matched 3:1 according to year and birth hospital. We performed multivariate analyses and split validation to define a predictive model based only on information available in the immediate perinatal period.
RESULTS:
We identified 350 case-subjects from a cohort of 608,014 live births. Highest intrapartum maternal temperature revealed a linear relationship with risk of infection below 100.5°F, above which the risk rose rapidly. Duration of rupture of membranes revealed a steadily increasing relationship with infection risk. Increased risk was associated with both late-preterm and postterm delivery. Risk associated with maternal group B Streptococcus colonization is diminished in the era of group B Streptococcus prophylaxis. Any form of intrapartum antibiotic given >4 hours before delivery was associated with decreased risk. Our model showed good discrimination and calibration (c statistic = 0.800 and Hosmer-Lemeshow P = .142 in the entire data set).
CONCLUSIONS:
A predictive model based on information available in the immediate perinatal period performs better than algorithms based on risk-factor threshold values. This model establishes a prior probability for newborn sepsis, which could be combined with neonatal physical examination and laboratory values to establish a posterior probability to guide treatment decisions.