Nosocomial Sepsis Risk Score for Preterm Infants in Low-resource Settings

Rosenberg, Rebecca E.; Ahmed, Asm Nawshad Uddin; Saha, Samir K.; Chowdhury, Mak Azad; Ahmed, Saifuddin; Law, Paul A.; Black, Robert E.; Santosham, Mathuram

doi:10.1093/tropej/fmp061

Cited by 31 publications

(35 citation statements)

References 36 publications

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“…Figure 1 shows the results of the search strategy. The research period spanned from 1993 to 2007 with 3 western European, [27][28][29] 4 South Asian, [30][31][32][33] 1 Canadian, 34 and 1 Turkish study. 35 All researches were performed in level III settings of which one 33 was conducted in a low-resource level III hospital.…”

Section: Resultsmentioning

confidence: 99%

“…In particular, the definitions of the clinical signs and the interobserver variability in interpretation might be a medium risk for bias. Two studies 29,33 had no validation cohort but used a bootstrapping statistical technique for internal validation. Most studies defined the time of assessment as "day of sepsis workup," so a time frame for data collection of a maximum of 24 hours preceding sepsis workup is acknowledged.…”

Section: Methodologic Quality Of the Included Studiesmentioning

confidence: 99%

“…Pretest probability of sepsis ranged between 17% to 55%, indicating an important variation in study population. Three studies did not include all neonates with suspicion of sepsis in their research; selection was made for neonates with gestational age ,34 weeks 29,33 and for birth weight $1000 g and #2500 g. 32 One study 35 did not report information on patient characteristics but did focus on nosocomial sepsis in neonates on neonatal intensive care. Two studies were internal 34 and external validation studies 28 of their former developed prediction score study.…”

Section: General Description Of the Included Studiesmentioning

confidence: 99%

“…Two studies were internal 34 and external validation studies 28 of their former developed prediction score study. Another 2 studies 32,33 are adapted external validation studies of Singh et al 30 …”

Section: General Description Of the Included Studiesmentioning

confidence: 99%

“…Figure 3 displays the forest plots of the 5 significant clinical parameters predictive for HABSI in neonates. Because 10 of 18 clinical parameters exposed medium to high statistical heterogeneity, a post hoc analysis was performed with 2 studies, 29,33 including solely low gestational age neonates (,34 weeks) and 9 clinical signs. Pooled OR and statistical heterogeneity of these 9 signs are tabulated in Table 4.…”

Section: Characteristics and Diagnostic Accuracy Of The Prediction Momentioning

confidence: 99%

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Prediction Models for Neonatal Health Care–Associated Sepsis: A Meta-analysis

et al. 2015

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BACKGROUND AND OBJECTIVES: Blood culture is the gold standard to diagnose bloodstream infection but is usually time-consuming. Prediction models aim to facilitate early preliminary diagnosis and treatment. We systematically reviewed prediction models for health care-associated bloodstream infection (HABSI) in neonates, identified superior models, and pooled clinical predictors. Data sources: LibHub, PubMed, and Web of Science. METHODS:The studies included designed prediction models for laboratory-confirmed HABSI or sepsis. The target population was a consecutive series of neonates with suspicion of sepsis hospitalized for $48 hours. Clinical predictors had to be recorded at time of or before culturing. Methodologic quality of the studies was assessed. Data extracted included population characteristics, total suspected and laboratory-confirmed episodes and definition, clinical parameter definitions and odds ratios, and diagnostic accuracy parameters. RESULTS:The systematic search revealed 9 articles with 12 prediction models representing 1295 suspected and 434 laboratory-confirmed sepsis episodes. Models exhibit moderate-good methodologic quality, large pretest probability range, and insufficient diagnostic accuracy. Random effects meta-analysis showed that lethargy, pallor/mottling, total parenteral nutrition, lipid infusion, and postnatal corticosteroids were predictive for HABSI. Post hoc analysis with low-gestational-age neonates demonstrated that apnea/bradycardia, lethargy, pallor/mottling, and poor peripheral perfusion were predictive for HABSI. Limitations include clinical and statistical heterogeneity.CONCLUSIONS: Prediction models should be considered as guidance rather than an absolute indicator because they all have limited diagnostic accuracy. Lethargy and pallor and/or mottling for all neonates as well as apnea and/or bradycardia and poor peripheral perfusion for very low birth weight neonates are the most powerful clinical signs. However, the clinical context of the neonate should always be considered.

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Section: Resultsmentioning

confidence: 99%

Section: Methodologic Quality Of the Included Studiesmentioning

confidence: 99%

Section: General Description Of the Included Studiesmentioning

confidence: 99%

Section: General Description Of the Included Studiesmentioning

confidence: 99%

Section: Characteristics and Diagnostic Accuracy Of The Prediction Momentioning

confidence: 99%

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Prediction Models for Neonatal Health Care–Associated Sepsis: A Meta-analysis

et al. 2015

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Impact of early kangaroo mother care versus standard care on survival of mild-moderately unstable neonates <2000 grams: A randomised controlled trial

Brotherton¹,

Gai²,

Kebbeh³

et al. 2021

EClinicalMedicine

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Background Understanding the effect of early kangaroo mother care on survival of mild-moderately unstable neonates <2000 g is a high-priority evidence gap for small and sick newborn care. Methods This non-blinded pragmatic randomised clinical trial was conducted at the only teaching hospital in The Gambia. Eligibility criteria included weight <2000g and age 1–24 h with exclusion if stable or severely unstable. Neonates were randomly assigned to receive either standard care, including KMC once stable at >24 h after admission (control) versus KMC initiated <24 h after admission (intervention). Randomisation was stratified by weight with twins in the same arm. The primary outcome was all-cause mortality at 28 postnatal days, assessed by intention to treat analysis. Secondary outcomes included: time to death; hypothermia and stability at 24 h; breastfeeding at discharge; infections; weight gain at 28d and admission duration. The trial was prospectively registered at www.clinicaltrials.gov (NCT03555981). Findings Recruitment occurred from 23rd May 2018 to 19th March 2020. Among 1,107 neonates screened for participation 279 were randomly assigned, 139 (42% male [ n = 59]) to standard care and 138 (43% male [ n = 59]) to the intervention with two participants lost to follow up and no withdrawals. The proportion dying within 28d was 24% (34/139, control) vs. 21% (29/138, intervention) (risk ratio 0·84, 95% CI 0·55 – 1·29, p = 0·423). There were no between-arm differences for secondary outcomes or serious adverse events (28/139 (20%) for control and 30/139 (22%) for intervention, none related). One-third of intervention neonates reverted to standard care for clinical reasons. Interpretation The trial had low power due to halving of baseline neonatal mortality, highlighting the importance of implementing existing small and sick newborn care interventions. Further mortality effect and safety data are needed from varying low and middle-income neonatal unit contexts before changing global guidelines.

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