Neonatal sepsis prediction through clinical decision support algorithms : A systematic review

• Aim: To systematically summarise the current evidence of employing clinical decision support algorithms (CDSAs) using non-invasive parameters for sepsis prediction in neonates. Methods: A comprehensive search in PubMed, CENTRAL and EMBASE was conducted. Screening, data extraction and risk of bias were performed by two authors. The certainty of the evidence was assessed using GRADE. PROSPERO ID: CRD42020205143. Results: After abstract and full-text screening, 36 studies comprising 18,096 infants were included. Most CDSAs evaluated heart rate (HR)-based parameters. Two publications derived from one randomised-controlled trial assessing HR characteristics reported significant reduction in 30-day septicaemia-related mortality. Thirty-four non-randomised studies found promising yet inconclusive results. Conclusion: Heart rate-based parameters are reliable components of CDSAs for sepsis prediction, particularly in combination with additional vital signs and demographics. However, inconclusive evidence and limited standardisation restricts clinical implementation of CDSAs outside of a controlled research environment. Further experimentation and comparison of parameter combinations and testing of new CDSAs are warranted. 

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Pediatrik (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Pediatrics (hsv//eng)

Keyword

algorithm

clinical decision system

machine learning

neonatal sepsis

sepsis detection

C reactive protein

abdominal distension

antibiotic therapy

Apgar score

apnea

artificial ventilation

aspiration

blood culture

bloodstream infection

body temperature

bradycardia

breathing pattern

clinical assessment

clinical decision support system

clinical evaluation

clinical feature

clinical practice

coagulase negative Staphylococcus

cyanosis

data extraction

decision support system

diagnostic accuracy

endotracheal intubation

evidence based practice

funding

GRADE approach

heart rate

heart rate variability

human

hyperthermia

hypotension

hypothermia

inflammation

length of stay

lethargy

mortality rate

neonatal intensive care unit

newborn

newborn sepsis

outcome assessment

periodic breathing

pneumonia

prediction

predictive value

prematurity

prospective study

randomized controlled trial (topic)

receiver operating characteristic

resuscitation

Review

risk assessment

risk factor

seizure

septicemia

systematic review

tachycardia

tachypnea

very low birth weight

vital sign

infant

sepsis

statistical bias

Algorithms

Bias

Decision Support Systems

Clinical

Humans

Infant

Newborn

Publication and Content Type

ref (subject category)

art (subject category)