Results
Baseline characters of participants
The baseline characters of participants are summarized in Tab 1.
Thoroughtout the study(Fig 1.B), 322 infants developed symptoms or signs
in the monitoring room. All of them were performed LUS, and clinic data
were collected. Twelve of them were excluded according to criteria(4
with complex malformation or congenital lung diseases, 3 were
transferred to another hospital; 5 without qualified LUS images). 310
infants enrolled in total, and their LUS images were obtained at one of
following timing—-(67, 85, 92, 37, 29 infants; respectively at
0.5h, 1h, 2h, 4h, 6h after birth). After three-day follow, 236 infants
were confirmed to be healthy, 74 were admitted to NICU due to pulmonary
issues, including RDS(28/74), TTN(31/74), pneumonia(6/74) and MAS(6/74).
The GA range was 34w+0d to 41w+5d, and the birth weight range was 1990g
to 4520g. Most patients and healthy infants were scanned at the timing
of 2 hours after birth. Patients were more likely to have a higher
respiratory rate(65(87.8%) vs 57(24.2%), p<0.01) and higher
incidence of lower TcSO2(bellow 95% for more than 3 mins, 23(31.1%) vs
18(7.6%), p<0.01).
High-risk patterns and Low-risk patterns
There are six LUS image patterns can be found in these late preterm and
term infants right after their birth(Fig 2). These patterns can be
categorized as ”High-risk” and ”Low-risk” ones. The low-risk patterns,
which means less likelihood of lung issues, include ”pure A-line”
pattern, ”Scarce discrete B-line” pattern, ”Moderate discrete B-line”
pattern, and ”Abundant discrete B-line”. In fact, the three kinds of
”discrete B-line” can be easily discerned when performing LUS and there
is no need to identify each of them, as they are significantly different
from ”pure A-line” and high-risk patterns, and they are less likely to
be a sign of lung issues. High-risk patterns inlude ”Coalesced B-line”
and ”Consolidation”.
The reliability of LUS to predict respiratory support in late preterm
and term infants
The ROC analysis for any respiratory support needs using High-risk
patterns yielded an AUC of 0.95(95%CI, 0.92-0.98, p<0.001).
Correspondingly, the ROC analysis for any respiratory support needs
using Low-risk patterns yielded an AUC of 0.89(95%CI, 0.85-0.93,
p<0.001). By contrast, as for RR(respiratory rate) which we
used conventionally to predict respiratory support need, its ROC only
yield an AUC of 0.70(95%CI, 0.64-0.76, p<0.001). The ROC of
LUS(high-patterns) and RR have a significant
difference(p<0.01)(Fig 3). Table 2 shows reliability data for
LUS and RR to predict any need for respiratory support. The ROC analysis
for the subgroups also was conducted, and the result of hood oxygen
support was shown(Tab 2), but due to an insufficient number of patients
who only obtained CPAP, MV, and PS treatment(23/74, 18/74, 29/74,
individually), the ROC for they may not reliable and results were not
shown.