Studies focusing on bone and joint infections (BJIs) in young infants are rare. Some cases of BJI are accompanied by sepsis. This study aimed to identify the clinical and bacteriological features of sepsis in neonates and young infants with BJIs. Neonates and infants younger than 3 months diagnosed with BJI in the present institution from 2014 to 2021 were retrospectively reviewed. Patient characteristics, clinical data, and outcomes were documented and compared between those with and without sepsis. Twenty-five patients with a mean age of 34.8 days were included. Nine BJI cases had concomitant sepsis (group A), and 16 had BJI without sepsis (group B). Within group A, staphylococcus aureus was the major pathogenic germ (5 cases, of which 4 were of the methicillin-resistant staphylococcus aureus (MRSA) type). There was no statistical difference in male-to-female ratio, age, history of hospitalization, anemia, birth asphyxia, peripheral leukocyte counts, C-reactive protein on admission, and sequelae between groups. Univariate analyses indicated a significant difference in the incidence of septic arthritis (SA) combined with osteomyelitis (OM) (88.9% vs 37.5%), congenital deformities (44.4% vs 0%), and mean duration of symptoms (2.83 days vs 9.21 days) in comparisons between groups A and B. Staphylococcus aureus is the main pathogenic bacteria in BJI cases complicated with sepsis in neonates and young infants. Among infants younger than 3 months diagnosed with BJI, those with concurrent SA and OM, MRSA infection, or congenital deformities are more likely to develop sepsis.

Models for reconstructing seismic response demands across multiple buildings can aid in cluster-level rapid postearthquake damage assessment. Response demands from 188 buildings affected by 25 earthquakes were used to develop a cross-building response reconstruction model. A structural response prediction model (SRPM) was developed, which is based on a modern ground motion model with added “building response” terms. A kriging algorithm is used to interpolate the within-event residuals which, together with the SRPM, form a generalized cross-building response reconstruction (CBRR) model. Given the recorded responses for a subset of instrumented buildings in a cluster, the demands in the uninstrumented buildings can be reconstructed by combining the median values generated from the SRPM and estimated within-event residuals for a given site obtained from the kriging model.