Is lymphangitic streaking associated with different pathogens?

OBJECTIVES: Little is known regarding the differences in microbiology associated with cellulitis or abscess with or without lymphangitic streaking. The objective of our study is to assess whether there are differences in the pathogens identified from wound cultures of patients with paronychia with and without associated lymphangitis. METHODS: Retrospective cross-sectional study at a tertiary pediatric emergency department over 25 years. We opted to assess patients with paronychia of the finger, assuming that these cases will have a greater variety of causative pathogens compared to other cases of cellulitis and soft tissue abscess that are associated with nail biting. Case identification was conducted using a computerized text-screening search that was refined by manual chart review. We included patients from 1 month to 20 years of age who underwent an incision and drainage (I&D) of a paronychia and had a culture obtained. The presence or absence of lymphangitis was determined from the clinical narrative in the medical record. We excluded patients treated with antibiotics prior to I&D as well as immune-compromised patients. We used descriptive statistics for prevalence and χ2 tests for categorical variables. RESULTS: Two hundred sixty-six patients met inclusion criteria. The median age was 9.7 years [IQR 4.7, 15.4] and 45.1% were female. Twenty-two patients (8.3%) had lymphangitic streaking associated with their paronychia. Patients with lymphangitis streaking were similar to those without lymphangitis in terms of age and sex (p = 0.52 and p = 0.82, respectively). Overall, the predominant bacteria was MSSA (40%) followed by MRSA (26%). No significant differences were found between the pathogens in the 22 patients with associated lymphangitis compared to the 244 patients without. CONCLUSION: Staphylococcus aureus represent the majority of pathogens in paronychia, although streptococcal species and gram-negative bacteria were also common. Among patients with paronychia of the finger, there seems to be no association between pathogen type and presence of lymphangitic streaking.

Linking world bank development indicators and outcomes of congenital heart surgery in low-income and middle-income countries: retrospective analysis of quality improvement data.

OBJECTIVE: Many low-income and middle-income countries (LMICs) struggle to provide the health services investment required for life-saving congenital heart disease (CHD) surgery. We explored associations between risk-adjusted CHD surgical mortality from 17 LMICs and global development indices to identify patterns that might inform investment strategies. DESIGN: Retrospective analysis: country-specific standardised mortality ratios were graphed against global development indices reflective of wealth and healthcare investment. Spearman correlation coefficients were calculated. SETTING AND PARTICIPANTS: The International Quality Improvement Collaborative (IQIC) keeps a volunteer registry of outcomes of CHD surgery programmes in low-resource settings. Inclusion in the IQIC is voluntary enrolment by hospital sites. Patients in the registry underwent congenital heart surgery. Sites that actively participated in IQIC in 2013, 2014 or 2015 and passed a 10% data audit were asked for permission to share data for this study. 31 sites in 17 countries are included. OUTCOME MEASURES: In-hospital mortality: standardised mortality ratios were calculated. Risk adjustment for in-hospital mortality uses the Risk Adjustment for Congenital Heart Surgery method, a model including surgical risk category, age group, prematurity, presence of a major non-cardiac structural anomaly and multiple congenital heart procedures during admission. RESULTS: The IQIC registry includes 24 917 congenital heart surgeries performed in children<18 years of age. The overall in-hospital mortality rate was 5.0%. Country-level congenital heart surgery standardised mortality ratios were negatively correlated with gross domestic product (GDP) per capita (r=-0.34, p=0.18), and health expenditure per capita (r=-0.23, p=0.37) and positively correlated with under-five mortality (r=0.60, p=0.01) and undernourishment (r=0.39, p=0.17). Countries with lower development had wider variation in mortality. GDP per capita is a driver of the association between some other measures and mortality. CONCLUSIONS: Results display a moderate relationship among wealth, healthcare investment and malnutrition, with significant variation, including superior results in many countries with low GDP per capita. These findings provide context and optimism for investment in CHD procedures in low-resource settings.