Each study was assigned to a year based on the midyear of the study. Studies were grouped based on the GBD region and 5-year time period (1990–1994; 1995–1999; 2000–2004; 2005–2009; 2010–2014; 2015–2018). If study dates were not provided, these were imputed as the publication date minus the median difference between the publication date and the mid-year for the remaining studies in the dataset.
Typhoid-specific lower breakpoints against fluoroquinolones (FQ) came into effect during our study period [24 ]. To allow the analysis of resistance trends over time, we classified ciprofloxacin intermediate (minimum inhibitory concentration (MIC) 0.12–0.5 μg/mL) and resistant S. Typhi and S. Paratyphi (MIC ≥ 1 μg/mL) according to the updated breakpoints (CLSI, 2012), as well as isolates with ‘decreased ciprofloxacin (or FQ) susceptibility’ (ciprofloxacin MIC 0.125–1.0 μg/mL) and nalidixic acid-resistant isolates (as proxy marker for ‘decreased ciprofloxacin (or fluoroquinolone) susceptibility’), as fluoroquinolone non-susceptible (FQNS). The term ‘decreased ciprofloxacin (or FQ) susceptibility’ described organisms with raised ciprofloxacin MICs that technically were not resistant due to the higher historical FQ breakpoints before 2012. If ciprofloxacin data were not available or it was not clear which breakpoints were used, nalidixic acid resistance data were used instead.
For all other antimicrobials, we classified intermediate susceptible organisms as resistant. We determined the percentage of patients with resistant S. Typhi or S. Paratyphi A isolates and used forest plots to illustrate the proportion of MDR and FQNS for each individual study; 95% confidence intervals (CI) were calculated using the Agresti-Coull method [25 ].
We combined individual studies using random effect meta-analysis to arrive at pooled prevalence rates of MDR and FQNS for each region, time period and serovar. Heterogeneity was assessed visually using forest plots and quantitatively using the I2 statistic and its associated p value [26 (link)]. In addition to the categorical data on the proportion of FQNS, we present quantitative ciprofloxacin MIC data for S. Typhi from large studies with > 90 isolates in Delhi, India. Stacked bar plots were used to illustrate changes in the distribution of ciprofloxacin MICs over the study period.
Ceftriaxone and azithromycin are recommended for the treatment of MDR and FQ-resistant enteric fever [11 ]. We also provide a descriptive analysis of ceftriaxone and azithromycin resistance as part of this review.
We used double arcsine transformation to stabilise the variance of proportions and performed random effects meta-analysis using the REML heterogeneity variance estimator [27 (link)]. Pooled prevalence was calculated for sub-groups that included at least three studies. All statistical analyses were conducted at a 5% significance level using the statistical software package ‘metafor’ in R (version 3.4.2).
Typhoid-specific lower breakpoints against fluoroquinolones (FQ) came into effect during our study period [24 ]. To allow the analysis of resistance trends over time, we classified ciprofloxacin intermediate (minimum inhibitory concentration (MIC) 0.12–0.5 μg/mL) and resistant S. Typhi and S. Paratyphi (MIC ≥ 1 μg/mL) according to the updated breakpoints (CLSI, 2012), as well as isolates with ‘decreased ciprofloxacin (or FQ) susceptibility’ (ciprofloxacin MIC 0.125–1.0 μg/mL) and nalidixic acid-resistant isolates (as proxy marker for ‘decreased ciprofloxacin (or fluoroquinolone) susceptibility’), as fluoroquinolone non-susceptible (FQNS). The term ‘decreased ciprofloxacin (or FQ) susceptibility’ described organisms with raised ciprofloxacin MICs that technically were not resistant due to the higher historical FQ breakpoints before 2012. If ciprofloxacin data were not available or it was not clear which breakpoints were used, nalidixic acid resistance data were used instead.
For all other antimicrobials, we classified intermediate susceptible organisms as resistant. We determined the percentage of patients with resistant S. Typhi or S. Paratyphi A isolates and used forest plots to illustrate the proportion of MDR and FQNS for each individual study; 95% confidence intervals (CI) were calculated using the Agresti-Coull method [25 ].
We combined individual studies using random effect meta-analysis to arrive at pooled prevalence rates of MDR and FQNS for each region, time period and serovar. Heterogeneity was assessed visually using forest plots and quantitatively using the I2 statistic and its associated p value [26 (link)]. In addition to the categorical data on the proportion of FQNS, we present quantitative ciprofloxacin MIC data for S. Typhi from large studies with > 90 isolates in Delhi, India. Stacked bar plots were used to illustrate changes in the distribution of ciprofloxacin MICs over the study period.
Ceftriaxone and azithromycin are recommended for the treatment of MDR and FQ-resistant enteric fever [11 ]. We also provide a descriptive analysis of ceftriaxone and azithromycin resistance as part of this review.
We used double arcsine transformation to stabilise the variance of proportions and performed random effects meta-analysis using the REML heterogeneity variance estimator [27 (link)]. Pooled prevalence was calculated for sub-groups that included at least three studies. All statistical analyses were conducted at a 5% significance level using the statistical software package ‘metafor’ in R (version 3.4.2).
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