| Literature DB >> 33017418 |
Yefang Ke1, Wenbo Lu1, Wenyuan Liu1, Pan Zhu2, Qunying Chen1, Zhe Zhu3,4.
Abstract
BACKGROUND: Non-typhoidal Salmonella (NTS), a common cause of diarrheal enterocolitis, may also cause severe invasive diseases. Limited information on NTS infections in children is available in China.Entities:
Mesh:
Substances:
Year: 2020 PMID: 33017418 PMCID: PMC7561262 DOI: 10.1371/journal.pntd.0008732
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Fig 1Distribution of the 166 NTS infection cases by year of admission and invasiveness.
The bar chart shows the number of NTS infection cases hospitalized in Ningbo in each year from 2012 to 2019, according to the invasive or non-invasive status of infections. Abbreviations: NTS = non-typhoidal Salmonella.
Distribution of 166 NTS isolates by invasive or non-invasive infection status and serotype, Ningbo, China, 2012–2019.
| Serotype | No. (%) of isolates from NTS infections (n = 166) | No. (%) of isolates from iNTS infections (n = 11) | No. (%) of isolates from non-iNTS infections (n = 155) | Invasiveness |
|---|---|---|---|---|
| Typhimurium | 104 (62.6%) | 2 (18.2%) | 102 (65.8%) | 1.9% |
| Dublin | 13 (7.8%) | 1 (9.1%) | 12 (7.7%) | 7.7% |
| Enteritidis | 8 (4.8%) | 1 (9.1%) | 7 (4.5%) | 12.5% |
| Choleraesuis | 6 (3.6%) | 1 (9.1%) | 5 (3.2%) | 16.7% |
| Bovis-morbificans | 5 (3.0%) | 1 (9.1%) | 4 (2.6%) | 20.0% |
| Untyped | 5 (3.0%) | 3 (27.3%) | 2 (1.3%) | 60.0% |
| 25 (15.1%) | 2 (18.2%) | 23 (14.8%) | 8.0% |
Abbreviations: NTS = non-typhoidal Salmonella, iNTS = invasive non-typhoidal Salmonella, non-iNTS = non-invasive non-typhoidal Salmonella
NTS with ≥5 isolates were listed individually, and those with <5 isolates were listed in the “other” category.
a Proportion of iNTS infections to the total number of NTS infections in that serotype.
Demographic, residential and clinical manifestations of children with NTS infections, Ningbo, China, 2012–2019.
| Characteristic | iNTS infections (n = 11) | Non-iNTS infections (n = 155) | Bivariate analysis | Multivariate analysis | ||
|---|---|---|---|---|---|---|
| OR (95%CI) | aOR (95%CI) | |||||
| Male | 7 (63.6%) | 93 (60.0%) | 0.812 | 1.167(0.328–4.154) | ||
| Age, months (IQR) | 13(6–93) | 13(8–21) | 0.915 | - | ||
| Age ≤6 months | 5 (45.5%) | 27 (17.4%) | 0.032 | 3.951(1.124–13.890) | 0.040 | 4.508(1.069–19.016) |
| Rural | 3 (27.3%) | 63 (40.6%) | 0.387 | 0.548(0.140–2.144) | ||
| Hb (mean ± SD) | 11.6±1.6 | 11.8±1.3 | 0.737 | 0.924(0.583–1.465) | ||
| Anemia (Hb <11.0 g/dL) | 5 (45.5%) | 43 (27.7%) | 0.220 | 2.171(0.629–7.484) | ||
| Severe anemia | 0 | 0 | - | - | ||
| Fever | 9 (81.8%) | 134 (86.5%) | 0.669 | 0.705(0.142–3.492) | ||
| Diarrhea | 6 (54.5%) | 144 (92.9%) | <0.001 | 0.092(0.024–0.349) | 0.020 | 0.170(0.038–0.760) |
| Bloody stools | 6 (54.5%) | 120 (77.4%) | 0.098 | 0.350(0.101–1.216) | ||
| Vomiting | 6 (54.5%) | 62 (40.0%) | 0.349 | 1.800(0.526–6.155) | ||
| Convulsion | 2 (18.2%) | 15 (9.7%) | 0.378 | 2.074(0.410–10.502) | ||
| Respiratory tract infection | 5 (45.5%) | 46 (29.7%) | 0.281 | 1.975(0.574–6.795) | ||
| Gastrointestinal virus infection | 1 (9.1%) | 19 (12.3%) | 0.756 | 0.716(0.087–5.910) | ||
| Leukemia | 2 (18.2%) | 1 (0.6%) | 0.005 | 34.222(2.829–413.913) | 0.023 | 27.148(1.576–467.616) |
All data of 166 children were available.
Abbreviations: NTS = non-typhoidal Salmonella, iNTS = invasive non-typhoidal Salmonella, non-iNTS = non-invasive non-typhoidal Salmonella, OR = odds ratio, aOR = adjusted odds ratio, 95%CI = 95% confidence interval
a Mann-Whitney test was used to calculate P value (other variables: logistic regression)
- Not performed or predicts failure perfectly.
Antibiotic resistance among iNTS and non-iNTS infections, Ningbo, China, 2012–2019.
| Antibiotic Resistance Type | iNTS infections (n = 11) | Non-iNTS infections (n = 155) | OR (95%CI) | |
|---|---|---|---|---|
| Agents | ||||
| Ampicillin | 7 (63.6%) | 123 (79.4%) | 0.281 | 0.495(0.138–1.777) |
| Ampicillin/sulbactam | 6 (54.5%) | 115 (74.2%) | 0.184 | 0.434(0.126–1.488) |
| Piperacillin/tazobactam | 0 (0.0%) | 10 (6.5%) | 0.386 | - |
| Ceftazidime | 0 (0.0%) | 42 (27.1%) | 0.046 | - |
| Ceftriaxone | 0 (0.0%) | 58 (37.4%) | 0.012 | - |
| Cefepime | 0 (0.0%) | 43 (27.7%) | 0.043 | - |
| Aztreonam | 0 (0.0%) | 49 (31.6%) | 0.027 | - |
| Ertapenem | 0 (0.0%) | 2 (1.3%) | 0.706 | - |
| Imipenem | 0 (0.0%) | 2 (1.3%) | 0.706 | - |
| Ciprofloxacin | 0 (0.0%) | 32 (20.6%) | 0.094 | - |
| Levofloxacin | 1 (9.1%) | 35 (22.6%) | 0.314 | 0.343(0.043–2.757) |
| TMP-SMX | 2 (18.2%) | 48 (31.0%) | 0.358 | 0.480(0.100–2.295) |
| Nitrofurantoin | 4 (36.4%) | 46 (29.7%) | 0.654 | 1.337(0.375–4.760) |
| 0 class (no resistant) | 3(27.3%) | 20(12.9%) | Reference | |
| 1 class | 2(18.2%) | 12(7.7%) | 0.915 | 1.111(0.162–7.632) |
| 2 classes | 1(9.1%) | 21(13.5%) | 0.337 | 0.317(0.030–3.311) |
| 3 classes | 4(36.4%) | 27(17.4%) | 0.988 | 0.988(0.198–4.915) |
| ≥ 4 classes | 1(9.1%) | 75(48.3%) | 0.041 | 0.089(0.009–0.901) |
| 0 agent (no resistant) | 4(36.4%) | 27(17.4%) | Reference | |
| 1 agent | 5(45.5%) | 43(27.7%) | 0.735 | 0.785(0.194–3.183) |
| ≥2 agents | 2(18.2%) | 85(54.8%) | 0.040 | 0.159(0.028–0.916) |
All antibiotic resistance data of 166 isolates were available
Abbreviations: NTS = non-typhoidal Salmonella, iNTS = invasive non-typhoidal Salmonella, non-iNTS = non-invasive non-typhoidal Salmonella, OR = odds ratio, CI = confidence interval
a Resistant to single antimicrobials, 1 class, 2 classes, 3 classes, ≥4 classes and 1or more agents of first-line agents, resistance was defined as an intermediate or resistant minimum inhibitory concentration. (intermediate inhibitory concentration to ciprofloxacin, was evaluated as 0.25–0.5 μg/mL.)
b Fisher exact test was used to calculate P value (other variables: logistic regression)
c Based on 166 NTS isolates with complete information for all the tested antibiotics.
d First-line agents: ampicillin, ceftriaxone, ciprofloxacin, or TMP-SMX.
- Predicts failure perfectly.
Fig 2Drug resistance trends (resistant to≥ 4 CLSI classes and ≥2 first-line agents) of 166 Salmonella isolates in Ningbo,2012–2019.
The percentage of resistance (%) over the 8-year study period in Ningbo is shown in the line graph.
Fig 3Distribution of 166 NTS infection cases and average monthly rainfall in Ningbo, 2012–2019.
The bar chart shows the distribution of the 166 NTS infection cases according to the month of admission. The average monthly rainfall over the 8-year study period in Ningbo is shown in the line graph. Abbreviations: NTS = non-typhoidal Salmonella, Jan = January, Feb = February, Mar = March, Apr = April, Jun = June, Jul = July, Aug = August, Sep = September, Oct = October, Nov = November, Dec = December.
Fig 4Distribution of the 166 NTS infection cases and average seasonal temperature in Ningbo, 2012–2019.
The bar chart shows the distribution of the 166 NTS infection cases according to the admission. The average seasonal temperature over the 8-year study period in Ningbo is shown in the line graph. Difference in seasonal numbers of NTS infections: P<0.01 vs winter, P<0.001 vs winter, ## P <0.01 vs spring, ### P <0.001 vs spring, Abbreviations: NTS = non-typhoidal Salmonella.