The authors have declared that no competing interests exist.
Conceived and designed the experiments: PDJ JT. Performed the experiments: PDJ JT. Analyzed the data: PDJ TC. Contributed reagents/materials/analysis tools: OP. Wrote the paper: PDJ JT OP TC SN.
New Delhi metallo-β-lactamase (NDM)-producing Gram-negative bacteria have spread globally and pose a significant public health threat. There is a need to better define risk factors and outcomes of NDM-1 clinical infection. We assessed risk factors for nosocomial infection with NDM-1-producers and associated in-hospital mortality.
A matched case-control study was conducted during a nosocomial outbreak of NDM-1-producers in an adult intensive care unit (ICU) in South Africa. All patients from whom NDM-1-producers were identified were considered (n=105). Cases included patients admitted during the study period in whom NDM-1 producing Gram-negative bacteria were isolated from clinical specimens collected ≥48 hours after admission, and where surveillance definitions for healthcare-associated infections were met. Controls were matched for age, sex, date of hospital admission and intensive-care admission. Conditional logistic regression was used to identify risk factors for NDM-1 clinical infection and associated in-hospital mortality.
38 cases and 68 controls were included.
NDM-1 infection is associated with significant in-hospital mortality. Risk factors for hospital-associated infection include the presence of co-morbid disease, mechanical ventilation and piperacillin/tazobactam exposure.
Resistance to β-lactams is a long recognised problem in Gram-negative bacteria[
In 2008 a novel metallo-β-lactamase designated New Delhi metallo-β-lactamase (NDM-1) was identified in a Swedish patient returning from India.[
With limited treatment options available, slowing and preventing the spread of
Study participant age ranged from 20 years to 90 years, with a mean age of 61.3 and a median age of 64. Verbal informed consent was obtained from all patients or their next of kin prior to conducting telephonic interviews which collected information on past hospitalization/chronic care admission and travel history. Verbal consent was obtained as this was a retrospective study and patients had subsequently relocated to various parts of the country. Consent was captured on a consent form by the researchers. Consent to review clinical records were obtained from the hospital and all patient data were anonymized and de-linked from unique identifiers prior to analysis. Ethics approval for this study, including the consent procedure, was obtained from the Human Research Ethics Committee (Medical) at the University of the Witwatersrand, Johannesburg. (M130248)
The outbreak occurred across three private hospitals in South Africa with strong referral links. This study was confined to the hospital where the majority of cases (90/105, 86%) were detected, and all cases and controls were from the adult ICU. The hospital is located in the greater Johannesburg area, has a total of 322 beds including a 37-bed ICU, and offers tertiary-level specialist care.
In early August 2011
All microbiological testing was conducted in routine private diagnostic laboratories servicing the private healthcare sector. Thirteen NDM-positive isolates (seven case isolates and six epidemiologically linked environmental specimens collected in the adult ICU) were subjected to DNA fingerprinting by macro-restriction analysis on pulsed-field gel electrophoresis (PFGE) at the Infection Control Services Laboratory, National Health Laboratory Services. PFGE was performed as described previously.[
The study design is summarized in
NDM-1 = New Delhi metallo-β-lactamase; RT-PCR = real-time polymerase chain reaction testing.
All patients admitted between 1 July 2011 and 31 October 2012 were eligible for inclusion. We included cases where
No controls could be found meeting the matching criteria for two cases and for three cases only two matching controls could be identified. Another 52 controls were excluded for missing/incomplete medical records (n = 26), record of screening NDM-1 positive on dry rectal swab (n = 13) or being admitted for less than 48 hours (n = 13). The final sample consisted of 38 cases and 68 controls.
Clinical data were collected for cases and controls from clinical records, laboratory results and hospital billing data. Exposure to antibiotics (carbapenems, aminoglycosides, fluoroquinolones, third- and fourth-generation cephalosporins, and piperacillin/tazobactam) and corticosteroids were recorded as total number of doses received. Exposure to medical devices (central venous line and indwelling urinary catheter) as well as selected medical interventions (haemodialysis, mechanical ventilation and parenteral nutrition) was recorded as total number of days exposed. Patients who underwent laparotomy or thoracotomy were grouped and compared to patients who received other (mainly orthopaedic) or no surgery. Co-morbid disease and severity of illness on admission was measured by calculating Charlson co-morbidity index and Mortality Probability Model III (MPM III) scores respectively.[
Data on past hospital or long-term care facility admission and international travel history in the year leading up to the admission of interest were collected through telephonic interviews for both cases and controls. All data were collected between November 2012 and November 2013 by trained professional nurses and medical doctors.
We evaluated risk factors associated with case status and compared in-hospital mortality between cases and controls. Except for MPM-III scores, where its calculation would have been invalid, there was no missing clinical data in the final sample used for analysis. Where past admission, travel history or MPM-III scores were missing, observations were excluded from the analysis.
Data were entered into Epi-Info version 7 and exported to Excel 2007 where it was inspected for errors before being imported to Stata Version 12 for statistical analysis. Continuous variables such as length of hospital stay, MPM-III and Charlson scores, are described through the reporting of means and standard deviations. Two sided t-test for two groups (cases and controls) was used to compare means of continuous variables with normal distributions. Where data were not normally distributed Mann-Whitney U test was used. For differences in proportions such as previous hospitalisation or travel history, Mantel–Haenszel Chi square test was used. Bivariate conditional logistic regression analysis was undertaken to calculate crude odds ratio’s for exposure to medical devises and interventions, antibiotics and duration of stay. Stepwise conditional logistic regression was conducted to identify factors associated with case status. All exposure variables with a
The most common NDM-1-producing isolate among the 38 cases was
PFGE showed two closely related clusters: cluster A comprised three case isolates and six environmental isolates, whilst cluster B comprised three case isolates. Given the protracted course of the outbreak, this suggests that these isolates are all related.[
Cases had a longer mean total length of hospital stay (44.0 vs 13.3 days,
Variable | Cases (n = 38) Mean (SD) | Controls(n = 68) Mean (SD) | |
---|---|---|---|
Time at risk (total, days) | 22.2 (±15.8) | 13.3 (±9.5) | |
Time at risk (intensive care, days) | 18.9 (±13.7) | 8.3 (±7.2) | |
Total length of stay (days) | 44.0 (±28.2) | 13.3 (±9.5) | |
Total length of ICU stay (days) | 32.5 (±27.0) | 8.3 (±7.2) | |
MPM III Score (%) | 11.5 (±7.1) | 8.3 (±6.8) | 0.072 |
Age Adjusted Charlson Score | 5.2 (±3.1) | 4.1 (±2.2) |
SD = standard deviation; time at risk: from admission to discharge/death (controls) or NDM-1 diagnosis (cases); MPM-III = Mortality Probability Model III; total length of stay: time from admission to discharge/death;
Cases had significantly higher odds of having been hospitalised or admitted to a long-term care facility in the previous year (OR 6.83; 95% CI 2.32–20.16) or being transferred from a referral hospital (OR 4.98; 95% CI 1.56–15.93) compared to controls (
Exposure Variable | Case patient (n = 38)with exposure | Control patient (n = 68) with exposure | Unadjusted OR(95%CI) | |||
---|---|---|---|---|---|---|
Number | % | Number | % | |||
Previous Hospitalization/Chronic care | ||||||
No | 10 | 29 | 40 | 83 | 1 | |
Yes | 24 | 71 | 8 | 17 | 6.83 (2.32–20.16) | |
Travel outside South Africa | ||||||
No | 30 | 94 | 47 | 98 | 1 | |
Yes | 2 | 6 | 1 | 2 | 3.24 (0.29–36.63) | 0.343 |
Transfer from referral hospital | ||||||
No | 23 | 61 | 60 | 88 | 1 | |
Yes | 15 | 39 | 8 | 12 | 4.98 (1.56–15.93) | |
HIV Status | ||||||
HIV negative | 34 | 89 | 63 | 93 | 1 | |
HIV positive | 4 | 11 | 5 | 7 | 1.53 (0.29–8.11) | 0.615 |
Time at risk (total) | ||||||
≤ 14 days | 17 | 45 | 44 | 65 | 1 | |
> 14 days | 21 | 55 | 24 | 35 | 2.12 (0.97–4.62) | 0.059 |
Time at risk (intensive care) | ||||||
1–7 days | 9 | 24 | 40 | 59 | 1 | |
>7 days | 29 | 76 | 28 | 41 | 4.82 (1.80–12.91) | |
Surgery |
||||||
No | 14 | 37 | 33 | 49 | 1 | |
Yes | 24 | 63 | 35 | 51 | 1.60 (0.72–3.56) | 0.254 |
Exposure to antibiotics |
||||||
No | 5 | 13 | 27 | 40 | 1 | |
Yes | 33 | 87 | 41 | 60 | 4.77 (1.38–16.48) |
*Refers to laparotomy or thoracotomy;
**Refers to receiving any dose or either a carbapenem or fluoroquinolone or aminoglycoside or third/fourth generation cephalosporin or piperacillin/tazobactam;
OR = odds ratio
On univariate analysis exposure to aminoglycosides, piperacillin/tazobactam and corticosteroids were significantly associated with case status (
Exposure Variable | Case patient (n = 38) with exposure | Control patient (n = 68) with exposure | Crude OR (95%CI) | |
---|---|---|---|---|
mean (SD) | mean (SD) | |||
Aminoglycosides (dose, any) | 10.42 (±22.53) | 2.43 (±10.23) | 1.03 (1.00–1.06) | |
Gentamycin | 0.97 (±5.35) | 0.25 (±1.74) | 1.07 (0.93–1.23) | 0.320 |
Amikacin | 7.29 (±18.79) | 2.17 (±10.05) | 1.02 (0.99–1.06) | 0.125 |
Tobramycin | 2.16 (±13.30) | 0 (±0) | - | - |
Fluoroquinolone (dose, any) | 1.53 (±3.75) | 0.91(±2.76) | 1.09 (0.96–1.24) | 0.162 |
Ciprofloxacin | 0.71 (±3.02) | 0.16 (±1.00) | 1.19 (0.90–1.57) | 0.234 |
Levofloxacin | 0.66 (±2.33) | 0.49 (±2.32) | 1.07 (0.91–1.26) | 0.429 |
Moxifloxacin | 0.15 (±0.97) | 0.26 (±1.32) | 0.96 (0.67–1.38) | 0.830 |
Carbapenem (dose, any) | 16.08(±29.93) | 5.59(±11.97) | 1.02 (1.00–1.05) | 0.062 |
Doripenem | 6.16 (±18.43) | 0.15(±1.21) | 1.18 (0.96–1.46) | 0.117 |
Ertapenem | 1.39 (±4.03) | 1.22 (±3.56) | 0.99 (0.88–1.12) | 0.930 |
Meropenem | 8.52 (±16.74) | 4.22 (±11.17) | 1.02 (0.99–1.05) | 0.175 |
Cephalosporin (dose, any) | 2.5 (±7.07) | 2.19 (±6.0) | 1.00 (0.94–1.06) | 0.992 |
Cefepime | 1.68 (±6.43) | 0.51 (±3.07) | 1.06 (0.96–1.16) | 0.240 |
Ceftriaxone | 0.82 (±2.82) | 1.67 (±4.93) | 0.93 (0.83–1.04) | 0.201 |
Pip-tazobactam (dose) | 11.03 (±12.10) | 6.17 (±10.31) | 1.05 (1.02–1.10) | |
Steroids (dose, any) | 23.5 (±23.93) | 7.22 (±12.96) | 1.05 (1.02–1.09) | |
Invasive Medical Devices | ||||
Central venous line (days) | 15.42 (±14.66) | 6.51 (±6.71) | 1.08 (1.03–1.13) | |
Urinary catheter (days) | 18.61 (±15.92) | 7.35 (±7.93) | 1.07 (1.03–1.12) | |
Medical Interventions | ||||
Mechanical Ventilation (days) | 7.47 (±8.55) | 0.94 (±2.34) | 1.27 (1.10–1.48) | |
Parental Nutrition (days) | 2.53 (±3.40) | 1.40 (±3.83) | 1.07 (0.96–1.20) | 0.217 |
Haemodialysis (days) | 6.03 (±14.3) | 0.68 (±2.74) | 1.16 (1.01–1.33) |
SD = standard deviation; OR = odds ratio.
Exposure Variable | Adjusted OR (95% CI) |
|
---|---|---|
Charlson co-morbidity index score | 1.59 (1.15–2.18) | |
Mechanical Ventilation (days) | 1.32 (1.10–1.59) | |
Piperacillin/tazobactam (dose) | 1.08 (1.02–1.15) |
* Adjusted for Charlson co-morbidity index score, mechanical ventilation and piperacillin/tazobactam; OR = odds ratio.
Of the 68 controls 10 died in hospital (14.7%), while 21 of the 38 cases died in hospital (55.3%);this translates to an attributable mortality of 47.5% (
Variable | Death (n = 31) n(%) | Unadjusted OR (95% CI) | Adjusted |
||
---|---|---|---|---|---|
Case—Control | |||||
Control | 10 (32) | 1 | 1 | ||
Case | 21 (68) | 12.81 (2.94–55.82) | 11.29 (2.57–49.60) | ||
Site of Infection | |||||
None | 10 (32) | 1 | 1 | ||
Pneumonia | 11 (36) | 5.5e (-) | 0.994 | 3.54e(-) | 0.993 |
Blood stream infection | 8 (26) | 9.03 (1.10–74.21) | 8.84 (1.09–71.55) | ||
Other | 2 (6) | 4.37 (0.37–51.24) | 0.240 | 3.51 (0.28–44.71) | 0.333 |
Isolate | |||||
None | 10 (32) | 1 | 1 | ||
16 (52) | 19.30 (2.50–148.83) | 16.57 (2.12–129.6) | |||
Other GNB | 5 (16) | 6.36 (0.72–56.51) | 0.097 | 6.08 (0.69–53.90) | 0.105 |
To our knowledge this is the largest epidemiological study investigating risk factors and in-hospital mortality associated with clinical infection during an outbreak of NDM-1-producers, and adds evidence to support rational preventive and control measures. We found that higher Charlson co-morbidity scores, mechanical ventilation and piperacillin/tazobactam exposure were independently associated with infection with NDM-1-producers. Secondly, in-hospital mortality was found to be significantly higher in patients with clinical infection due to NDM-1-producers. Molecular strain typing of NDM-1-producing
We identified three previously published papers reporting on risk factors for infection with NDM-1-producers. The first was a review of reported cases (n = 77) across the European Union which found travel to India, Pakistan or the Balkans to be associated with NDM-1 acquisition.[
Our findings that an increased duration of exposure to central venous lines, urinary catheters, mechanical ventilation and haemodialysis were associated with an increased risk of infection with NDM-1-producers are consistent with risk factors for the acquisition of carbapenemase-producers identified by previous investigators. Medical devices such as urinary catheters[
Of the early NDM-1 cases detected in the United States and United Kingdom, many had epidemiological links to India and Pakistan.[
In-hospital mortality for extended-spectrum beta-lactamase producers has been reported at around 37%[
The hospital undertook a range of interventions to control the outbreak. Patients found to be colonized with NDM-1-producers through the rectal screening program were cohorted and assigned dedicated nursing staff and medical equipment. Healthcare workers and cleaning staff received targeted education about the importance of hand hygiene, and stringent hand washing protocols were instituted throughout the hospital. Hand hygiene practice in the adult ICU was monitored for compliance through closed circuit television. Infrastructural alterations to the adult ICU increased the ICU’s capacity to effectively isolate patients. Weekly meetings were attended by multidisciplinary role-players, including the hospital infection prevention and control practitioners, hospital management staff, medical microbiologists, hospital clinicians, and members of the National Institute for Communicable Diseases’ Outbreak Response Unit. Controlling the outbreak was resource intensive and demanded a concerted effort from all role-players, with critical review of the outbreak situation and re-evaluation of interventional strategies throughout. Although sporadic cases of colonisation or infection with NDM-1-producers continue to be reported, no clusters or epidemiologically-linked cases have been identified since the end of the outbreak.
This study has a number of limitations. Due to the inherent nature of outbreak investigations, there were a limited number of potential cases. All potential cases were reviewed and as many matching controls as were available were included. However, the small sample size limits the study’s power to detect other antimicrobial agents as risk factors for infection with NDM-1-producers. The outbreak was confined to the adult ICU, limiting generalisability to a paediatric population. Missing clinical records and missing data on international travel and previous admissions in the year leading up to the admission of interest reduced our sample size and ability to evaluate pre-hospitalization risk factors. The fluctuating point prevalence of NDM-1-producers and the clinicians’ enhanced diagnostic suspicion of infection with NDM-1-producers as the outbreak evolved may bias findings. We addressed this, however, by matching controls for date of hospital admission.
Given the dearth of new antimicrobials in the drug development pipeline, the burgeoning threat of conquer by virtually untreatable multidrug-resistant organisms of clinical relevance is becoming realised thanks to the emergence and rapid spread of, amongst others, the carbapenemases.[
We thank the following colleagues for their kind support and valuable assistance: Dr Trevor Frankish, Dr Steve Taylor, Trisha Fourie, Mariaan Greese, Joy Cleghorn, Chrismar Hattingh, Melanie Janse van Vuuren, Dr Victor Matabane, Rob Stewart, Dr Leandra Blann, Dr Singh-Moodley and Professor Adriano Duse.