Table 4.
Analysis of risk factors associated with carbapenem non-susceptibility of K. pneumoniae isolates
| Univariable analysis of risk factors associated with carbapenem non-susceptibility | Multivariable analysis of risk factors associated with carbapenem non-susceptibility | |||
|---|---|---|---|---|
| OR (95% CI)a | p-valueb | OR (95% CI)c | p-valueb | |
| Year | ||||
| 2011 | 1 | – | 1 | – |
| 2012 | 1.00 (0.64, 1.57) | 0.994 | 0.99 (0.63, 1.56) | 0.964 |
| 2013 | 1.29 (0.84, 1.99) | 0.239 | 1.30 (0.85, 2.01) | 0.229 |
| 2014 | 1.78 (1.16, 2.75) | 0.009 | 1.84 (1.19, 2.84) | 0.006 |
| 2015 | 1.87 (1.23, 2.86) | 0.004 | 1.99 (1.29, 3.05) | 0.002 |
| 2016 | 2.00 (1.32, 3.05) | 0.001 | 2.10 (1.38, 3.22) | 0.001 |
| Quarter | ||||
| Jan - Mar | 1 | – | 1 | – |
| Apr - Jun | 1.14 (0.93, 1.40) | 0.217 | 1.13 (0.92, 1.39) | 0.248 |
| Jul - Sept | 1.07 (0.87, 1.31) | 0.515 | 1.06 (0.87, 1.30) | 0.553 |
| Oct - Dec | 1.05 (0.86, 1.30) | 0.618 | 1.07 (0.87, 1.31) | 0.542 |
| Age (years) | ||||
| < 1 | 0.49 (0.21, 1.11) | 0.089 | 0.26 (0.11, 0.61) | 0.002 |
| 1–19 | 2.28 (1.45, 3.58) | < 0.001 | 1.67 (1.06, 2.66) | 0.029 |
| 20–39 | 2.87 (2.17, 3.79) | < 0.001 | 2.38 (1.78, 3.18) | < 0.001 |
| 40–49 | 1.88 (1.33, 2.64) | < 0.001 | 1.49 (1.05, 2.10) | 0.025 |
| 50–59 | 2.10 (1.63, 2.70) | < 0.001 | 1.62 (1.26, 2.10) | < 0.001 |
| 60–69 | 1.73 (1.37, 2.18) | < 0.001 | 1.35 (1.06, 1.71) | 0.013 |
| 70–79 | 1.57 (1.28, 1.94) | < 0.001 | 1.33 (1.08, 1.65) | 0.007 |
| 80+ | 1 | – | 1 | – |
| Sex | ||||
| Male | 1.81 (1.57, 2.10) | < 0.001 | 1.57 (1.35, 1.83) | < 0.001 |
| Female | 1 | – | 1 | – |
| Hospital Care Level | ||||
| Secondary Care | 1 | – | 1 | – |
| Tertiary Care | 3.52 (2.02, 6.11) | < 0.001 | 2.68 (1.55, 4.66) | < 0.001 |
| Specialist Care | 2.16 (1.39, 3.37) | 0.001 | 2.44 (1.57, 3.78) | < 0.001 |
| Prevention and Rehabilitation Care | 1.92 (0.93, 3.98) | 0.078 | 2.22 (1.09, 4.52) | 0.028 |
| Other | 0.91 (0.26, 3.21) | 0.886 | 1.03 (0.29, 3.61) | 0.966 |
| Type of care | ||||
| Intensive care unit | 2.58 (2.20, 3.03) | < 0.001 | 2.37 (1.98, 2.84) | < 0.001 |
| Normal hospital ward | 1 | – | 1 | – |
| Other | 1.96 (1.26, 3.06) | 0.003 | 1.69 (1.08, 2.64) | 0.022 |
| Clinical specialty | ||||
| Surgery and related | 1.50 (1.24, 1.82) | < 0.001 | 1.15 (0.94, 1.40) | 0.176 |
| Internal medicine | 1 | – | 1 | – |
| Other | 1.50 (1.26, 1.78) | < 0.001 | 0.98 (0.81, 1.18) | 0.821 |
| Sample type | ||||
| Swabs | 2.35 (1.94, 2.85) | < 0.001 | 1.87 (1.53, 2.29) | < 0.001 |
| Blood culture | 1.45 (1.01, 2.06) | 0.043 | 1.08 (0.76, 1.56) | 0.661 |
| Puncture | 1.46 (0.90, 2.37) | 0.126 | 1.08 (0.66, 1.76) | 0.769 |
| Urine | 1 | – | 1 | – |
| Wound | 1.90 (1.49, 2.41) | < 0.001 | 1.45 (1.13, 1.87) | 0.003 |
| Respiratory | 2.07 (1.69, 2.53) | < 0.001 | 1.21 (0.97, 1.51) | 0.093 |
| Other | 3.01 (1.98, 4.58) | < 0.001 | 2.11 (1.37, 3.23) | < 0.001 |
| Region | ||||
| Northwest | 1 | – | 1 | – |
| West | 1.70 (0.93, 3.14) | 0.087 | 1.73 (0.98, 3.06) | 0.057 |
| Southwest | 1.03 (0.55, 1.93) | 0.922 | 1.01 (0.55, 1.84) | 0.983 |
| Southeast | 1.10 (0.55, 2.20) | 0.783 | 0.89 (0.46, 1.71) | 0.721 |
| Northeast | 1.57 (0.74, 3.33) | 0.241 | 1.43 (0.69, 2.98) | 0.336 |
| County Type | ||||
| Rural | 1 | – | 1 | – |
| City | 1.34 (0.93, 1.92) | 0.119 | 1.17 (0.74, 1.84) | 0.508 |
| Counties by Social Deprivation Index | ||||
| 1 (lowest deprivation) | 1 | – | 1 | – |
| 2 | 1.29 (0.68, 2.44) | 0.444 | 1.29 (0.70, 2.36) | 0.412 |
| 3 | 0.96 (0.51, 1.82) | 0.897 | 0.88 (0.47, 1.64) | 0.687 |
| 4 | 0.84 (0.44, 1.61) | 0.609 | 0.79 (0.42, 1.47) | 0.452 |
| 5 (highest deprivation) | 0.99 (0.53, 1.84) | 0.971 | 0.91 (0.49, 1.69) | 0.758 |
| Hospital Beds per 10.000 inhabitants | ||||
| 8.2–57.2 | 1 | – | 1 | – |
| 57.3–71.5 | 0.96 (0.59, 1.56) | 0.870 | 0.87 (0.53, 1.42) | 0.577 |
| 71.6–90.9 | 0.82 (0.51, 1.33) | 0.431 | 0.62 (0.36, 1.08) | 0.093 |
| 91.0–219.0 | 1.49 (0.94, 2.36) | 0.087 | 1.01 (0.58, 1.77) | 0.969 |
Isolates from patients with missing values on the variables were not included in the analysis
CI confidence interval, OR odds ratio
aHierarchical Logistic Regression model accounting for clustering within counties and hospitals
bWald test
cHierarchical Logistic Regression model accounting for clustering within counties and hospitals adjusting for year, quarter age, sex, hospital care level, type of care, clinical specialty, sample type, region, county type, social deprivation index, and hospital beds per 10,000 inhabitants