Volume 10, Number 8—August 2004
Research
Antimicrobial Drug Use and Methicillin-resistant Staphylococcus aureus, Aberdeen, 1996–2000
, José María López-Lozano‡, Arielle Beyaert§, Máximo Camacho§, Rachel Wilson†, David Stuart†, and Ian M. Gould†
Table 4
Estimated multivariate Polynomial Distributed Lag (PDL) model for monthly %MRSA (R2=0.902)a
| Explaining variable | Lag (mo.) | Direct effectb |
Indirect effectc |
Sum of both effectsd |
||||
|---|---|---|---|---|---|---|---|---|
| Coeff | T-stat | p | Coeff | Coeffe | T-stat | p | ||
| %MRSA |
1 |
0.420 |
3.96 |
0.0003 |
||||
| Macrolide use |
||||||||
| Each month |
1 |
0.083 |
0.083 |
4.02 |
0.0003 |
|||
| 2 |
0.055 |
0.035 |
0.090 |
5.34 |
<0.0001 |
|||
| 3 |
0.027 |
0.038 |
0.065 |
6.02 |
<0.0001 |
|||
| 4 |
0.027 |
0.027 |
3.16 |
0.003 |
||||
| Overall |
1–3 |
0.165 |
4.02 |
0.0003 |
||||
| 2–4 |
0.100 |
|||||||
| 1–4 |
0.265 |
|||||||
| Third-generation cephalosporin use |
||||||||
| Each month |
4 |
0.116 |
0.116 |
2.75 |
0.009 |
|||
| 5 |
0.087 |
0.049 |
0.136 |
3.27 |
0.002 |
|||
| 6 |
0.058 |
0.057 |
0.115 |
3.70 |
0.0007 |
|||
| 7 |
0.029 |
0.048 |
0.077 |
3.91 |
0.0004 |
|||
| 8 |
0.032 |
0.032 |
2.75 |
0.009 |
||||
| Overall |
4–7 |
0.290 |
2.75 |
0.009 |
||||
| 5–8 |
0.186 |
|||||||
| 4–8 |
0.476 |
|||||||
| Fluoroquinolone use |
||||||||
| Each month |
4 |
0.170 |
0.170 |
3.43 |
0.002 |
|||
| 5 |
0.085 |
0.071 |
0.156 |
3.37 |
0.002 |
|||
| 6 |
0.066 |
0.066 |
2.31 |
0.03 |
||||
| Overall |
4–5 |
0.255 |
3.43 |
0.002 |
||||
| 5–6 |
0.137 |
|||||||
| 4–6 |
0.392 |
|||||||
| Constant | –36.7 | –4.42 | 0.0001 | |||||
aMRSA, methicillin-resistant Staphylococcus aureus.
bPast %MRSA as well as past use of these three antimicrobial drug classes had direct effects on %MRSA. These direct effects diminished the longer the lag time.
cBecause every increase in %MRSA by the value 1 was followed the next month by a significant increase in %MRSA by the value 0.420, use of the three antimicrobial drug classes also had indirect effects on the %MRSA. As 0.420 is <1, these indirect effects necessarily vanished over time. As an example, decreasing indirect effects are only presented for a few months. There were substantial indirect effects of macrolide use up to month 8 (final coefficient for sum of both effects = 0.284), of third-generation cephalosporin use up to month 12 (final coefficient for sum of both effects = 0.499), and of fluoroquinolone use up to month 11 (final coefficient for sum of both effects = 0.440).
dEach month, the total effect of each class of antimicrobial on the %MRSA resulted from the sum of the direct and indirect effects.
eThe estimated coefficients indicate the values by which the %MRSA would increase in response to an increase in 1 DDD per 1,000 patient-days for each of the three significant antimicrobial classes, when all other variables remain constant. Since the average figure for monthly patient-days at Aberdeen Royal Infirmary is 22,800, 10 DDD per 1,000 patient-days correspond to approximately 230 DDD per month or thirty 7- to 8-day antimicrobial courses. For example, an increase in macrolide use by 10 DDD per 1,000 patient-days on a certain month, or 30 more patients treated with a macrolide as compared with the previous month, would lead to a direct increase in %MRSA by 0.83, 1 month later, by 0.55, 2 months later and by 0.27, 3 months later. The total direct effect would therefore be evident after 3 months, amounting to an increase in %MRSA by the value 1.65. Additionally, %MRSA indirectly attributable to macrolide use would increase by the value 0.35 (i.e., 0.83 x 0.42) after 2 months and by 0.38 (i.e.. [0.83 x 0.42] + [0.55 x 0.42]) after 3 months. From the 4th month onwards, there would be no direct effect of macrolide use on the %MRSA, only ever-decreasing indirect effects that would practically disappear after 8 months (decreasing effects in months 5 to 8 not shown).