Volume 10, Number 8—August 2004
Research
Antimicrobial Drug Use and Methicillin-resistant Staphylococcus aureus, Aberdeen, 1996–2000
Table 3
Summary of transfer function models explaining the monthly %MRSA by use of each antimicrobial drug classa
Antimicrobial classb | Average delay (months) | Direction of effectc | p value | R2d |
---|---|---|---|---|
Combinations of penicillins with β-lactamase inhibitors |
2
4 |
Positive
Positive |
0.04
0.01 |
0.92 |
β-lactamase-resistant penicillins |
0
6 |
Negative
Positive |
0.02
0.002 |
0.90 |
Macrolides |
1 |
Positive |
0.0001 |
0.93 |
Penicillins with extended spectrum |
1 |
Positive |
0.03 |
0.91 |
Third-generation cephalosporins |
1 |
Positive |
0.04 |
0.90 |
β−lactamase sensitive penicillins |
6 |
Positive |
0.04 |
0.89 |
Combinations of sulfonamides and trimethoprim, including derivatives |
4 |
Positive |
0.02 |
0.90 |
Fluoroquinolones |
4 |
Positive |
0.0004 |
0.92 |
Second-generation cephalosporins |
No relationship |
|||
Other antibacterialsd |
0 |
Positive |
0.002 |
0.91 |
Tetracyclines |
4
7 |
Positive
Negative |
0.03
0.0007 |
0.91 |
Aminoglycosides |
No relationship |
|||
Lincosamides |
7 |
Positive |
0.02 |
0.89 |
First-generation cephalosporins |
No relationship |
|||
Carbapenems | 3 | Positive | 0.03 | 0.90 |
aMRSA, methicillin-resistant Staphylococcus aureus.
bGlycopeptide use is not presented in this table because it showed an inverse relationship with %MRSA. In other words, %MRSA explained the monthly variations of glycopeptide use and not the reverse (Discussion).
cPositive direction of effect: increase in antimicrobial use results in increase in %MRSA and inversely. Negative direction of effect: increase in antimicrobial use results in decrease in %MRSA and inversely.
dAll models include the variable %MRSA with a 1-month delay with a p value < 0.0001.
dAmphenicols, monobactams, other quinolones, imidazoles, fusidic acid, and nitrofurantoin derivatives.