Results
Study selection turned out to be challenging. This was partly due to the
characteristics of the intervention studied which preclude blinding and
limit options for even partial randomization. The search process
retrieved a sole cluster randomised trial and for this reason we decided
to include less robust study types and perform a sensitivity analysis in
case of conflicting results.
Fifteen relevant studies formed our dataset including seven prospective
trials and eight simple before-and-after studies (Table 1). Nine studies
evaluated the effects of antibiotic cycling versus a control
group[13][14][15][16][17][18][19][20][21].
Three papers compared antimicrobial cycling with antibiotic
mixing[22][23][24], that is administering the scheduled
antimicrobial agents on a successive patient basis. The last three
assessed the resistance potential of each of the alternating on-cycle
antibiotics, that is the variations in risk of antibiotic resistant
infection and/or colonization during cycles of different predominant
antibiotic use[25][26][27].
Fixed durations of each cycle ranged from one week to eight months. The
rotating agents were piperacillin-tazobactam with cefepime in two
cases[13][25], fluoroquinolones with beta lactams in three
cases[18][26][27]. The rest rotated the aforementioned
agents with carbapenems and aminoglycosides in varying combinations. In
some protocols de-escalation to suitable narrow-spectrum agents was
permitted but in others it was not, with six teams proceeding to
de-escalation in view of bacterial susceptibility
results[16][17][19][23][24][27], five teams
avoiding de-escalation to increase the on-cycle antimicrobial
use[14][15][18][21][26] and four teams not
clarifying their practices enough for their readers to be able to
ascertain specifically what they did[13][20][22][25].
Four studies provided bacterial typing data to assist in the evaluation
of cross-transmission dynamics[14][18][25][27].
Furthermore, methodologies differed as to whether surveillance cultures
or cultures from clinically presumed infections, unit-wide or
patient-specific, were recorded as indicators of resistance incidence.
Among those studies which compared an experimental with a control cohort
there were seven simple before-and-after and two prospective trials.
Seven of these provided data with regard to antimicrobial protocols in
the control
group[14][15][16][18][19][20][21] and two
did not set out their standard practice[13][17]. Oddly, many
studies fail to state any explicit goal of their chosen intervention,
but the available information suggests that the institution of an
antimicrobial rotation policy aimed to increase heterogeneity of
antimicrobial administration in the intervention group by utilising more
antimicrobial classes of similar spectrum in a scheduled fashion. The
results, however, appear rather conflicting.
In particular, if one takes into account bacterial susceptibilities to
the rotated agents which are apparently a more straightforward indicator
of the policy’s effectiveness four studies did not achieve any
measurable success and five reported variable improvement (Table 1). The
most noteworthy study in the group reporting negative findings is
probably the trial conducted by Toltzis et al. Its main distinctive
feature is the use of a contemporary control group, and its use of
bacterial typing data facilitates interpretation of the available
findings. The researchers observed no benefits even when only clonally
discordant isolates were taken into account[14].
The group reporting positive findings encompassed two studies which
observed an increase in P. aeruginosa susceptibility to one and
two of the rotated agents respectively[17][18] and two studies
which reported improvements in Extended-spectrum Beta Lactamase (ESBL)
incidence (p<0.05)[20][21]. One of the latter used a
rather small sample while none of the aforementioned seemingly
successful studies utilized bacterial typing. Thus, the possibility that
the observed findings could be a result of horizontal transfer of
bacterial clones due to breaks in infection control cannot be excluded
as in the study conducted by Toltzis et al.
Nijssen et al reported lower colonization rates for
ciprofloxacin-resistant isolates in the intervention group but no
changes for cephalosporin-resistant isolates[18]. Highly homogeneous
prescription of fluoroquinolones in the control arm, a radical reduction
in ciprofloxacin administration in the intervention arm along with the
main mechanism of fluoroquinolone resistance which incurs spontaneous
chromosomal mutations favoured by increased selective pressures could
perhaps explain the observed results, but no firm interpretation is
possible.
Frequency of cycling did not appear to be associated with the
possibility of positive or inconclusive outcomes as it varied widely in
both groups. Furthermore, the fact that universal lack of randomization
and blinding would potentially predispose to some degree of selection
and information bias in favour of more positive outcomes, and while no
specific biases were evident, this inevitable contextual bias should be
taken into account.
Three studies assessed antimicrobial rotation compared to administering
the agents on a successive patient basis to maximise antibiotic
heterogeneity, a practice known as antibiotic mixing. Two of those,
including one using the robust cluster-randomised cross-over design,
observed no significant differences[23][24]. Jayashree et al
reported lower resistance rates in both cycling and mixing periods
compared to a three-month baseline period. The latter, however, was too
short to be informative[24]. The third reported higher cefepime
susceptibility rates for P. aeruginosa during cycling (p=0.01)
but no further improvements[22]. De-escalation as well as
combination therapy were permitted in two instances[23][24], and
their allowability was not clarified in the third[22]. None of the
teams used typing data to assess cross-transmission dynamics.
As for the remaining studies, Ginn et al cycled piperacillin-tazobactam
with cefepime and found that cefepime showed as a more important driver
for the onset of bacterial resistance with the proportion of admissions
complicated by resistant infections during cefepime cycles being more
than twice as high compared to piperacillin-tazobactam cycles
(p<0.001)[25]. Van Loon et al cycled levofloxacin with
cefpirome and piperacillin-tazobactam. concluding that levofloxacin use
was associated with higher levofloxacin-resistance rates, but cefpirome
was seemingly not prone to the selection of cefpirome-resistant
strains[26]. Tsukayama et al rotated fluoroquinolones with
piperacillin-tazobactam but did not find any significant correlations
between the on-cycle antibiotic class and the probability of resistance
onset. However, the authors report high use of off-cycle antibiotics
which could potentially act as a confounding factor[27].
Finally, all but two studies provided some data regarding the on- and
off-cycle antimicrobial consumption during the experimental period,
while seven studies measured variable side effects as indicators of the
policy’s potential collateral damage including morbidity and/or
mortality rates reported by six
studies[15][16][19][22][23][24]. None of these
recorded worrying trends in intervention groups.