Rate of bacterial positivity following antibiotic initiation: A systematic review and meta-analysis

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However, its diagnostic accuracy is often compromised by prior antibiotic administration, which can reduce the recovery of viable organisms and lead to false-negative results. Given the variability and limitation in existing studies, a systematic review is needed to better understand the influence of antibiotics on culture yield. Methods We conducted an electronic search in PubMed, Embase, Scopus and Web of Science from their inception through March 2025. The Newcastle-Ottawa Scale was used to assess the methodological quality of the included articles. Random effect models were used to estimate the proportions and 95% Confidence Intervals (CI). The protocol for this review was registered in the PROSPERO: CRD42025648397. Results Of the 1,226 articles obtained from the search, 11 were eligible. They consisted of 67,330 samples with culture results after antibiotic administration. The pooled proportion for bacterial growth was 37% (95% CI: 20%-56%) and 18% (95% CI: 10%-29%) before and after antibiotic administration, respectively. Significant heterogeneity ( I 2 : 99.8%, p-value = 0) was observed across the included studies. Conclusion Bacterial growth decreased by more than half following antibiotic administration, indicating a strong suppressive effect. This highlights the importance of considering the timing of sample collection in relation to antibiotic initiation. Where necessary, particularly in cases of uncertain clinical progress, sampling after antibiotic administration can be useful for monitoring prognosis and guiding further treatment decisions. Bacterial Positivity Culture Antibiotic Use Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Bacterial cultures remain fundamental to the diagnosis of infectious diseases, providing definitive identification of pathogens and essential data for antimicrobial susceptibility testing ( 1 , 2 ). The recovery of viable organisms from clinical specimens allows for precise, pathogen-directed therapy and supports antimicrobial stewardship efforts. However, culture-based diagnostics are highly sensitive to pre-analytical factors most notably, prior antibiotic exposure ( 3 ). In clinical settings, empiric antibiotics are often administered before microbiological samples are collected, particularly in patients with suspected severe infections. Although early treatment is critical for improving outcomes ( 4 ), it can significantly impair diagnostic accuracy. Antibiotics may suppress or eliminate viable bacteria at the site of infection, leading to false-negative culture results. This can complicate clinical decision-making, delay appropriate therapy adjustments, and contribute to unnecessary continuation of broad-spectrum antimicrobial agents ( 5 ). The impact of antibiotic administration on culture positivity varies across specimen types, timing, and the pharmacodynamics of the drugs involved ( 6 ). Blood, cerebrospinal fluid, pleural and peritoneal fluids, bile, synovial fluid, tissue biopsies, and wound swabs are all affected to varying degrees. Some specimens, such as blood, may exhibit a rapid decline in culture yield due to immediate systemic antibiotic distribution, while others such as bile or pleural fluid may retain diagnostic value for a longer period. The variability in antimicrobial tissue penetration and local immune responses further complicates predictions about culture yield following therapy ( 7 ). In response to these challenges, molecular diagnostic technologies, including polymerase chain reaction (PCR) and fluorescence in situ hybridization (FISH), have gained traction in clinical microbiology ( 8 ). These methods offer faster turnaround times and can detect microbial DNA or RNA even in the absence of viable organisms. However, they often lack the ability to provide antimicrobial susceptibility data and may not detect all clinically relevant pathogens. As such they are complementary rather than substitutive to traditional culture methods. Although the suppressive effect of antibiotics on culture growth is widely acknowledged, the degree and timing of this effect remains inconsistently described in the literature. Variations in study design, clinical context, sample collection protocols, and diagnostic methods have led to the conflicting findings, making it difficult to draw generalized conclusions. Moreover, much of the available evidence is limited to single-centre studies or specific infection types, limiting its broader applicability. This systematic review was therefore undertaken to consolidate existing evidence on the effect of antibiotic administration on bacterial culture positivity. Methods Study design and search strategy This review was registered in the International Prospective Register for Systematic Reviews (PROSPERO: CRD42025648397). The review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA)( 9 ). Relevant evidence was extracted from PubMed, Embase, Scopus and Web of Science spanning from database inception to 4th March 2025, except for PubMed, where the search was updated until 12th March 2025. The search terms and search strategy for the research question were developed with assistance for the research librarian and adapted to each database. The keywords included ‘antibiotics’, ‘antibacterial agents’, ‘antibacterial therapy’, ‘antibiotic administration’ ,‘bacterial infection’, ‘bacterial culture’, ‘positivity rate’, ‘culture positivity’, ‘diagnostic yield’, and ‘culture growth’. The review team used MeSH (medical sub-heading terms) for PubMed search, while Boolean operator ‘AND’ combined both or all of the keywords, while ‘OR’ searched articles containing at least one of the keywords. Study selection Articles obtained from the database search were uploaded to Covidence software (Veritas Health Innovation, Melbourne, Australia) which identified and removed duplicates. Two reviewers (A.M.I & P.E.J) independently conducted titles and abstract screening using the COVIDENCE software, selecting articles that described bacterial growth on culture and bacterial culture results of patients with clinically confirmed infection. During full-text screening, the two reviewers (A.M.I & P.E.J) excluded studies that were not open access, studies with bacterial culture results without evidence of antibiotic administration, studies without specification of the participants who received antibiotics, studies without bacterial culture results after antibiotic administration and culture samples taken within one hour after antibiotic administration. The discrepancies were resolved by the third reviewer (G.M.B). Data extraction and narrative synthesis Two independent reviewers (A.M.I & P.E.J) extracted data from the included studies using a standardized excel spreadsheet including the author, publication year, country, study design, age group, disease condition, key finding, study limitation, number of events and total population before and after antibiotic administration. The two reviewers (A.M.I & P.E.J) independently and inductively conducted thematic mapping of the key themes and findings from the included articles relevant to the study objectives. Risk of Bias Two independent reviewers (A.M.I and G.M.B) use the Newcastle-Ottawa Scale (NOS) to assess the included studies. The NOS which consists of a total of 9 questions encompassing participant selection, cohort comparability, and outcome evaluation by two authors. The responses to the questions were assigned a score of 1 for indicated weighted responses and 0 for all other responses. The final score of each article was reached upon consensus of the reviewers. Data analysis We analysed data using in R Version 2024.12.1 + 563. Proportions of bacterial growth from the included studies were calculated with logit transformation (‘PLOGIT’) applied as the summary measure to account for the wide range of proportions. The weighted prevalence [(95% Confidence Interval (CI)] of bacterial growth on culture was estimated using random effects model and presented in forest plots. Meta-analyses were performed for studies that reported proportions of bacterial growth before and after antibiotic administration. Study heterogeneity was assessed using the I² statistic. The Egger’s linear regression test of funnel plot asymmetry was also performed ( 10 ). A p-value of less than 0.05 was considered statistically significant. In this review, the number of events (n) and total population (N) were defined as the number of samples (culture bottles) showing positive bacterial growth if specified, or alternatively the number of patients with bacterial growth on culture among those who received antibiotics or were sampled. When both sample-level and patient-level data were available, we prioritized the number of samples. Meta-analysis was restricted to studies that reported bacterial culture results both before and after antibiotic administration. Results Our evidence search yielded 1,226 articles which were all uploaded to Covidence for screening. Seventy duplicates were removed, and 1,118 articles were excluded based on the study title and abstract. Thirty-eight articles were assessed for eligibility, of which 11 articles met the inclusion criteria for full-text analysis (Fig. 1 ). The included articles involved over 67,330 samples with culture results after antibiotic administration. Seven articles were eligible in meta-analysis, comprising of more than 12,399 culture samples taken prior to antibiotic administration and about 7,560 culture samples after antibiotic administration. Study characteristics The included studies were published between 2011( 11 ) and 2024 ( 12 ). Three out of the 11 included articles were prospective studies which deployed various methods including cross-sectional ( 13 ), case-control ( 14 ), and cohort ( 15 ) study. Of the eight retrospective studies included, two analysed previously collected tissue samples ( 12 , 16 ), while six utilized data from electronic health records ( 11 , 17 – 20 ), including one time-series retrospective cohort study ( 21 ). All retrospective studies were conducted in high-income countries with established electronic health records systems including the USA ( 17 , 21 ), Italy ( 11 ), Australia ( 20 ), Belgium ( 18 ), Poland ( 16 ) and Germany ( 19 ) that facilitated the availability of the required data for retrieval. Only one study has been conducted in several countries across Asia (Thailand) and Africa (the Gambia, Kenya, Mali, South Africa and Zambia) ( 14 ). Two articles performed bacterial culture detection using both culture and molecular diagnostic methods namely, PCR ( 14 , 16 ). Methodological quality was assessed in all included articles, of which eight articles had moderate quality ( 12 , 13 , 16 – 21 ) and three articles had good quality ( 11 , 14 , 15 ) (Table 1 ). Table 1 Characteristics of the included articles, key findings and methodological quality. Author Study design Country Population characteristics Sample characteristics Antibiotic resistance Key findings Methodological quality Age group Disease condition Tissue biopsy Antibiotic given Antibiotic Banks 2011 ( 13 ) Prospective cohort study USA Adults Post radical prostatectomy secondary to Prostate Cancer Urine Cefazolin or TMT-SMZ or Cephalexin Ampicillin, Ciprofloxacin, Penicillin, Norfloxacin, cefazolin and tetracycline Low burden of symptoms despite the high frequency of bacteriuria. Moderate quality Driscoll 2017 ( 14 ) Case-control study 7 countries: Bangladesh, The Gambia, Kenya, Mali, South Africa, Thailand and Zambia Children (< 5yrs) 1–59 months Severe or very severe Pneumonia Blood, nasopharyngeal swabs, sputum Not specified Not specified Exposure to antibiotics reduces bacterial yield on culture by 45%. Good quality Dutta 2022 ( 21 ) Retrospective time series cohort study USA Adults Sepsis Blood Not specified Not specified Blood cultures collected after intravenous antibiotic administration had reduced bacterial positivity rates. Moderate quality Hummel 2009 ( 19 ) Retrospective study Germany All age groups (16-85yrs) Haematological malignancy with episodes of neutropenic fever. Blood Piperacillin with a beta-lactam inhibitor or carbapenem as monotherapy Not specified Blood culture sampling is useful in patients with febrile neutropenia even after antibiotic therapy initiation. Moderate quality Kim 2024 ( 12 ) Retrospective study South Korea Adults Infectious spondylitis Blood, infected disc and swab Not specified Not specified Pre-operative antibiotic treatment may reduce the sensitivity of microbiological detection, particularly in blood and tissue cultures. Blood culture shows higher sensitivity to bacterial growth than swab and tissue culture. Moderate quality Lucignano 2011 ( 11 ) Retrospective cohort study Italy Children (< 18 years) Systemic Inflammatory Response Syndrome (SIRS) Blood Not specified Not specified Blood cultures detect a wider variety of bacterial species. Molecular diagnostics offer higher sensitivity and faster results. Good quality Wang 2020 ( 20 ) Retrospective study Australia Adults Haematological malignancies with febrile neutropenia. Blood Not specified Not specified Blood cultures collected more than 24 hours after initiation of broad spectrum antibiotics yield less clinically relevant micro-organisms. Moderate quality Scheer 2018 ( 15 ) Prospective cohort study Germany Adults Severe sepsis, septic shock. Blood Beta lactam antibiotics, cephalosporins, carbapenems Not specified Less pathogens detection occurs after initiation of antibiotics Good quality Stankey 2018 ( 17 ) Retrospective cohort study USA Children < 18 yrs Pleural empyema Blood Not specified Not specified Blood cultures show a greater decline in positivity following antibiotic administration compared to pleural fluid cultures Moderate quality Goethem 2022 ( 18 ) Retrospective cohort study Belgium All age groups Bacteraemia (UTI, pyomyositis, endocarditis, meningitis) Blood Vancomycin or Beta-lactam antibiotics Not specified The highest probability of detecting Staphylococcus aureus Bacteraemia is achieved by collecting two blood culture sets on days 2 and 4 after initiation of therapy. Moderate quality Zrodlowski 2018 ( 16 ) Retrospective cohort study Poland Children (< 18 yrs) Sepsis Blood Not specified Not specified Molecular diagnostic methods such as FISH and PCR enable preliminary detection of bacteria before culture results are available, making them useful for screening purposes Moderate quality Keywords : Fluorescent in situ hybridisation (FISH) Polymerase Chain Reaction (PCR) Trimethoprim sulfamethoxazole (TMT-SMZ) Urinary tract infection (UTI) Publication bias The funnel plot demonstrated asymmetrical distribution of studies around the central vertical line (Fig. 2 ). Five out of 7 studies ( 12 , 14 , 15 , 17 , 19 ) clustered at the top, indicating larger studies with smaller standard errors. This pattern suggests potential publication bias and supports previously observed high heterogeneity in the meta-analysis. Commonly isolated bacteria Ten of the 11 included articles indicated the types of bacteria isolated upon culture ( 11 – 20 ). For convenience, we identified the 3 most frequently isolated bacteria and categorised as either gram-positive or gram-negative. Escherichia coli was the most isolated gram-negative bacteria ( 12 , 13 , 15 , 19 , 20 ), and Pseudomonas aeruginosa ( 11 – 13 , 20 ). In this review, all studies with leading Escherichia coli isolates involved adult patients ( 12 , 13 , 15 , 19 , 20 ) with urinary tract infections ( 13 ), infectious spondylitis ( 12 ), sepsis ( 15 ) and febrile neutropenia ( 19 , 20 ). However, Pseudomonas aeruginosa as isolated among newborns with sepsis ( 11 ) and adults with infectious spondylitis ( 12 ) and underlying co-morbidities such as haematological malignancies ( 20 ) and prostate cancer ( 13 ). Pseudomonas aeruginosa infections were mainly from patients with compromised immunity, prolonged hospital stay or from medical interventions such as urinary-catheter use. The most common gram-positive bacteria isolates were Staphylococcus aureus ( 12 , 14 , 15 , 17 , 18 ), Streptococcus pneumoniae ( 12 , 14 , 17 ) and Staphylococcus epidermidis ( 13 , 20 ). Staphylococcus aureus isolates were respiratory tract infections in paediatrics ( 14 , 17 ) and blood borne infections in adults ( 12 , 15 ). Streptococcus pneumoniae was isolated from adults with infectious spondylitis ( 12 ) and paediatrics with respiratory tract infections such as pneumonia ( 14 ) and empyema ( 17 ). Staphylococcus epidermidis isolates were from adults with suspected hospital acquired infections from urinary catheters ( 13 ) and with comorbidities including haematological malignancies ( 20 ). Commonly prescribed antibiotics and resistance patterns Seven studies reported on the antibiotics prescribed to the patients prior to culture sample collection. These include Trimethoprim-Sulfamethoxazole ( 13 , 18 , 19 ), cephalosporins ( 15 ) such as ciprofloxacin ( 13 ) and cephalexin ( 13 ), and penicillin including amoxicillin ( 14 ) and piperacillin ( 15 , 19 ). Staphylococcus aureus was identified to be resistant to ampicillin, ciprofloxacin, penicillin, norfloxacin, cefazolin, and tetracycline ( 13 ) and Methicillin-Resistant strains of Staphylococcus aureus (MRSA) were identified ( 12 , 13 ). Additionally, Escherichia coli was identified to be resistant to fluoroquinolones. Effects of antibiotics on bacterial growth with time The use of antibiotic therapy was identified to reduce bacterial growth on culture. Two articles reported that antibiotics reduced culture positivity following antibiotic administration ( 12 , 20 ). Additionally, two studies demonstrated that bacterial growth on culture further declined with continued antibiotic use over time ( 18 , 20 ). Wang et al reported a 44.65% decrease in bacterial growth of culture samples collected 24 hours after initiation of broad spectrum antibiotics ( 20 ). Goethem et al . further highlighted the importance of timing by examining Staphylococcus aureus growth longitudinally for 5 consecutive days ( 18 ). This study recommended follow-up cultures between day 2 and day 4 after antibiotic initiation to detect persistent bacteraemia ( 18 ). Although their approach of collecting blood cultures over five consecutive days detects the gradual decline of ongoing infection, it remains largely impractical in routine clinical settings due to cost and resource limitations. Bacterial growth before antibiotic administration Seven articles were meta-analysed to estimate the proportion of positive bacterial cultures prior to antibiotic administration (Fig. 3 ). The pooled proportion was 37% (95% CI: 20%-56%), indicating that, 37% culture sample are positive before antibiotic administration. There was substantial heterogeneity across the studies ( I 2 : 99.5%, p-value < 0.001), as reflected by the wide range reported proportions ranging from 10% as reported by Lucignano 2011 ( 11 ) to 74% as reported by Kim 2011 ( 12 ). However, the relatively narrow confidence intervals of the individual studies suggest good precision within each study. Bacterial growth after antibiotic administration Eleven articles were included in the meta-analysis to estimate the proportion of bacterial growth following antibiotic administration (Fig. 4 ). The pooled proportion of positive cultures was 18% (95% CI: 10%-29%), indicating that 18% of cultures remained positive after antibiotic administration. Significant heterogeneity was observed across studies ( I 2 : 99.8%, p-value = 0), which is reflected in the wide variation in sample size and culture positivity rates-ranging from 4% as reported by Dutta 2022 ( 21 ) to 55% as reported by Goethem 2022 ( 18 ). Sub-group analysis of bacterial growth after antibiotic administration Based on patient age Participants of the included studies were categorized by age into three groups: children (under 18 years), adults (above 18 years) and all age groups (if participants were inclusive of both children and adults). The pooled proportion of bacterial positivity following antibiotic initiation was 22% (95%CI: 4%-68%) for all age groups, 18% (95% CI: 8%-35%) in adults and 16% (95%CI: 8%-30%) in children (Fig. 5 ). Based on the underlying medical condition In this review, we classified the included studies into two categories: those involving with patients with underlying medical conditions (such as cancer) and patient with primary clinical infections, considered as without underlying medical conditions. The pooled proportion of bacterial positivity following antibiotic administration was 24% (95% CI: 12%-41%) in patients without underlying medical condition and 10% (95% CI: 6%-18%) in those with underlying medical conditions (Fig. 6 ). Discussion Evidence pooled from 11 studies with 67,330 culture samples from participants who had already taken antibiotics, has shown that bacterial growth on culture declines from 37% before antibiotic therapy to 18% after antibiotic administration. The common isolated bacteria were Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa . All ( 11 – 13 , 15 – 21 ) except one ( 14 ) of the included articles were conducted in high-income countries, where health systems and financing schemes facilitate access to culture sampling for patients. These settings also benefit from well-established health information systems that support efficient data retrieval for retrospective analyses. In contrast, only one study ( 14 ) included participants from low- and middle-income countries (LMICs), specifically from Africa and Asia. There were no retrospective studies conducted in LMICs, likely due to limited access to culture sampling, which often requires out-of-pocket payment and lack of uniform health information systems ( 22 ). Consequently, representation from LMICs is largely limited to prospective, research-funded studies, highlighting a critical gap in the availability of good quality routine data from these regions. Bacterial positivity prior to antibiotic administration was relatively low, with a pooled estimate of 37% (95% CI: 20%-56%). A potential explanation for this finding is that some patients may have had non-bacterial infections, such as viral sepsis, which mimic the clinical presentations of bacterial infections ( 23 ). Alternately, the low bacterial growth prior to antibiotic administration could be attributed to heterogeneity in study design and sample types. The variation in sample types and laboratory culture practices influences the positivity rates. For example, blood cultures often yield bacterial growth compared to Cerebrospinal Fluid (CSF) cultures, which in meningitis cases, may exhibit pleocytosis ( 24 ). Additionally, the variation in study designs including the reporting bias related to antibiotic use, makes it uncertain whether the participants had self-medicated prior to treatment initiation. However, majority of the included studies were conducted in high-income countries where antibiotic use is typically regulated, which may limit the extent of unreported pre-treatment exposure ( 25 ). Our review did not assess the appropriateness of antibiotic prescribing practices in individual studies, nor did it account for the potential use of sub-optimal or counterfeit antibiotics. We observed bacterial growth after antibiotic administration with a pooled estimate of 18% (95% CI: 10%-29%). This persistent bacterial growth could be attributed to several reasons including sub-optimal dosing ( 26 ), use of counterfeit antibiotics ( 27 ), and timing of sample collection relative to antibiotic initiation ( 18 , 20 ). While existing guidelines for sepsis management emphasize the importance of obtaining cultures before initiating antibiotics in suspected sepsis ( 28 , 29 ), however there are no specific recommendations on culture sampling after antibiotics initiation. Based on the current findings on bacterial growth post-antibiotics, we recommend considering sampling for bacterial culture even when the patient has been initiated antibiotics, where feasible. This could aid monitoring the patient prognosis. The top three isolated bacteria in this review; Escherichia Coli , Staphylococcus aureus and Pseudomonas aeruginosa, consistent with the well-documented global burden of bacterial bloodstream infections ( 30 ). All of the articles that identified Escherichia Coli as the most predominant isolated gram-negative were from high-income countries. This finding aligns with the known epidemiological patterns of Escherichia Coli , which is responsible for approximately 27% of documented bacteraemia episodes in high income countries ( 31 ). The burden of Escherichia Coli is reported to be particularly high among adults and among patients with urogenital infections ( 31 ) consistent with our findings. Our review identified fluoroquinolone resistance in Escherichia coli, consistent with existing literature, which highlights that infections with resistant strains are more persistent than those caused by susceptible strains ( 32 ). The global prevalence of Staphylococcus aureus colonization in humans is estimated at 24.9%, underscoring its clinical predominance ( 33 ). This finding is consistent with our review, in which Staphylococcus aureus was the most commonly isolated gram-positive bacterium across the included studies. This review found Staphylococcus aureus to be predominantly resistant to third-generation penicillin, particularly ampicillin ( 13 ), which contrasts with a recent systematic review from Africa indicating higher resistance to second-generation penicillin ( 34 ). Overall, the existing evidence underscores Escherichia coli and Staphylococcus aureus as the leading antimicrobial resistant pathogens associated with mortality worldwide ( 35 ). Strength and limitations To the best of our knowledge, this is the first systematic review that analyses the bacterial growth on culture after antibiotic administration. However, our findings should be interpreted in the light of the following limitations. We calculated the proportion of bacterial growth on culture after antibiotic administration based on either the number of samples or the number of patients with positive cultures, depending on what was reported. However, we did not account for the possibility of multiple samples being collected from a single patient, nor did we standardize for the recommended diagnostic practice of obtaining 2–3 culture bottles in cases of suspected bacteraemia. The included studies varied widely in their culture methodologies and sampling protocols, which may have contributed to differences in bacterial positivity rates and introduced heterogeneity into the pooled estimates. Only a limited number of studies reported bacterial growth on culture prior to antibiotic administration, which constrained our ability to produce a robust pooled estimate for this group. Conclusion Bacterial culture positivity was lower after antibiotic administration compared to pre-treatment levels, indicating a reduction in viable bacterial load following therapy. However, the continued presence of bacterial growth in some samples suggests that certain pathogens may persist despite treatment, potentially due to delayed antibiotic action, inadequate tissue penetration, or emerging resistance. These findings imply that the bactericidal effect of antibiotics may strengthen over time, reinforcing the clinical value of obtaining follow-up cultures after the treatment has begun, particularly in patients who show limited or delayed clinical improvement. Continued post-treatment sampling can serve as a practical tool to monitor patient prognosis, guide therapy adjustments, and identify bacterial strains with reduced susceptibility. This strategy is especially relevant in settings with a high burden of antimicrobial resistance where empirical treatment may not always align with pathogen sensitivity. Future studies should focus on characterizing the bacterial strains that persist after antibiotic initiation with particular attention to their resistance profiles. Such research is essential to determine whether persistent culture positivity reflects the presence of truly resistant organisms, delayed clearance, or other host-pathogen dynamics. Insights from these studies could inform more effective diagnostic algorithms and antibiotic stewardship strategies, ultimately improving clinical outcomes and preserving antibiotic efficacy. Abbreviations CI – Confidence Interval CSF - Cerebrospinal Fluid LMICs – Low and Middle Income Countries MRSA - Methicillin-Resistant strains of Staphylococcus aureus Declarations Ethical approval Not applicable. Consent for publication Not applicable. Availability of data and materials All data supporting the conclusions of this study are available from the corresponding author upon reasonable request. Competing interests The authors have no competing interests to declare. Acknowledgements We thank Covidence, a not-for-profit organization dedicated to quality evidence synthesis and its’ contribution to evidence-based decision-making for assigning a free review to the account managed by A.M.I. Funding The authors received no external funding to conduct this review. Contributions GMB and AMI performed protocol registration, risk of bias analysis, data analysis and drafted the manuscript. AMI and PJE participated in study screening and data extraction. All authors performed manuscript revision and approved the final version of the manuscript. References Baron EJ, Miller JM, Weinstein MP, Richter SS, Gilligan PH, Thomson RB, Jr., et al. 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Troendle M, Pettigrew A. A systematic review of cases of meningitis in the absence of cerebrospinal fluid pleocytosis on lumbar puncture. BMC Infectious Diseases [Internet]. 2019 [cited; 19(1):692. Available from: 10.1186/s12879-019-4204-z. Zay Ya K, Win PTN, Bielicki J, Lambiris M, Fink G. Association Between Antimicrobial Stewardship Programs and Antibiotic Use Globally: A Systematic Review and Meta-Analysis. JAMA Network Open [Internet]. 2023 [cited 5/3/2025]; 6(2):e2253806-e. Available from: 10.1001/jamanetworkopen.2022.53806. Hartman SJF, Brüggemann RJ, Orriëns L, Dia N, Schreuder MF, de Wildt SN. Pharmacokinetics and Target Attainment of Antibiotics in Critically Ill Children: A Systematic Review of Current Literature. Clinical Pharmacokinetics [Internet]. 2020 [cited; 59(2):173-205. Available from: 10.1007/s40262-019-00813-w. Kelesidis T, Kelesidis I, Rafailidis PI, Falagas ME. Counterfeit or substandard antimicrobial drugs: a review of the scientific evidence. Journal of Antimicrobial Chemotherapy [Internet]. 2007 [cited 5/2/2025]; 60(2):214-36. Available from: 10.1093/jac/dkm109. Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2021. Critical Care Medicine [Internet]. 2021 [cited; 49(11):e1063-e143. Available from: 10.1097/ccm.0000000000005337. Guarino M, Perna B, Cesaro AE, Maritati M, Spampinato MD, Contini C, et al. 2023 Update on Sepsis and Septic Shock in Adult Patients: Management in the Emergency Department. J Clin Med [Internet]. 2023 [cited; 12(9). Available from: 10.3390/jcm12093188. Kern WV, Rieg S. Burden of bacterial bloodstream infection—a brief update on epidemiology and significance of multidrug-resistant pathogens. Clinical Microbiology and Infection [Internet]. 2020 [cited; 26(2):151-7. Available from: https://doi.org/10.1016/j.cmi.2019.10.031. Bonten M, Johnson JR, van den Biggelaar AHJ, Georgalis L, Geurtsen J, de Palacios PI, et al. Epidemiology of Escherichia coli Bacteremia: A Systematic Literature Review. Clinical Infectious Diseases [Internet]. 2020 [cited 4/30/2025]; 72(7):1211-9. Available from: 10.1093/cid/ciaa210. MacKinnon MC, Sargeant JM, Pearl DL, Reid-Smith RJ, Carson CA, Parmley EJ, et al. Evaluation of the health and healthcare system burden due to antimicrobial-resistant Escherichia coli infections in humans: a systematic review and meta-analysis. Antimicrobial Resistance & Infection Control [Internet]. 2020 [cited; 9(1):200. Available from: 10.1186/s13756-020-00863-x. Adeiza SS, Islam MA, Shittu A. Global, regional, and national burdens: An overlapping meta-analysis on Staphylococcus aureus and its drug-resistant strains. One Health Bulletin [Internet]. 2024 [cited; 4(4):164-80. Available from: 10.4103/ohbl.ohbl_10_24. Haindongo EH, Ndakolo D, Hedimbi M, Vainio O, Hakanen A, Vuopio J. Antimicrobial resistance prevalence of Escherichia coli and Staphylococcus aureus amongst bacteremic patients in Africa: a systematic review. Journal of Global Antimicrobial Resistance [Internet]. 2023 [cited; 32:35-43. Available from: https://doi.org/10.1016/j.jgar.2022.11.016. Murray CJL, Ikuta KS, Sharara F, Swetschinski L, Robles Aguilar G, Gray A, et al. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. The Lancet [Internet]. 2022 [cited 2025/03/04]; 399(10325):629-55. Available from: 10.1016/S0140-6736(21)02724-0. Cite Share Download PDF Status: Published Journal Publication published 20 Dec, 2025 Read the published version in Systematic Reviews → Version 1 posted Reviewers agreed at journal 20 Jun, 2025 Reviewers invited by journal 20 Jun, 2025 Editor assigned by journal 19 Jun, 2025 First submitted to journal 19 Jun, 2025 Editorial decision: Major revision 18 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6651562","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":474113915,"identity":"ee508d2e-f2a1-401b-9c0d-4485e35aa50e","order_by":0,"name":"Annabel M Itaeli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYJACZgYGCx4gzXggoQJIsQNZDYS1SPCA9BxIOMPAwMNMpBYGsBbGNiK08M/uPfi5oEJCxp798IEDD+fZJO5nZj74cAaDnZwuDn0Sd84lS884A3QYT1rCgcRtaYk9zGzJhhsYko3NDuCw5kaOgTRvG8gvOQZALYeBWnjMJB8wANk4tMjfyDH+zfsPqIX//YcDiXOI0GJwI8dMmrcBqEUiB6isAaplAx4thkAt1jOOAbXceGZwIOFYmnHPYaBfZhjg9osc0GG3C2ps7Nn7kx8+/FFjI9ve3nzwYU+FnRxO7+MABqQpHwWjYBSMglGACgB1HlnrhzzvmwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0008-0961-2640","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":true,"prefix":"","firstName":"Annabel","middleName":"M","lastName":"Itaeli","suffix":""},{"id":474113916,"identity":"f8c269fc-f004-4261-82dc-8cfb31bc3f3d","order_by":1,"name":"Petra E Joseph","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Petra","middleName":"E","lastName":"Joseph","suffix":""},{"id":474113917,"identity":"8375b510-6855-4724-822c-fb51902dcf73","order_by":2,"name":"Bruno Sunguya","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Bruno","middleName":"","lastName":"Sunguya","suffix":""},{"id":474113918,"identity":"21587188-99df-4f67-ac6f-70141546a61e","order_by":3,"name":"George Msema Bwire","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"George","middleName":"Msema","lastName":"Bwire","suffix":""}],"badges":[],"createdAt":"2025-05-13 05:20:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6651562/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6651562/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13643-025-03032-6","type":"published","date":"2025-12-20T15:57:33+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85278695,"identity":"582c6244-bc3f-42fe-a082-cb7b1e3dc8c1","added_by":"auto","created_at":"2025-06-24 07:49:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":183029,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flow diagram illustrating the study selection process adopted from Covidence 2025\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6651562/v1/bcfb674b6c78d2e96b86aeb8.png"},{"id":85278693,"identity":"d0733c1a-a0dc-4cbc-9c7f-1fa505671fce","added_by":"auto","created_at":"2025-06-24 07:49:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":69698,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot showing the publication bias for studies included in the meta-analysis\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6651562/v1/253802c10875f577dfcc4e7d.png"},{"id":85279703,"identity":"95021189-6424-42fe-9fe3-51781ce351d4","added_by":"auto","created_at":"2025-06-24 07:57:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":129369,"visible":true,"origin":"","legend":"\u003cp\u003eProportion of bacterial growth before antibiotic administration. Each horizontal line represents a study’s proportion and 95% CI. The size of the grey square reflects the relative weight of each study. The diamond at the bottom indicates the pooled estimate of the proportion with its 95% CI.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6651562/v1/8358df7d19942965cdfc9123.png"},{"id":85280994,"identity":"fde5bd66-dce6-4255-9917-bd4385009263","added_by":"auto","created_at":"2025-06-24 08:13:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":165330,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing the proportion of bacterial growth after antibiotic administration.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6651562/v1/82a906768d47b25278bdf2ed.png"},{"id":85279707,"identity":"620fb4a4-2e21-41ca-a183-330c828ff679","added_by":"auto","created_at":"2025-06-24 07:57:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":300043,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing the proportion of positive bacterial culture after antibiotic administration, stratified by age category (adults, children and all age groups).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6651562/v1/5a949c589892d0eeb3429e69.png"},{"id":85278701,"identity":"233d403a-088f-4af9-a6ad-50814c283b47","added_by":"auto","created_at":"2025-06-24 07:49:09","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":269350,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing positive bacterial growth on culture after antibiotic administration, stratified by underlying medical condition.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6651562/v1/c38dbc68f1bfcdf48e52d4f3.png"},{"id":98815630,"identity":"7e8b39b5-b273-464f-af8f-d84fb7b74c6f","added_by":"auto","created_at":"2025-12-22 16:15:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1439446,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6651562/v1/19e5a634-c8d4-46d1-b09f-d7a80af83cf9.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eRate of bacterial positivity following antibiotic initiation: A systematic review and meta-analysis\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eBacterial cultures remain fundamental to the diagnosis of infectious diseases, providing definitive identification of pathogens and essential data for antimicrobial susceptibility testing (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The recovery of viable organisms from clinical specimens allows for precise, pathogen-directed therapy and supports antimicrobial stewardship efforts. However, culture-based diagnostics are highly sensitive to pre-analytical factors most notably, prior antibiotic exposure (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn clinical settings, empiric antibiotics are often administered before microbiological samples are collected, particularly in patients with suspected severe infections. Although early treatment is critical for improving outcomes (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), it can significantly impair diagnostic accuracy. Antibiotics may suppress or eliminate viable bacteria at the site of infection, leading to false-negative culture results. This can complicate clinical decision-making, delay appropriate therapy adjustments, and contribute to unnecessary continuation of broad-spectrum antimicrobial agents (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe impact of antibiotic administration on culture positivity varies across specimen types, timing, and the pharmacodynamics of the drugs involved (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Blood, cerebrospinal fluid, pleural and peritoneal fluids, bile, synovial fluid, tissue biopsies, and wound swabs are all affected to varying degrees. Some specimens, such as blood, may exhibit a rapid decline in culture yield due to immediate systemic antibiotic distribution, while others such as bile or pleural fluid may retain diagnostic value for a longer period. The variability in antimicrobial tissue penetration and local immune responses further complicates predictions about culture yield following therapy (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn response to these challenges, molecular diagnostic technologies, including polymerase chain reaction (PCR) and fluorescence in situ hybridization (FISH), have gained traction in clinical microbiology (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). These methods offer faster turnaround times and can detect microbial DNA or RNA even in the absence of viable organisms. However, they often lack the ability to provide antimicrobial susceptibility data and may not detect all clinically relevant pathogens. As such they are complementary rather than substitutive to traditional culture methods.\u003c/p\u003e \u003cp\u003eAlthough the suppressive effect of antibiotics on culture growth is widely acknowledged, the degree and timing of this effect remains inconsistently described in the literature. Variations in study design, clinical context, sample collection protocols, and diagnostic methods have led to the conflicting findings, making it difficult to draw generalized conclusions. Moreover, much of the available evidence is limited to single-centre studies or specific infection types, limiting its broader applicability. This systematic review was therefore undertaken to consolidate existing evidence on the effect of antibiotic administration on bacterial culture positivity.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eStudy design and search strategy\u003c/p\u003e\u003cp\u003eThis review was registered in the International Prospective Register for Systematic Reviews (PROSPERO: CRD42025648397). The review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA)(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Relevant evidence was extracted from PubMed, Embase, Scopus and Web of Science spanning from database inception to 4th March 2025, except for PubMed, where the search was updated until 12th March 2025. The search terms and search strategy for the research question were developed with assistance for the research librarian and adapted to each database. The keywords included ‘antibiotics’, ‘antibacterial agents’, ‘antibacterial therapy’, ‘antibiotic administration’ ,‘bacterial infection’, ‘bacterial culture’, ‘positivity rate’, ‘culture positivity’, ‘diagnostic yield’, and ‘culture growth’. The review team used MeSH (medical sub-heading terms) for PubMed search, while Boolean operator ‘AND’ combined both or all of the keywords, while ‘OR’ searched articles containing at least one of the keywords.\u003c/p\u003e\u003cp\u003eStudy selection\u003c/p\u003e\u003cp\u003eArticles obtained from the database search were uploaded to Covidence software (Veritas Health Innovation, Melbourne, Australia) which identified and removed duplicates. Two reviewers (A.M.I \u0026amp; P.E.J) independently conducted titles and abstract screening using the COVIDENCE software, selecting articles that described bacterial growth on culture and bacterial culture results of patients with clinically confirmed infection. During full-text screening, the two reviewers (A.M.I \u0026amp; P.E.J) excluded studies that were not open access, studies with bacterial culture results without evidence of antibiotic administration, studies without specification of the participants who received antibiotics, studies without bacterial culture results after antibiotic administration and culture samples taken within one hour after antibiotic administration. The discrepancies were resolved by the third reviewer (G.M.B).\u003c/p\u003e\u003cp\u003eData extraction and narrative synthesis\u003c/p\u003e\u003cp\u003eTwo independent reviewers (A.M.I \u0026amp; P.E.J) extracted data from the included studies using a standardized excel spreadsheet including the author, publication year, country, study design, age group, disease condition, key finding, study limitation, number of events and total population before and after antibiotic administration. The two reviewers (A.M.I \u0026amp; P.E.J) independently and inductively conducted thematic mapping of the key themes and findings from the included articles relevant to the study objectives.\u003c/p\u003e\u003cp\u003eRisk of Bias\u003c/p\u003e\u003cp\u003eTwo independent reviewers (A.M.I and G.M.B) use the Newcastle-Ottawa Scale (NOS) to assess the included studies. The NOS which consists of a total of 9 questions encompassing participant selection, cohort comparability, and outcome evaluation by two authors. The responses to the questions were assigned a score of 1 for indicated weighted responses and 0 for all other responses. The final score of each article was reached upon consensus of the reviewers.\u003c/p\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eWe analysed data using in R Version 2024.12.1 + 563. Proportions of bacterial growth from the included studies were calculated with logit transformation (‘PLOGIT’) applied as the summary measure to account for the wide range of proportions. The weighted prevalence [(95% Confidence Interval (CI)] of bacterial growth on culture was estimated using random effects model and presented in forest plots. Meta-analyses were performed for studies that reported proportions of bacterial growth before and after antibiotic administration. Study heterogeneity was assessed using the \u003cem\u003eI²\u003c/em\u003e statistic. The Egger’s linear regression test of funnel plot asymmetry was also performed (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). A p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e\u003cp\u003eIn this review, the number of events (n) and total population (N) were defined as the number of samples (culture bottles) showing positive bacterial growth if specified, or alternatively the number of patients with bacterial growth on culture among those who received antibiotics or were sampled. When both sample-level and patient-level data were available, we prioritized the number of samples. Meta-analysis was restricted to studies that reported bacterial culture results both before and after antibiotic administration.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOur evidence search yielded 1,226 articles which were all uploaded to Covidence for screening. Seventy duplicates were removed, and 1,118 articles were excluded based on the study title and abstract. Thirty-eight articles were assessed for eligibility, of which 11 articles met the inclusion criteria for full-text analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The included articles involved over 67,330 samples with culture results after antibiotic administration. Seven articles were eligible in meta-analysis, comprising of more than 12,399 culture samples taken prior to antibiotic administration and about 7,560 culture samples after antibiotic administration.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStudy characteristics\u003c/p\u003e \u003cp\u003eThe included studies were published between 2011(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) and 2024 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Three out of the 11 included articles were prospective studies which deployed various methods including cross-sectional (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), case-control (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), and cohort (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) study. Of the eight retrospective studies included, two analysed previously collected tissue samples (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), while six utilized data from electronic health records (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), including one time-series retrospective cohort study (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). All retrospective studies were conducted in high-income countries with established electronic health records systems including the USA (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), Italy (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), Australia (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), Belgium (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), Poland (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) and Germany (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) that facilitated the availability of the required data for retrieval. Only one study has been conducted in several countries across Asia (Thailand) and Africa (the Gambia, Kenya, Mali, South Africa and Zambia) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Two articles performed bacterial culture detection using both culture and molecular diagnostic methods namely, PCR (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Methodological quality was assessed in all included articles, of which eight articles had moderate quality (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) and three articles had good quality (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the included articles, key findings and methodological quality.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAuthor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStudy design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePopulation characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eSample characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAntibiotic resistance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKey findings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMethodological quality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDisease condition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTissue biopsy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAntibiotic given\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAntibiotic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBanks 2011 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProspective cohort study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePost radical prostatectomy secondary to Prostate Cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCefazolin or TMT-SMZ or Cephalexin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAmpicillin, Ciprofloxacin, Penicillin, Norfloxacin, cefazolin and tetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow burden of symptoms despite the high frequency of bacteriuria.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDriscoll 2017 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCase-control study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 countries: Bangladesh, The Gambia, Kenya, Mali, South Africa, Thailand and Zambia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChildren (\u0026lt;\u0026thinsp;5yrs) 1\u0026ndash;59 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSevere or very severe Pneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood, nasopharyngeal swabs, sputum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eExposure to antibiotics reduces bacterial yield on culture by 45%.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eGood quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDutta 2022 (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective time series cohort study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBlood cultures collected after intravenous antibiotic administration had reduced bacterial positivity rates.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHummel 2009 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAll age groups (16-85yrs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHaematological malignancy with episodes of neutropenic fever.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePiperacillin with a beta-lactam inhibitor or carbapenem as monotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBlood culture sampling is useful in patients with febrile neutropenia even after antibiotic therapy initiation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKim 2024 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInfectious spondylitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood, infected disc and swab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePre-operative antibiotic treatment may reduce the sensitivity of microbiological detection, particularly in blood and tissue cultures. Blood culture shows higher sensitivity to bacterial growth than swab and tissue culture.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLucignano 2011 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective cohort study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChildren (\u0026lt;\u0026thinsp;18 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSystemic Inflammatory Response Syndrome (SIRS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBlood cultures detect a wider variety of bacterial species. Molecular diagnostics offer higher sensitivity and faster results.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eGood quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWang 2020 (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAustralia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHaematological malignancies with febrile neutropenia.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBlood cultures collected more than 24 hours after initiation of broad spectrum antibiotics yield less clinically relevant micro-organisms.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScheer 2018 (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProspective cohort study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSevere sepsis, septic shock.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBeta lactam antibiotics, cephalosporins, carbapenems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLess pathogens detection occurs after initiation of antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eGood quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStankey 2018 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective cohort study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChildren\u0026thinsp;\u0026lt;\u0026thinsp;18 yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePleural empyema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBlood cultures show a greater decline in positivity following antibiotic administration compared to pleural fluid cultures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoethem 2022 (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective cohort study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBelgium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAll age groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBacteraemia (UTI, pyomyositis, endocarditis, meningitis)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eVancomycin or Beta-lactam antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eThe highest probability of detecting \u003cem\u003eStaphylococcus aureus\u003c/em\u003e Bacteraemia is achieved by collecting two blood culture sets on days 2 and 4 after initiation of therapy.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZrodlowski 2018 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrospective cohort study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChildren (\u0026lt;\u0026thinsp;18 yrs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNot specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMolecular diagnostic methods such as FISH and PCR enable preliminary detection of bacteria before culture results are available, making them useful for screening purposes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKeywords\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eFluorescent in situ hybridisation (FISH)\u003c/p\u003e \u003cp\u003ePolymerase Chain Reaction (PCR)\u003c/p\u003e \u003cp\u003eTrimethoprim sulfamethoxazole (TMT-SMZ)\u003c/p\u003e \u003cp\u003eUrinary tract infection (UTI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePublication bias\u003c/p\u003e \u003cp\u003eThe funnel plot demonstrated asymmetrical distribution of studies around the central vertical line (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Five out of 7 studies (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) clustered at the top, indicating larger studies with smaller standard errors. This pattern suggests potential publication bias and supports previously observed high heterogeneity in the meta-analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCommonly isolated bacteria\u003c/p\u003e \u003cp\u003eTen of the 11 included articles indicated the types of bacteria isolated upon culture (\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). For convenience, we identified the 3 most frequently isolated bacteria and categorised as either gram-positive or gram-negative. \u003cem\u003eEscherichia coli\u003c/em\u003e was the most isolated gram-negative bacteria (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In this review, all studies with leading \u003cem\u003eEscherichia coli\u003c/em\u003e isolates involved adult patients (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) with urinary tract infections (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), infectious spondylitis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), sepsis (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) and febrile neutropenia (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). However, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e as isolated among newborns with sepsis (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) and adults with infectious spondylitis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) and underlying co-morbidities such as haematological malignancies (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) and prostate cancer (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e infections were mainly from patients with compromised immunity, prolonged hospital stay or from medical interventions such as urinary-catheter use.\u003c/p\u003e \u003cp\u003eThe most common gram-positive bacteria isolates were \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). \u003cem\u003eStaphylococcus aureus\u003c/em\u003e isolates were respiratory tract infections in paediatrics (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and blood borne infections in adults (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e was isolated from adults with infectious spondylitis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) and paediatrics with respiratory tract infections such as pneumonia (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) and empyema (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e isolates were from adults with suspected hospital acquired infections from urinary catheters (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) and with comorbidities including haematological malignancies (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCommonly prescribed antibiotics and resistance patterns\u003c/p\u003e \u003cp\u003eSeven studies reported on the antibiotics prescribed to the patients prior to culture sample collection. These include Trimethoprim-Sulfamethoxazole (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), cephalosporins (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) such as ciprofloxacin (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) and cephalexin (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), and penicillin including amoxicillin (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) and piperacillin (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). \u003cem\u003eStaphylococcus aureus\u003c/em\u003e was identified to be resistant to ampicillin, ciprofloxacin, penicillin, norfloxacin, cefazolin, and tetracycline (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) and Methicillin-Resistant strains of \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (MRSA) were identified (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Additionally, \u003cem\u003eEscherichia coli\u003c/em\u003e was identified to be resistant to fluoroquinolones.\u003c/p\u003e \u003cp\u003eEffects of antibiotics on bacterial growth with time\u003c/p\u003e \u003cp\u003eThe use of antibiotic therapy was identified to reduce bacterial growth on culture. Two articles reported that antibiotics reduced culture positivity following antibiotic administration (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Additionally, two studies demonstrated that bacterial growth on culture further declined with continued antibiotic use over time (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Wang \u003cem\u003eet al\u003c/em\u003e reported a 44.65% decrease in bacterial growth of culture samples collected 24 hours after initiation of broad spectrum antibiotics (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Goethem \u003cem\u003eet al\u003c/em\u003e. further highlighted the importance of timing by examining Staphylococcus aureus growth longitudinally for 5 consecutive days (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). This study recommended follow-up cultures between day 2 and day 4 after antibiotic initiation to detect persistent bacteraemia (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Although their approach of collecting blood cultures over five consecutive days detects the gradual decline of ongoing infection, it remains largely impractical in routine clinical settings due to cost and resource limitations.\u003c/p\u003e \u003cp\u003eBacterial growth before antibiotic administration\u003c/p\u003e \u003cp\u003eSeven articles were meta-analysed to estimate the proportion of positive bacterial cultures prior to antibiotic administration (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The pooled proportion was 37% (95% CI: 20%-56%), indicating that, 37% culture sample are positive before antibiotic administration. There was substantial heterogeneity across the studies ( \u003cem\u003eI\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e: 99.5%, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as reflected by the wide range reported proportions ranging from 10% as reported by Lucignano 2011 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) to 74% as reported by Kim 2011 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, the relatively narrow confidence intervals of the individual studies suggest good precision within each study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBacterial growth after antibiotic administration\u003c/p\u003e \u003cp\u003eEleven articles were included in the meta-analysis to estimate the proportion of bacterial growth following antibiotic administration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The pooled proportion of positive cultures was 18% (95% CI: 10%-29%), indicating that 18% of cultures remained positive after antibiotic administration. Significant heterogeneity was observed across studies (\u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e: 99.8%, p-value\u0026thinsp;=\u0026thinsp;0), which is reflected in the wide variation in sample size and culture positivity rates-ranging from 4% as reported by Dutta 2022 (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) to 55% as reported by Goethem 2022 (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSub-group analysis of bacterial growth after antibiotic administration\u003c/p\u003e \u003cp\u003eBased on patient age\u003c/p\u003e \u003cp\u003eParticipants of the included studies were categorized by age into three groups: children (under 18 years), adults (above 18 years) and all age groups (if participants were inclusive of both children and adults). The pooled proportion of bacterial positivity following antibiotic initiation was 22% (95%CI: 4%-68%) for all age groups, 18% (95% CI: 8%-35%) in adults and 16% (95%CI: 8%-30%) in children (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on the underlying medical condition\u003c/p\u003e \u003cp\u003eIn this review, we classified the included studies into two categories: those involving with patients with underlying medical conditions (such as cancer) and patient with primary clinical infections, considered as without underlying medical conditions. The pooled proportion of bacterial positivity following antibiotic administration was 24% (95% CI: 12%-41%) in patients without underlying medical condition and 10% (95% CI: 6%-18%) in those with underlying medical conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eEvidence pooled from 11 studies with 67,330 culture samples from participants who had already taken antibiotics, has shown that bacterial growth on culture declines from 37% before antibiotic therapy to 18% after antibiotic administration. The common isolated bacteria were \u003cem\u003eEscherichia coli, Staphylococcus aureus\u003c/em\u003e and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eAll (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) except one (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) of the included articles were conducted in high-income countries, where health systems and financing schemes facilitate access to culture sampling for patients. These settings also benefit from well-established health information systems that support efficient data retrieval for retrospective analyses. In contrast, only one study (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) included participants from low- and middle-income countries (LMICs), specifically from Africa and Asia. There were no retrospective studies conducted in LMICs, likely due to limited access to culture sampling, which often requires out-of-pocket payment and lack of uniform health information systems (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Consequently, representation from LMICs is largely limited to prospective, research-funded studies, highlighting a critical gap in the availability of good quality routine data from these regions.\u003c/p\u003e \u003cp\u003eBacterial positivity prior to antibiotic administration was relatively low, with a pooled estimate of 37% (95% CI: 20%-56%). A potential explanation for this finding is that some patients may have had non-bacterial infections, such as viral sepsis, which mimic the clinical presentations of bacterial infections (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Alternately, the low bacterial growth prior to antibiotic administration could be attributed to heterogeneity in study design and sample types. The variation in sample types and laboratory culture practices influences the positivity rates. For example, blood cultures often yield bacterial growth compared to Cerebrospinal Fluid (CSF) cultures, which in meningitis cases, may exhibit pleocytosis (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Additionally, the variation in study designs including the reporting bias related to antibiotic use, makes it uncertain whether the participants had self-medicated prior to treatment initiation. However, majority of the included studies were conducted in high-income countries where antibiotic use is typically regulated, which may limit the extent of unreported pre-treatment exposure (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur review did not assess the appropriateness of antibiotic prescribing practices in individual studies, nor did it account for the potential use of sub-optimal or counterfeit antibiotics. We observed bacterial growth after antibiotic administration with a pooled estimate of 18% (95% CI: 10%-29%). This persistent bacterial growth could be attributed to several reasons including sub-optimal dosing (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), use of counterfeit antibiotics (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), and timing of sample collection relative to antibiotic initiation (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). While existing guidelines for sepsis management emphasize the importance of obtaining cultures before initiating antibiotics in suspected sepsis (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), however there are no specific recommendations on culture sampling after antibiotics initiation. Based on the current findings on bacterial growth post-antibiotics, we recommend considering sampling for bacterial culture even when the patient has been initiated antibiotics, where feasible. This could aid monitoring the patient prognosis.\u003c/p\u003e \u003cp\u003eThe top three isolated bacteria in this review; \u003cem\u003eEscherichia Coli\u003c/em\u003e, \u003cem\u003eStaphylococcus aureus\u003c/em\u003e and Pseudomonas aeruginosa, consistent with the well-documented global burden of bacterial bloodstream infections (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). All of the articles that identified \u003cem\u003eEscherichia Coli\u003c/em\u003e as the most predominant isolated gram-negative were from high-income countries. This finding aligns with the known epidemiological patterns of \u003cem\u003eEscherichia Coli\u003c/em\u003e, which is responsible for approximately 27% of documented bacteraemia episodes in high income countries (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The burden of \u003cem\u003eEscherichia Coli\u003c/em\u003e is reported to be particularly high among adults and among patients with urogenital infections (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) consistent with our findings. Our review identified fluoroquinolone resistance in Escherichia coli, consistent with existing literature, which highlights that infections with resistant strains are more persistent than those caused by susceptible strains (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe global prevalence of \u003cem\u003eStaphylococcus aureus\u003c/em\u003e colonization in humans is estimated at 24.9%, underscoring its clinical predominance (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). This finding is consistent with our review, in which \u003cem\u003eStaphylococcus aureus\u003c/em\u003e was the most commonly isolated gram-positive bacterium across the included studies. This review found \u003cem\u003eStaphylococcus aureus\u003c/em\u003e to be predominantly resistant to third-generation penicillin, particularly ampicillin (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), which contrasts with a recent systematic review from Africa indicating higher resistance to second-generation penicillin (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Overall, the existing evidence underscores \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e as the leading antimicrobial resistant pathogens associated with mortality worldwide (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStrength and limitations\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this is the first systematic review that analyses the bacterial growth on culture after antibiotic administration. However, our findings should be interpreted in the light of the following limitations. We calculated the proportion of bacterial growth on culture after antibiotic administration based on either the number of samples or the number of patients with positive cultures, depending on what was reported. However, we did not account for the possibility of multiple samples being collected from a single patient, nor did we standardize for the recommended diagnostic practice of obtaining 2\u0026ndash;3 culture bottles in cases of suspected bacteraemia. The included studies varied widely in their culture methodologies and sampling protocols, which may have contributed to differences in bacterial positivity rates and introduced heterogeneity into the pooled estimates. Only a limited number of studies reported bacterial growth on culture prior to antibiotic administration, which constrained our ability to produce a robust pooled estimate for this group.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBacterial culture positivity was lower after antibiotic administration compared to pre-treatment levels, indicating a reduction in viable bacterial load following therapy. However, the continued presence of bacterial growth in some samples suggests that certain pathogens may persist despite treatment, potentially due to delayed antibiotic action, inadequate tissue penetration, or emerging resistance. These findings imply that the bactericidal effect of antibiotics may strengthen over time, reinforcing the clinical value of obtaining follow-up cultures after the treatment has begun, particularly in patients who show limited or delayed clinical improvement.\u003c/p\u003e \u003cp\u003eContinued post-treatment sampling can serve as a practical tool to monitor patient prognosis, guide therapy adjustments, and identify bacterial strains with reduced susceptibility. This strategy is especially relevant in settings with a high burden of antimicrobial resistance where empirical treatment may not always align with pathogen sensitivity. Future studies should focus on characterizing the bacterial strains that persist after antibiotic initiation with particular attention to their resistance profiles. Such research is essential to determine whether persistent culture positivity reflects the presence of truly resistant organisms, delayed clearance, or other host-pathogen dynamics. Insights from these studies could inform more effective diagnostic algorithms and antibiotic stewardship strategies, ultimately improving clinical outcomes and preserving antibiotic efficacy.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCI \u0026ndash; Confidence Interval\u003c/p\u003e\n\u003cp\u003eCSF - Cerebrospinal Fluid\u003c/p\u003e\n\u003cp\u003eLMICs \u0026ndash; Low and Middle Income Countries\u003c/p\u003e\n\u003cp\u003eMRSA - Methicillin-Resistant strains of \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eAll data supporting the conclusions of this study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe thank Covidence, a not-for-profit organization dedicated to quality evidence synthesis and its\u0026rsquo; contribution to evidence-based decision-making for assigning a free review to the account managed by A.M.I.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe authors received no external funding to conduct this review.\u003c/p\u003e\n\u003cp\u003eContributions\u003c/p\u003e\n\u003cp\u003eGMB and AMI performed protocol registration, risk of bias analysis, data analysis and drafted the manuscript. AMI and PJE participated in study screening and data extraction. \u0026nbsp;All authors performed manuscript revision and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBaron EJ, Miller JM, Weinstein MP, Richter SS, Gilligan PH, Thomson RB, Jr., et al. A Guide to Utilization of the Microbiology Laboratory for Diagnosis of Infectious Diseases: 2013 Recommendations by the Infectious Diseases Society of America (IDSA) and the American Society for Microbiology (ASM)a. Clinical Infectious Diseases [Internet]. 2013 [cited 5/6/2025]; 57(4):e22-e121. Available from: 10.1093/cid/cit278.\u003c/li\u003e\n\u003cli\u003ePeker N, Couto N, Sinha B, Rossen JW. Diagnosis of bloodstream infections from positive blood cultures and directly from blood samples: recent developments in molecular approaches. Clin Microbiol Infect [Internet]. 2018 [cited; 24(9):944-55. 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Available from: 10.1016/S0140-6736(21)02724-0.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"systematic-reviews","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sysr","sideBox":"Learn more about [Systematic Reviews](http://systematicreviewsjournal.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/sysr/default.aspx","title":"Systematic Reviews","twitterHandle":"@MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Bacterial Positivity, Culture, Antibiotic Use","lastPublishedDoi":"10.21203/rs.3.rs-6651562/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6651562/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBacterial culture remains a critical tool for pathogen identification and antimicrobial susceptibility testing. However, its diagnostic accuracy is often compromised by prior antibiotic administration, which can reduce the recovery of viable organisms and lead to false-negative results. Given the variability and limitation in existing studies, a systematic review is needed to better understand the influence of antibiotics on culture yield.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted an electronic search in PubMed, Embase, Scopus and Web of Science from their inception through March 2025. The Newcastle-Ottawa Scale was used to assess the methodological quality of the included articles. Random effect models were used to estimate the proportions and 95% Confidence Intervals (CI). The protocol for this review was registered in the PROSPERO: CRD42025648397.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 1,226 articles obtained from the search, 11 were eligible. They consisted of 67,330 samples with culture results after antibiotic administration. The pooled proportion for bacterial growth was 37% (95% CI: 20%-56%) and 18% (95% CI: 10%-29%) before and after antibiotic administration, respectively. Significant heterogeneity (\u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e: 99.8%, p-value\u0026thinsp;=\u0026thinsp;0) was observed across the included studies.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBacterial growth decreased by more than half following antibiotic administration, indicating a strong suppressive effect. This highlights the importance of considering the timing of sample collection in relation to antibiotic initiation. Where necessary, particularly in cases of uncertain clinical progress, sampling after antibiotic administration can be useful for monitoring prognosis and guiding further treatment decisions.\u003c/p\u003e","manuscriptTitle":"Rate of bacterial positivity following antibiotic initiation: A systematic review and meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-24 07:49:04","doi":"10.21203/rs.3.rs-6651562/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-06-20T13:46:28+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-20T12:46:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-20T00:47:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Systematic Reviews","date":"2025-06-19T09:28:51+00:00","index":"","fulltext":""},{"type":"decision","content":"Major revision","date":"2025-06-18T12:22:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"systematic-reviews","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sysr","sideBox":"Learn more about [Systematic Reviews](http://systematicreviewsjournal.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/sysr/default.aspx","title":"Systematic Reviews","twitterHandle":"@MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8f35d1d6-c6ac-4827-8f0f-f2c0a3594de5","owner":[],"postedDate":"June 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-22T16:13:31+00:00","versionOfRecord":{"articleIdentity":"rs-6651562","link":"https://doi.org/10.1186/s13643-025-03032-6","journal":{"identity":"systematic-reviews","isVorOnly":false,"title":"Systematic Reviews"},"publishedOn":"2025-12-20 15:57:33","publishedOnDateReadable":"December 20th, 2025"},"versionCreatedAt":"2025-06-24 07:49:04","video":"","vorDoi":"10.1186/s13643-025-03032-6","vorDoiUrl":"https://doi.org/10.1186/s13643-025-03032-6","workflowStages":[]},"version":"v1","identity":"rs-6651562","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6651562","identity":"rs-6651562","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}