Authors: Annabel M. Itaeli, Petra E. Joseph, Bruno F. Sunguya, George Msema Bwire
Categories: Research, Bacterial positivity, Culture, Antibiotic use
Source: Systematic Reviews
Authors: Annabel M. Itaeli, Petra E. Joseph, Bruno F. Sunguya, George Msema Bwire
Bacterial 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 limitations in the existing studies, a systematic review is needed to better understand the influence of antibiotics on culture yield.
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 effects models were used to estimate the proportions and 95% Confidence Intervals (CIs). The protocol for this review was registered in PROSPERO: CRD42025648397.
Of the 1226 articles obtained from the search, 11 were eligible. The eligible articles comprised 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 < 0.001) was observed across the included studies.
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.
PROSPERO: CRD42025648397
Bacterial cultures remain fundamental in 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 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].
Bacterial infections constitute a substantial global health burden, accounting for an estimated 13% of worldwide mortality in 2019 [4]. These pathogens were implicated in 56.2% of sepsis-related deaths, with Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa emerging as the predominant clinically significant organisms [4]. In clinical practice, empiric antibiotics are often administered before microbiological samples are collected, especially in patients with suspected severe infections. Prompt antibiotic administration, particularly within 1 to 3 h of sepsis diagnosis, has been shown to reduce in-hospital mortality [5]. Although early treatment is critical for improving outcomes [6], 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 [7].
The impact of antibiotic administration on culture positivity varies across specimen types, timing, and the pharmacodynamics of drugs involved [8]. 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 [9].
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 [10]. 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. Therefore, they serve as complementary rather than substitutive to traditional culture methods. Moreover, their availability remains limited in resource-constrained settings, particularly in low- and middle-income countries (LMICs), where empirical treatment is the norm due to minimal access to culture diagnostics [11].
Although the suppressive effect of antibiotics on culture growth is widely acknowledged, the degree and timing of this effect remain inconsistently described in the literature. Variations in study design, clinical context, sample collection protocols, and diagnostic methods have led to 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. Prior systematic reviews have either focused narrowly on specific pathogens [12, 13] or clinical scenarios [14] and have not adequately addressed the relationship between antibiotic administration and culture yield. This systematic review was therefore undertaken to consolidate existing evidence on the effect of antibiotic administration on bacterial culture positivity.
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) [15]. 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 strategies for the research question were developed with the assistance of a 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 the PubMed search. Boolean operators were ‘AND’ was used to combine keywords, and ‘OR’ was used to link synonyms or related terms within a concept.
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 and P.E.J) independently conducted title and abstract screening using the COVIDENCE software. We initially included articles that reported bacterial growth on culture in patients with clinically confirmed infection who had received antibiotic treatment. During full-text screening, the two reviewers (A.M.I and P.E.J) excluded studies that were not open access, lacked evidence of antibiotic administration alongside bacterial culture results, did not specify which participants received antibiotics, did not report bacterial culture results after antibiotic administration or collected culture samples less than 8 h after initial antibiotic administration. The discrepancies were resolved by a third reviewer (G.M.B).
Two independent reviewers (A.M.I and P.E.J) extracted data from the included studies using a standardized excel spreadsheet. The variables extracted include study author, publication year, country, study design, age group, disease condition, key finding, study limitation, number of events, and proportion of bacterial growth on culture (frequency/total) before and after antibiotic administration. The two reviewers (A.M.I and P.E.J) independently and inductively conducted thematic mapping of the key themes and findings from the included articles relevant to the study objectives.
Two independent reviewers (A.M.I and G.M.B) used the Newcastle–Ottawa Scale (NOS) to assess the included studies. The NOS consists of a total of 9 questions encompassing participant selection, cohort comparability, and outcome evaluation. 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.
We analysed data using 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 a 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 I^2^ statistic. The Egger’s linear regression test of funnel plot asymmetry was also performed [16]. A p-value of less than 0.05 was considered statistically significant.
In this review, bacterial positivity was calculated as the proportion of samples with positive growth (number of events, n) divided by the total sample (N). The total sample (N) comprised the total number of cultured samples. When both sample-level and patient-level data were available, we reported the number of samples. Meta-analysis was restricted to studies that reported bacterial culture results both before and after antibiotic administration. Notably, bacterial positivity was equally weighted across different specimen types, including blood, swabs, and sputum.
Our evidence search yielded 1226 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 culture sample results after antibiotic administration. Seven articles were eligible in meta-analysis, comprising more than 12,399 culture samples taken prior to antibiotic administration and about 7560 culture samples after antibiotic administration.Fig. 1PRISMA flow diagram illustrating the study selection process adopted from Covidence 2025
The included studies were published between 2011 [17] and 2024 [18]. Three out of the 11 included articles were prospective studies of several study designs including cross-sectional [19], case–control [20], and cohort [21] designs. Of the eight included retrospective studies, two analysed previously collected tissue samples [18, 22], while six retrieved data from electronic health records [17, 23–26], including one time-series retrospective cohort study [27]. All retrospective studies were conducted in high-income countries with established electronic health records systems including the USA [23, 27], Italy [17], Australia [26], Belgium [24], Poland [22] and Germany [25] that facilitated the availability of the required data for retrieval. Only one study was conducted in several countries across Asia (Thailand) and Africa (the Gambia, Kenya, Mali, South Africa, and Zambia) [20]. Two articles performed bacterial culture detection using both culture and molecular diagnostic methods, namely, PCR [20, 22]. Methodological quality was assessed in all included articles, of which eight articles had moderate quality [18, 19, 22–27] and three articles had good quality [17, 20, 21] (Table 1). Table 1Characteristics of the included articles, key findings and methodological qualityAuthorStudy designCountryPopulation characteristicsSample characteristicsAntibiotic resistanceKey findingsMethodological qualityAge groupDisease conditionTissue biopsyAntibiotic givenAntibiotic Banks 2011 [19] Prospective cohort studyUSAAdultsPost-radical prostatectomy secondary to prostate cancerUrineCefazolin or TMT-SMZ or CephalexinAmpicillin, Ciprofloxacin, Penicillin, Norfloxacin, cefazolin and tetracyclineLow burden of symptoms despite the high frequency of bacteriuria.Moderate quality Driscoll 2017 [20] Case–control study7 Bangladesh, The Gambia, Kenya, Mali, South Africa, Thailand, and ZambiaChildren (< 5 years) 1–59 monthsSevere or very severe pneumoniaBlood, nasopharyngeal swabs, sputumNot specifiedNot specifiedExposure to antibiotics reduces bacterial yield on culture by 45%Good quality Dutta 2022 [27] Retrospective time series cohort studyUSAAdultsSepsisBloodNot specifiedNot specifiedBlood cultures collected after intravenous antibiotic administration had reduced bacterial positivity rates.Moderate quality Hummel 2009 [25] Retrospective studyGermanyAll age groups (16–85 years)Haematological malignancy with episodes of neutropenic feverBloodPiperacillin with a beta-lactam inhibitor or carbapenem as monotherapyNot specifiedBlood culture sampling is useful in patients with febrile neutropenia even after antibiotic therapy initiation.Moderate quality Kim 2024 [18] Retrospective studySouth KoreaAdultsInfectious spondylitisBlood, infected disc and swabNot specifiedNot specifiedPre-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 [17] Retrospective cohort studyItalyChildren (< 18 years)Systemic inflammatory response syndrome (SIRS)BloodNot specifiedNot specifiedBlood cultures detect a wider variety of bacterial species. Molecular diagnostics offer higher sensitivity and faster results.Good quality Wang 2020 [26] Retrospective studyAustraliaAdultsHaematological malignancies with febrile neutropeniaBloodNot specifiedNot specifiedBlood cultures collected more than 24 h after initiation of broad spectrum antibiotics yield less clinically relevant micro-organisms.Moderate quality Scheer 2018 [21] Prospective cohort studyGermanyAdultsSevere sepsis, septic shockBloodBeta lactam antibiotics, cephalosporins, carbapenemsNot specifiedLess pathogens detection occurs after initiation of antibiotics.Good quality Stankey 2018 [23] Retrospective cohort studyUSAChildren < 18 yearsPleural empyemaBloodNot specifiedNot specifiedBlood cultures show a greater decline in positivity following antibiotic administration compared to pleural fluid cultures.Moderate qualityGoethem 2022 [24]Retrospective cohort studyBelgiumAll age groupsBacteraemia (UTI, pyomyositis, endocarditis, meningitis)BloodVancomycin or Beta-lactam antibioticsNot specifiedThe 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 qualityZrodlowski 2018 [22]Retrospective cohort studyPolandChildren (< 18 years)SepsisBloodNot specifiedNot specifiedMolecular 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
The funnel plot demonstrated asymmetrical distribution of studies around the central vertical line (Fig. 2). Five out of 7 studies [18, 20, 21, 23, 25] 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.Fig. 2Funnel plot showing the publication bias for seven studies included in the meta-analysis
Ten of the 11 included articles indicated the types of bacteria isolated upon culture [17–26]. For ease of interpretation, we identified the three most frequently isolated bacterial species and categorised them as either gram-positive or gram-negative. Escherichia coli [18, 19, 21, 25, 26] and Pseudomonas aeruginosa [17–19, 26] were the most frequently isolated gram-negative bacteria. In this review, all studies with Escherichia coli as the leading isolated bacterial species involved adult patients [18, 19, 21, 25, 26] with urinary tract infections [19], infectious spondylitis [18], sepsis [21] and febrile neutropenia [25, 26]. However, Pseudomonas aeruginosa was the prominent isolated bacterial species among newborns with sepsis [17] and adults with infectious spondylitis [18] and patients with underlying co-morbidities such as haematological malignancies [26] and prostate cancer [19]. Pseudomonas aeruginosa isolates were mainly from patients with compromised immunity, prolonged hospital stays, or from medical interventions such as urinary-catheter use.
The most common gram-positive bacterial isolates were Staphylococcus aureus [18, 20, 21, 23, 24], Streptococcus pneumoniae [18, 20, 23] and Staphylococcus epidermidis [19, 26]. Staphylococcus aureus isolates were from respiratory tract infections in paediatrics [20, 23] and blood-borne infections in adults [18, 21]. Streptococcus pneumoniae was isolated from adults with infectious spondylitis [18] and paediatrics with respiratory tract infections such as pneumonia [20] and empyema [23]. Staphylococcus epidermidis isolates were from adults with suspected hospital-acquired infections from urinary catheters [19] and with comorbidities including haematological malignancies [26].
Seven studies specified the antibiotics prescribed to patients prior to culture sample collection. These include Trimethoprim-Sulfamethoxazole [19, 24, 25], cephalosporins [21] such as ciprofloxacin [19] and cephalexin [19], and penicillin including amoxicillin [20] and piperacillin [21, 25]. Staphylococcus aureus was identified to be resistant to ampicillin, ciprofloxacin, penicillin, norfloxacin, cefazolin, and tetracycline [19]. Methicillin-Resistant strains of Staphylococcus aureus (MRSA) were also identified [18, 19]. Additionally, Escherichia coli was identified to be resistant to fluoroquinolones.
Antibiotic therapy was found to reduce bacterial growth on culture over time. Two out of 11 included articles explored the time-dependent reduction of bacterial growth on culture following antibiotic initiation [24, 26]. Wang et al. reported a 44.65% decrease in bacterial growth of culture samples collected 24 h after initiation of broad-spectrum antibiotics [26]. Goethem et al. further highlighted the importance of timing by examining Staphylococcus aureus growth longitudinally for 5 consecutive days [24]. This study recommended follow-up cultures between day 2 and day 4 after antibiotic initiation to detect persistent bacteraemia [24]. 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.
Seven articles were meta-analysed to estimate the proportion of positive bacterial cultures before antibiotic administration (Fig. 3). The pooled proportion was 37% (95% CI 20–56%), indicating that 37% of culture samples 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 of reported proportions, ranging from 10% as reported by Lucignano 2011 [17] to 74% as reported by Kim 2011 [18]. However, the relatively narrow confidence intervals of the individual studies suggest good precision within each study.Fig. 3Proportion of bacterial growth before antibiotic administration, based on data from seven included studies. 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
Eleven articles were meta-analysed 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 [27] to 55% as reported by Goethem 2022 [24].Fig. 4Forest plot showing the proportion of bacterial growth after antibiotic administration, based on data from 11 included articles
Participants’ age was categorized into three 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 after antibiotic initiation was 22% (95% CI 4–68%, I^2^ = 99.8%, p < 0.0001) for all age groups, 18% (95% CI 8–35%, I^2^ = 99.6%, p < 0.0001) in adults, and 16% (95% CI 8%–30%, I^2^ = 96.7%, p < 0.0001) in children (Fig. 5).Fig. 5Forest plot showing the proportion of positive bacterial culture after antibiotic administration, stratified by age category (adults, children, and all age groups), based on data from 11 included articles
We classified the included studies into two those involving patients with underlying medical conditions (such as cancer) and patients with primary clinical infections who were considered as without underlying medical conditions. The pooled proportion of bacterial positivity after antibiotic administration was 24% (95% CI 12–41%, I^2^ = 97.2%, p < 0.0001) in patients without underlying medical conditions and 10% (95% CI 6–18%, I^2^ = 979.9%, p = 0) in those with underlying medical conditions (Fig. 6).Fig. 6Forest plot showing positive bacterial growth on culture after antibiotic administration, stratified by underlying medical condition, based on data from 11 included articles
To the best of our knowledge, this is the first systematic review to comprehensively evaluate bacterial growth on culture after antibiotic administration. Evidence pooled from 11 studies (67,330 culture samples) shows that bacterial growth on culture declined from 37% before antibiotic therapy to 18% after antibiotic treatment. The predominant bacterial species isolated were Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa.
All [17–19, 21–27] except one [20] of the included articles were conducted in high-income countries, where healthcare infrastructure 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 [20] 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 uniform health information systems and culture sampling, which often requires out-of-pocket payment [28]. 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%. 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 [29]. Alternately, the low bacterial growth prior to antibiotic administration could be attributed to heterogeneity in study design and sample types. The variability in the specimen types introduced inconsistency in reported positivity rates. For example, blood cultures often yield bacterial growth compared to cerebrospinal fluid (CSF) cultures, which in meningitis cases, may exhibit pleocytosis [30]. 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, the 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 [31].
Our review did not evaluate whether antibiotic prescriptions were appropriate, or whether sub-optimal or counterfeit antibiotics were used. We observed a marked reduction in bacterial growth following antibiotic administration; however, some pathogens persist despite therapy, with a pooled estimate of 18%. This persistence could be attributed to several reasons, including sub-optimal dosing [32], use of counterfeit antibiotics [33], and timing of sample collection relative to antibiotic initiation [24, 26]. While existing guidelines for sepsis management emphasize the importance of obtaining cultures before initiating antibiotics in patients suspected for sepsis [34, 35], there are no specific recommendations on culture sampling after antibiotics’ initiation. Based on the current findings on bacterial growth post-antibiotics, we recommend that, where feasible, bacterial cultures be obtained after antibiotics have been initiated. This could aid monitoring patient’s prognosis.
Adults (aged ≥ 18 years) demonstrated higher bacterial culture positivity following antibiotic administration compared to children (aged < 18 years), with pooled proportions of 18% and 16%, respectively. This finding requires careful interpretation given the broad age categorization employed in our analysis. The human immunity system undergoes age-related changes from birth through adulthood, with children under 5 years and the elderly having less regulated immune responses [36, 37]. Using 18 years as the cut-off point in this review likely obscured the expected age-related immunological variations, which would typically be reflected in the bacterial positivity rates. Future studies should apply more detailed age sub-group analyses to better capture these host-related dynamics.
Patients without underlying medical conditions exhibited significantly higher bacterial culture positivity following antibiotic administration compared to those with comorbidities, with pooled proportions of 24% versus 10%, respectively. This finding aligns with existing evidence on immune function among patients with chronic diseases. Individuals with underlying medical conditions, such as cancer, exhibit systemic immunosuppression and receive frequent antibiotic therapy, thereby reducing bacterial proliferation and subsequent culture positivity [38].
The top three isolated bacteria in this review—Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa—are consistent with the well-documented global burden of bacterial bloodstream infections [39]. 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 [12]. The burden of Escherichia coli is reported to be particularly high among adults and among patients with urogenital infections [12] consistent with our findings. Our review identified fluoroquinolone resistance in Escherichia coli, aligning with existing literature that discusses the increased persistence of infections caused by resistant strains compared to those caused by susceptible strains [40].
The global prevalence of Staphylococcus aureus colonization in humans is estimated at 24.9%, highlighting its clinical significance [13]. 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 [19], which contrasts with a recent systematic review from Africa indicating higher resistance to second-generation penicillin [41]. Overall, the existing evidence underscores Escherichia coli and Staphylococcus aureus as the leading antimicrobial resistant pathogens associated with mortality worldwide [42].
Our findings should be interpreted in the light of the following limitations. Given that the unit of analysis was the number of samples tested, we did not account for the possibility that multiple samples may have been collected from the same patient. Although microbiological guidelines recommend multiple sampling from a single patient for quality control purposes, we did not standardize for the recommended diagnostic practice. We did not account for potential confounding factors such as antibiotic type, quality, dosage, frequency, susceptibility, or treatment adherence, all of which may have influenced culture positivity. The high heterogeneity (I^2^ > 99%) across included studies persisted even after sub-group analyses by age and comorbidity. This reflects variation in clinical populations, tissue biopsies, culture methodologies, and sampling protocols. 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. Lastly, the scarcity of data from LMICs limits the generalizability of the study findings.
Bacterial culture positivity declined after antibiotic administration, indicating a reduction in viable bacterial load. 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 reinforce the clinical value of obtaining follow-up cultures after the treatment has begun, particularly in patients who show limited or delayed clinical improvement. 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 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.