Abstract
Background
Infective endocarditis (IE) is a life-threatening condition caused by Viridans Group Streptococci (VGS) in low and middle-income countries. Data on epidemiology and molecular resistance mechanisms in the high-risk resource-limited setting of Khyber Pakhtunkhwa (KP), Pakistan, are scarce. This study aimed to determine the prevalence, risk factors, and molecular analysis of antimicrobial resistance in VGS isolated from IE patients in KP.
Methods
A cross-sectional study was done on 350 IE suspected patients admitted to tertiary care hospitals in KP. Blood cultures were performed and isolates were identified using standard microbiological methods followed by species confirmation via PCR (sodA, gtf, gyrB, and rpoB genes). Kirby–Bauer disk diffusion method was performed. Antibiotic resistance genes ermB, mefA, tetM, tetO, and pbp2x were analyzed by PCR. Statistical analyses of socio-demographic and clinical data were was performed using logistic regression.
Results
Among the 350 suspected IE patients, 62 (17.7%) were confirmed to have VGS-IE. The Streptococcus mitis group was the predominant species (41.9%) followed by S. sanguinis (19.4%), and the S. anginosus group (16.1%). Overall, 38.7% of isolates were multidrug-resistant Resistance to Penicillin (25.8%), erythromycin (40.3%) and tetracycline (32.3%) was recorded. Penicillin MIC₉₀ (4 µg/mL) reached the resistance breakpoint, suggesting penicillin monotherapy may not be adequate for empirical therapy. Gene pbp2x was detected in all β-lactam–resistant isolates, ermB in 40.3% and mefA in 48% of macrolide-resistant isolates, and tetM/tetO in 65% and 35% of tetracycline-resistant isolates, respectively. No independent risk factors reached statistical significance though elevated (non-significant) odds were observed. Limited access to dental care showed borderline significance (aOR = 2.10; 95% CI: 1.01–4.38; p = 0.05), whereas other variables such as prosthetic heart valves 9(aOR = 2.05, 95% CI: 0.74–5.67) and prior antibiotic use aOR = 1.35, 95% CI: 0.64–2.86) had elevated point estimates but did not remain significant after adjustment.
Conclusion
This is the first molecular epidemiological study from KP that demonstrates the high prevalence of VGS-IE with considerable multidrug resistance confirmed for genetic determinants. These findings emphasized the urgent need for improved antimicrobial stewardship, access to better dental care, and the integration of region-specific risk factors into preventive strategies to mitigate the burden of IE in regions with low-income settings.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12866-025-04648-3.
Keywords: Infective endocarditis, Viridans group streptococci, Antimicrobial resistance, Resistance genes, Risk factors, Khyber pakhtunkhwa, Low- and Middle-Income countries (LMICs)
Introduction
Infective endocarditis (IE) is a severe bacterial infection of the endocardial surface of the heart, notably the valves, and is associated with high rates of morbidity and mortality worldwide, specially in developing countries [1]. Among different pathogens responsible for IE, the Viridans Group Streptococci (VGS) are well-known pathogens [2]. The prevalence is high in individuals with predisposing conditions like rheumatic heart disease (RHD), prosthetic cardiac valves, or congenital structural heart defects, infection often originating from the oral cavity following bacteremia [3].
The epidemiology of IE has evolved, notably influenced by changes in healthcare practices, the increasing use of invasive practices, and irrational use of antibiotics [4]. In high-income countries, Staphylococcus aureus is the predominant cause [5]. In contrast, VGS remains a primary cause of IE in low and middle-income countries (LMICs), the trend largely linked to the persistent high prevalence of RHD and poor oral healthcare [6, 7]. Studies from Pakistan have documented this with one five-year experience at a tertiary care hospital in Karachi Pakistan, identifying streptococci, including VGS, as a major cause of community-acquired IE [8], and another study from Buner, Khyber Pakhtunkhwa (KP), Pakistan reported a significant proportion of culture-positive IE cases attributable to these bacteria [9].
Pakistan and the province of KP, especially, present a unique and high-risk setting for VGS-associated IE. This region has reported a high burden of RHD in children This region has reported a high burden of rheumatic heart disease (RHD) across age groups, with particularly high prevalence noted in pediatric populations [7], as well as persistent RHD-related morbidity in adults [8], compounded by widespread use of smokeless tobacco products like naswar (a local smokeless tobacco product for the mouth), limited access to dental care [10], and unregulated antibiotic use [11]. Despite this high-risk environment, there is a lack of comprehensive data on the prevalence, risk factors, and molecular mechanisms of antimicrobial resistance in VGS isolates from IE patients in KP.
Globally, resistance in VGS is mediated by well-characterized genes, including ermB and mefA (conferring macrolide resistance) [12], tetM and tetO (mediating tetracycline resistance) [13], and alterations in pbp2x (reducing susceptibility to beta-lactams) [14]. However, most of the previous studies from this region reported only phenotypic characterization of antibiotic resistance, and the prevalence of these resistance determinants in the Pakistani population remains unreported [9].
To our knowledge, this is the first study from KP to employ a combined culture-molecular approach to specifically investigate VGS-IE, its resistance determinants, and associated genetic profiles. This critical knowledge gap hinders the development of effective, region-specific preventive and therapeutic strategies.
Methodology
Ethical approval
The study was designed as a PhD research project of the first author and was reviewed and approved by the Ethical and Research Committee of Kohat University of Science and Technology (KUST), Kohat, Pakistan, under reference number (No. KUST/Ethical Committee/1975, dated December 02, 2024, supplementary file S1). In addition to this, formal administrative permission was also obtained from the participating hospitals. Written informed consent was obtained from all participants before enrollment in the study. Confidentiality of the patient’s data was maintained throughout the research.
Study area and study design
This hospital-based cross-sectional study with prospective enrollment was conducted was conducted from December 2024 to September 2025 in Khyber Pakhtunkhwa (KP), Pakistan, a province with an estimated population of over 35 million comprising both urban and rural populations with limited access to healthcare. The research target was patients who were admitted and suspected of infective endocarditis to the cardiology units and cardiac surgery wards of major tertiary care and teaching hospitals across KP. Participating centers included the Lady Reading Hospital (LRH), Hayatabad Medical Complex (HMC), and Khyber Teaching Hospital (KTH), Peshawar, the three largest government tertiary hospitals with dedicated cardiology and cardiac surgery departments. Additional patient recruitment was carried out at cardiology wards at district-level hospitals of Kohat, Hangu, Bannu, Dera Ismail Khan (DI Khan) Districts, and the Peshawar Institute of Cardiology (PIC), a specialized cardiac care and interventional cardiology center serving as a provincial referral institute. These hospitals receive patients from all districts of KP and neighboring tribal regions, providing a representative cross-section of the province’s cardiac patient population. The inclusion of both general tertiary hospitals, district-level hospitals, and a specialized cardiology institute enhanced the reliability and diversity of the data, thus reflecting real patterns of infective endocarditis management in the region. The geographical distribution of the sampling districts and participating hospitals included in this study across Khyber Pakhtunkhwa, Pakistan, is illustrated in Fig. 1.
Fig. 1.
Geographical representation of sampling areas and hospitals in Khyber Pakhtunkhwa, Pakistan. The map illustrates the districts from which samples were collected for this study. Sampling districts are highlighted in red, including Peshawar, Kohat, Hangu, Bannu, and Dera Ismail Khan. Major hospitals where specimens were obtained are indicated: Khyber Teaching Hospital (KTH), Lady Reading Hospital (LRH), and Hayatabad Medical Complex (HMC) in Peshawar
Inclusion and exclusion criteria
The sample size was calculated using Cochran’s formula or the World Health Organization (Lwanga & Lemeshow, 1991) method:
 |
where Z = 1.96 (95% confidence level), p = 0.20 (estimated prevalence based on prior regional data), and d = 0.05 (precision). This yielded a minimum sample size of 246 patients. To compensate for potential non-response, incomplete data, and culture-negative cases common in IE cohorts due to prior antibiotic exposure, we increased the target enrollment by an additional 30–35%, resulting in a final sample size of 350 suspected IE patients. This expanded sample ensured adequate statistical power for prevalence estimation and multivariable regression analyses.
The patients were included if they were adults (≥ 18 years) presenting with clinical features meeting the criteria for possible or definite IE according to the modified Duke criteria [15].
The exclusion criteria included patients who had received systemic antibiotic therapy for more than 48 h before blood culture collection, those with a confirmed alternative diagnosis explaining their symptoms, and cases with polymicrobial bacteremia or pregnancy. Patients presenting with non-infective cardiac conditions including ischemic heart disease, rheumatic valvular disease without active infection, cardiomyopathy, congenital heart defects, or other forms of non-infective endocarditis were also excluded. Additionally, individuals with antibiotic exposure within the preceding three months were noted separately for risk factor analysis but were excluded when such exposure interfered with accurate diagnostic evaluation for VGS-associated infective endocarditis. These criteria ensured the inclusion of only those patients with a clear and uncompromised clinical suspicion of infective endocarditis.
Data collection
Socio-demographic and clinical information were obtained from all enrolled patients using a pre-tested, self-structured questionnaire (Supplementary file S2) and review of available medical records. The data included age, gender, area of residence (urban/rural), socio-economic status, and medical history relevant to infective endocarditis. Clinical parameters included history of rheumatic heart disease (RHD), presence of a prosthetic cardiac valve, oral hygiene status, recent antibiotic exposure within the preceding three months, intravenous drug use (IVDU), and nutritional status assessed by Body Mass Index (BMI). Data was collected by the PhD scholar through patient interviews, clinical examination, and chart reviews, assisted by a trained nurse or cardiologist to ensure accuracy and uniformity across participating centers.
Sample collection and bacterial identification
Under aseptic conditions, 5–10 mL of venous blood was collected from each patient and inoculated into BACTEC aerobic blood culture bottles. The Isolates were identified based on colony morphology, hemolysis patterns, Gram staining, and catalase reaction. Presumptive VGS isolates were confirmed via PCR targeting the sodA, gyrB, gtf, and rpoB genes [16].
Antimicrobial susceptibility testing
Antibiotic susceptibility testing was performed for antibiotics including Penicillin G (Pen); Amoxicillin (AMX); Ceftriaxone (CRO); Erythromycin (ERY); Clindamycin (CLI); Tetracycline (TET), Doxycycline (DOX); Azithromycin (AZM); Vancomycin (VAN); Linezolid (LZN) using the Kirby–Bauer disk diffusion method on Mueller-Hinton agar supplemented with 5% sheep blood, followed by determination of Minimum Inhibitory Concentrations (MICs) using E-test strips as per guidelines of Clinical and Laboratory Standards Institute guidelines. Multidrug resistance (MDR) was defined as non-susceptibility to ≥ 3 antimicrobial classes as per CLSI criteria (CLSI M100, 2024) [17].
Molecular identification of isolates
Genomic DNA was extracted from overnight fresh cultures of presumptive viridans group streptococci (VGS) using a commercial bacterial DNA extraction kit (Thermo Fisher Scientific, USA). Species identification was performed by amplification of sodA, rpoB, gtf and gyrB gene fragments using previously published primers [18–20] including the foundational approach described by Hoshino et al. (2005) [16], which supports the molecular differentiation of nonhemolytic streptococci. Each 25 µL reaction contained 12.5 µL of 2× PCR Master Mix (Thermo Fisher Scientific), 10 pmol of each primer (Table 1), 2 µL of DNA template, and nuclease-free water. PCR products were resolved by electrophoresis on 1.5% agarose gels stained with ethidium bromide and visualized under UV transillumination. Primer sequences and optimized PCR conditions are summarized in Supplementary file S3.
Table 1.
Diagnostic yield of culture and PCR for viridans group Streptococci (n = 350)
| Method | Positive cases (n) | Percentage (%) |
|---|---|---|
| Blood culture | 58 | 16.6 |
| PCR (sodA, gtf, gyrB, rpoB) | 55 | 15.7 |
| Combined detection (culture + PCR)* | 62 | 17.7 |
*Combined detection refers to cases positive by either culture or PCR
Detection of resistance genes
In the second part of the experiment, detection of antimicrobial resistance determinants targeted to ermB and mefA (macrolide resistance), tetM and tetO (tetracycline resistance), and pbp2x (β-lactam resistance) genes using already used primer sets [21–23]. PCR composition and cycling parameters were identical except for annealing temperatures (45–58 °C) optimized per primer pair (Supplementary file S3). Amplicons were analyzed on 1.5% agarose gels alongside a 100 bp molecular size markers.
Statistical analysis
Data was analyzed using SPSS Statistics (version 26.0). Descriptive statistics were presented as frequencies and percentages for the variables recorded. Patients with clinically suspected IE (culture and PCR-negative for VGS) were analyzed using the Chi-square test or Fisher’s exact test, where applicable. Variables with a p-value < 0.2 in univariate analysis were further used in a multivariate logistic regression model to identify independent predictors that were presented as adjusted odds ratios (aOR) with 95% confidence intervals (CI). A p-value of < 0.05 was considered statistically significant. The control group for the risk factor analysis was defined as patients with clinically suspected IE who were negative for VGS by both culture and PCR (n = 288). The control group consisted of patients who met the clinical criteria for suspected infective endocarditis but were negative for VGS by both blood culture and PCR. These controls were not required to be negative for all pathogens; rather, they were included regardless of whether another microorganism was identified, as long as VGS was not detected by either diagnostic method.
Results
Prevalence and diagnostic confirmation
Out of 350 clinically suspected IE patients, 62 (17.7%) were confirmed to have VGS-IE based on culture and/or PCR results and constituted the final study cohort for all subsequent analyses (Table 1). Hospital-wise distribution of viridans group streptocci positive cases are shown in supplementary file S4.
Species distribution
Among the 62 confirmed VGS isolates, the Streptococcus mitis group was the most prevalent, accounting for 41.9% (n = 26) of cases, followed by S. sanguinis (19.4%, n = 12), and the S. anginosus group (16.1%, n = 10). Other species identified included S. salivarius (9.7%, n = 6), S. mutans (8.1%, n = 5), and S. oralis (4.8%, n = 3) (Table 2).
Table 2.
Species distribution of viridans-group Streptococci (VGS) isolated from IE patients (n = 62)
| Species identified* | Frequency (n) | Percentage (%) |
|---|---|---|
| Streptococcus mitis group | 26 | 41.9% |
| Streptococcus sanguinis | 12 | 19.4% |
| Streptococcus anginosus group | 10 | 16.1% |
| Streptococcus salivarius | 6 | 9.7% |
| Streptococcus mutans | 5 | 8.1% |
| Streptococcus oralis | 3 | 4.8% |
| Total | 62 | 100% |
*Species assignments were based on molecular identification using discriminatory loci (gyrB, rpoB, sodA, gtf). These markers provide validated differentiation among mitis-group species; therefore, S. oralis was reported separately rather than merged into the S. mitis group
Antimicrobial susceptibility and resistance genetics
The overall resistance profile of the 62 isolates showed high rates of resistance to different classes of antibiotics. Resistance to penicillin was observed in 16 isolates (25.8%), with corresponding resistance rates of 24.2% to amoxicillin and 19.4% to ceftriaxone. High resistance was also observed to macrolides (erythromycin 40.3%, azithromycin 27.4%) and tetracyclines (tetracycline 32.3%, doxycycline 25.8%). All isolates remained fully susceptible to vancomycin and linezolid. The results of antibiotic resistance profiles is shown in Table 3.
Table 3.
Antibiotic resistance of viridans group Streptococci stratified by species (n = 62)
| Species (n) | PEN R n (%) | AMX R n (%) | CRO R n (%) | ERY R n (%) | AZM R n (%) | CLI R n (%) | TET R n (%) | DOX R n (%) | VAN R n (%) |
LZD R n (%) | MDR n (%) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| S. mitis group (26) |
9 (34.6) |
8 (30.8) |
6 (23.1) |
13 (50.0) | 9 (34.6) | 6 (23.1) |
9 (34.6) |
7 (26.9) |
0 (0.0) |
0 (0.0) |
11 (42.3) |
|
S. sanguinis (12) |
2 (16.7) |
2 (16.7) |
2 (16.7) |
5 (41.7) |
4 (33.3) | 2 (16.7) |
4 (33.3) |
3 (25.0) |
0 (0.0) |
0 (0.0) |
5 (41.7) |
| S. anginosus group (10) |
3 (30.0) |
3 (30.0) |
2 (20.0) |
4 (40.0) |
2 (20.0) | 2 (20.0) |
3 (30.0) |
2 (20.0) |
0 (0.0) |
0 (0.0) |
4 (40.0) |
|
S. salivarius (6) |
1 (16.7) |
1 (16.7) |
1 (16.7) |
2 (33.3) |
1 (16.7) | 1 (16.7) |
2 (33.3) |
1 (16.7) |
0 (0.0) |
0 (0.0) |
2 (33.3) |
|
S. mutans (5) |
1 (20.0) |
1 (20.0) |
1 (20.0) |
1 (20.0) |
1 (20.0) | 1 (20.0) |
1 (20.0) |
1 (20.0) |
0 (0.0) |
0 (0.0) |
1 (20.0) |
|
S. oralis (3) |
0 (0.0) |
0 (0.0) |
0 (0.0) |
0 (0.0) |
0 (0.0) |
1 (33.3) |
1 (33.3) |
1 (33.3) |
0 (0.0) |
0 (0.0) |
1 (33.3) |
|
Total (62) |
16 (25.8) |
15 (24.2) |
12 (19.4) |
25 (40.3) | 17 (27.4) | 13 (21.0) |
20 (32.3) |
15 (24.2) |
0 (0.0) |
0 (0.0) |
24 (38.7) |
PEN PenicillinG, AMX Amoxicillin, CRO Ceftriaxone, ERY Erythromycin, AZM Azithromycin, CLI Clindamycin, TET Tetracycline, DOX Doxycycline, VAN Vancomycin, LZD Linezolid, MDR Multi Drug Resistant
As detailed in Table 3, Fig. 2, the Streptococcus mitis group, being the most prevalent (n = 26), showed the highest absolute number of resistant isolates and significant resistance rates across all drug classes. It showed significant resistance to beta-lactams (penicillin 34.6%, ceftriaxone 23.1%), macrolides (erythromycin 50.0%), and tetracyclines (tetracycline 34.6%). The S. sanguinis group (n = 12) and the S. anginosus group (n = 10) also showed considerable resistance to these drug classes. All isolates, regardless of species, remained fully susceptible to vancomycin and linezolid. The interspecies variability in antimicrobial resistance patterns is visually illustrated in Fig. 2A and B, which corroborates the species-stratified resistance rates presented in Table 3.
Fig. 2.
Antibiotic resistance patterns among Viridans Group Streptococci (VGS) isolated from infective endocarditis patients. A Species-specific resistance distribution for major VGS groups, including S. mitis, S. sanguinis, S. anginosus, S. salivarius, S. mutans, and S. oralis, illustrating interspecies variability in resistance to key antibiotic classes. B Overall prevalence (%) of resistance to β-lactams (penicillin, amoxicillin, ceftriaxone), macrolides (erythromycin, azithromycin), lincosamides (clindamycin), and tetracycline-class agents (tetracycline, doxycycline) among all VGS isolates (n = 62). Abbreviation: PEN = PenicillinG, AMX = Amoxicillin, CRO = Ceftriaxone, ERY = Erythromycin, AZM = Azithromycin, CLI = Clindamycin, TET = Tetracycline, DOX = Doxycycline, VAN = Vancomycin, LZD = Linezolid, MDR = Multi Drug Resistant
Molecular detection of antibiotic resistance genes
Molecular analysis of the 62 isolates was performed. PCR amplification of housekeeping and resistance-associated genes was successfully achieved in the isolates included in this study. Clear and specific amplicons were obtained for the housekeeping genes rpoB (~ 700 bp), gyrB (~ 1100 bp), and gtf (~ 517 bp). Likewise, resistance genes were reliably amplified, yielding expected product sizes for mefA (~ 350 bp), ermB (~ 648 bp), tetM (~ 406 bp), tetO (~ 171 bp), and pbp2x (~ 2.1 kb). The amplified products demonstrated sharp, distinct bands upon agarose gel electrophoresis, confirming the presence of the respective genetic determinants. Representative gel images for all amplified genes are provided in Supplementary file S4. Table 4 summarizes the overall antibiotic resistance profile of the VGS isolates and the corresponding resistance genes detected. A high level of resistance was observed to macrolides and tetracyclines, with erythromycin resistance reaching 40.3% and tetracycline resistance 32.3%. Penicillin non-susceptibility was documented in 25.8% of isolates, all of which carried the pbp2x gene.
Table 4.
Antibiotic resistance profile of viridans group Streptococci isolates (n = 62) and correlation with resistance genes
| Antibiotic | Resistant isolates | MIC range of resistant isolates (µg/mL) | Key resistance genes detected |
|---|---|---|---|
| Penicillin G | 16 (25.8%) | 0.5–8.0 | pbp2x (16, 100%) |
| Amoxicillin | 15 (24.2%) | 0.5–4.0 | pbp2x (15, 100%) |
| Ceftriaxone | 12 (19.4%) | 0.5–4.0 | pbp2x (10, 83.3%) + other mechanisms |
| Erythromycin | 25 (40.3%) | 1–8 | ermB (20, 80.0%), mefA (12, 48.0%) |
| Azithromycin | 17 (27.4%) | 1–4 | ermB (12, 70.6%), mefA (9, 52.9%) |
| Clindamycin | 13 (21.0%) | 0.5–2.0 | ermB (10, 76.9%) |
| Tetracycline | 20 (32.3%) | 2–16 | tetM (13, 65.0%), tetO (7, 35.0%) |
| Doxycycline | 16 (25.8%) | 1–8 | tetM (11, 68.8%), tetO (5, 31.3%) |
| Vancomycin | 0 (0.0%) | ≤ 0.5 | None detected |
| Linezolid | 0 (0.0%) | ≤ 1.0 | None detected |
| Multidrug resistance* | 24 (38.7%) | --- | Combinations of ermB, mefA, tetM, tetO, pbp2x |
*Multidrug resistance (MDR) was defined as non-susceptibility to ≥ 3 antimicrobial classes as per CLSI criteria
Minimum inhibitory concentration (MIC) distribution
MIC testing was done to confirm concerning resistance trends. The MIC₉₀ values for penicillin and ceftriaxone were recorded as 4.0 µg/mL and 2.0 µg/mL respectively indicating that a significant subset of the population had MICs at or approaching near the CLSI resistance breakpoints. This confirms a significant level of reduced susceptibility to beta-lactams. In contrast, elevated MIC₉₀ values were observed for erythromycin (8.0 µg/mL), tetracycline (16.0 µg/mL), and doxycycline (8.0 µg/mL) thus confirming the high-level resistance evident in the disk diffusion assay. All MICs for vancomycin and linezolid were within the susceptible range (Table 5).
Table 5.
Minimum inhibitory concentrations (MICs) of viridans group Streptococci isolates (n = 62)
| Antibiotic | MIC range (µg/mL) | MIC 50 (µg/mL) | MIC 90 (µg/mL) | CLSI 2024 resistance breakpoint (µg/mL) |
|---|---|---|---|---|
| Penicillin G | 0.03–8.0 | 0.12 | 4.0 | ≥ 4.0 |
| Amoxicillin | 0.03–4.0 | 0.12 | 2.0 | ≥ 2.0 |
| Ceftriaxone | 0.06–4.0 | 0.25 | 2.0 | ≥ 4.0 |
| Erythromycin | 0.06–16.0 | 0.5 | 8.0 | ≥ 1.0 |
| Azithromycin | 0.06–8.0 | 0.5 | 4.0 | ≥ 2.0 |
| Clindamycin | 0.03–4.0 | 0.25 | 2.0 | ≥ 1.0 |
| Tetracycline | 0.12–32.0 | 2.0 | 16.0 | ≥ 8.0 |
| Doxycycline | 0.06–16.0 | 1.0 | 8.0 | ≥ 4.0 |
| Vancomycin | 0.25–1.0 | 0.5 | 0.5 | ≥ 2.0 |
| Linezolid | 0.12–1.0 | 0.5 | 1.0 | ≥ 4.0 |
Demographic and clinical characteristics of the IE patients
The present study cohort consisted of 350 patients with a clinical suspicion of infective endocarditis. The mean age of the participants was 42.7 years, with the largest proportion (42.6%, n = 149) included within the 31–50 years age group. A male predominance was observed, accounting for 62.0% (n = 218) of the cohort. Most patients were urban residents (58.0%, n = 203). Significant clinical risk factors included a history of rheumatic heart disease (RHD) in 30.0% (n = 105) of patients and intravenous drug use (IVDU) in 10.0% (n = 35). Contextual risk factors were highly prevalent that as most patients were of low socioeconomic status (52.0%, n = 182) reported limited access to dental care (60.0%, n = 210), and used local tobacco or naswar (46.6%, n = 163). Additionally, 21.4% (n = 75) of the patients were underweight, indicating a notable prevalence of malnutrition within the cohort (Table 6).
Table 6.
Demographic and clinical characteristics of infective endocarditis patients (n = 350)
| Variable | Category | Frequency (n) | Percentage (%) |
|---|---|---|---|
| Age group | 18–30 years | 89 | 25.4 |
| 31–50 years | 149 | 42.6 | |
| 51–70 years | 84 | 24.0 | |
| > 70 years | 28 | 8.0 | |
| Gender | Male | 218 | 62.0 |
| Female | 134 | 38.0 | |
| Residence | Urban | 203 | 58.0 |
| Rural | 147 | 42.0 | |
| Rheumatic heart disease | Yes | 105 | 30.0 |
| No | 245 | 70.0 | |
| IV drug use | Yes | 35 | 10.0 |
| No | 315 | 90.0 | |
| Socioeconomic status | Low | 182 | 52.0 |
| Middle/High | 168 | 48.0 | |
| Access to dental care | Limited | 210 | 60.0 |
| Adequate | 140 | 40.0 | |
| Tobacco/naswar chewing | Yes | 163 | 46.6 |
| No | 187 | 53.4 | |
| Nutritional status (BMI) | Underweight | 75 | 21.4 |
| Normal/High | 275 | 78.6 |
Risk factor analysis
Analysis by univariate logistic regression of the 350 patient cohort (62 cases versus 288 controls) showed several factors with significantly elevated crude odds ratios for VGS-IE. These included prosthetic heart valves implantation (OR = 2.56, 95% CI: 1.12–5.85, p = 0.03), IVDU (OR = 2.33, 95% CI: 1.08–5.03, p = 0.03) low socioeconomic status (OR = 1.85, 95% CI: 1.08–3.18, p = 0.03) and limited access to dental care (OR = 2.12, 95% CI: 1.21–3.72, p = 0.01). However, upon multivariate adjustment, none of these factors retained formal statistical significance as an independent predictor. Despite this, prosthetic valve implantation (aOR = 2.05, 95% CI: 0.74–5.67) and prior antibiotic use (aOR = 1.35, 95% CI: 0.64–2.86) continued to demonstrate high, though limited access to dental care was marginally significant (aOR = 2.10, 95% CI: 1.01–4.38, p = 0.05) (Table 7).
Table 7.
Univariate and multivariate logistic regression of risk factors for viridans group Streptococci infective endocarditis (n = 62 cases vs. 288 controls)
| Predictor | Crude OR (95% CI) | p-value | Adjusted OR (95% CI) | p-value |
|---|---|---|---|---|
| Poor oral hygiene | 0.87 (0.38–1.98) | 0.74 | 0.92 (0.44–1.90) | 0.81 |
| Rheumatic heart disease | 0.98 (0.42–2.29) | 0.97 | 0.75 (0.36–1.56) | 0.45 |
| Prosthetic valve | 2.56 (1.12–5.85) | 0.03 | 2.05 (0.74–5.67) | 0.15 |
| Prior antibiotic use* | 1.01 (0.43–2.36) | 0.99 | 1.35 (0.64–2.86) | 0.43 |
| Urban residence | 1.05 (0.61–1.82) | 0.86 | 0.69 (0.35–1.35) | 0.28 |
| Male sex | 1.02 (0.59–1.76) | 0.95 | 1.20 (0.61–2.34) | 0.58 |
| IV drug use | 2.33 (1.08–5.03) | 0.03 | 1.95 (0.63–6.00) | 0.25 |
| Low socioeconomic status | 1.85 (1.08–3.18) | 0.03 | 1.95 (0.98–3.89) | 0.06 |
| Limited access to dental care | 2.12 (1.21–3.72) | 0.01 | 2.10 (1.01–4.38) | 0.05 |
| Tobacco/naswar chewing | 1.54 (0.90–2.63) | 0.11 | 1.65 (0.82–3.32) | 0.12 |
| Malnutrition (low BMI) | 1.37 (0.76–2.47) | 0.30 | 1.40 (0.66–2.95) | 0.35 |
Variables with p<0.2 in univariate analysis entered into the multivariate logistic regression model. Controls were defined as VGS culture / PCR-negative patients
*Prior antibiotic use’ was defined as any antibiotic consumption within the three months preceding admission, excluding the 48-hour period before blood culture
Discussion
This study represents the first molecular epidemiological analysis of Viridans Group Streptococci infective endocarditis (IE) from the Khyber Pakhtunkhwa (KP) region of Pakistan. While previous reports from this province have reported the bacteriological profile of IE that were largely based on phenotypic methods and did not focus specifically on the molecular characterization of VGS [9]. Our data integrates the culture, PCR based species confirmation and resistance gene detection confirmed an overall VGS-IE prevalence of 17.7% and establishes this bacterial group as a significant etiological agent in the local population suffering from IE. This finding aligns with national data from other provinces indicate that the streptococci are responsible for a considerable proportion of IE cases in Pakistan, particularly among individuals with predisposing conditions like RHD and improper dental hygiene [8, 9]. In contrast to the epidemiological shift towards Staphylococcus aureus in high-income countries [24]. The enduring predominance of VGS in this low-income setting emphasizes the persistent influence of regional risk factors pervasive in LMICs, including a high RHD burden, limited access to oral healthcare, and unregulated antibiotic use [25–27].
The species distribution in our cohort was dominated by the S. mitis group (41.9%) and S. sanguinis(19.4%) and the finding is consistent with regional and global profiles. A study from Quetta, in Pakistan’s Balochistan province, also reported a high prevalence of oral streptococci, including S. mutans (25.6%) and S. mitis (19.4%) in dental caries [28]. Similarly, research from South India has identified the S. mitis group as a predominant cause of VGS bacteremia [29]. As commensals of the oropharyngeal region, these species are well-recognized pathogens in subacute IE [30]. The high prevalence of the S. mitis group reinforces its emerging role as a leading cause of VGS-IE, a trend supported by studies highlighting its significant virulence potential in community-acquired infections [31, 32]. The notable detection of the S. anginosus group (16.1%) is also significant, as this group is frequently associated with abscess formation and may indicate a more invasive disease phenotype [33].
This study provides the first genetic confirmation of beta-lactam resistance mechanisms in VGS from KP, highlighting a concerning trend of rising resistance. The antibiotic sensitivity profile recorded in this study presents an alarming picture that aligns with the rising trends observed across South Asia. A key finding of our study is the reporting of a high prevalence of penicillin reistance (25.8%), which we confirmed with the detection of the pbp2x gene in samples. This finding is in consistence with the 32.14% reported in a recent study from Lahore, Pakistan [34] and falls within the 20–65% range documented in other Pakistani reports [35, 36]. It is also in accordance with high rates of 34–60% reported from neighboring India and China [37, 38], although it is higher than the 15.4% reported from Jordan [39]. This data highlights that penicillin resistance in VGS is a severe and widespread problem in the region likely propelled by decades of unregulated and irrational antibiotic use. The clinical relevance of this finding is confirmed by the elevated MIC₉₀ value for penicillin (4.0 µg/mL), approaching the CLSI resistance breakpoint and given the high prevalence of penicillin non-susceptibility, empirical monotherapy with penicillin may be inadequate. Therefore, combined therapy should be considered.
Conversely, we recorded higher levels of resistance to macrolides (erythromycin 40.3%) and tetracyclines (tetracycline 32.3%) with 38.7% of isolates classified as multidrug resistant (MDR). To our knowledge, this is the first report from KP to document the genetic determinants of this MDR phenotypes in viridans streptococci revealing high carriage of ermB (40.3%) and tetM (32.3%) genes. These rates substantially exceed the 18.5% macrolide resistance reported from Karachi [9]. It is important to note that some international comparisons such as Finnish data showing 22.4% erythromycin and 27.3% tetracycline resistance are based on carriage isolates, which typically show lower resistance than invasive or IE-associated strains [34, 35]. While not directly comparable, these figures highlight the markedly higher resistance burden in our clinical isolates, likely driven by unregulated antibiotic use and weaker stewardship practices in the region. The elevated MIC₉₀ values for erythromycin (8.0 µg/mL) and tetracycline (16.0 µg/mL) in our study confirmed the presence of a high level clinically relevant resistance likely to be driven by widespread use of non prescription antibiotic in the community and agricultural sectors across South Asia [40].
Molecular analysis provided a genetic confirmation of phenotypic characterization of antibiotic resistance. The pbp2x gene was detected in all penicillin-resistant isolates, confirming the role of altered penicillin-binding proteins. Furthermore the high co-occurance and co-carriage of macrolide (ermB, mefA) and tetracycline (tetM, tetO) resistance genes facilitates the observed MDR phenotype. The prevalence of ermB (40.3%) and tetM (32.3%) in our isolates is markedly higher than rates reported in a Tunisian pediatric population (12.84% for ermB and 9.17% for tetM), though tetO was more common there (27.52%) [41]. The observed differences in resistance gene prevalence compared to Tunisian pediatric data may be partly attributable to the age-group variation between the study populations. The tetM and tetO genes confer tetracycline resistance through ribosomal protection [42]. Similar resistance genetics have been reported elsewhere, a study from Turkey found ermB in 56% and pbp2x in 20% of resistant VGS isolates [12, 43]. While the current clinical impact of pbp2x may be limited, its presence is a critical warning that necessitates ongoing surveillance for rising beta-lactam resistance. The 100% susceptibility to vancomycin and linezolid confirms that these agents as reliable last line options for treatment of severe or MDR cases. However, their high cost and limited availability in Pakistan’s public health sector render them inaccessible for patients from remote areas, highlights the urgent need to revise local empirical treatment guidelines and implement stringent antibiotic stewardship programs.
Although several factors such as prosthetic heart valves, IVDU, and low socioeconomic status showed strong epidemiological signals in unadjusted analyses, none remained statistically significant after multivariate adjustment. This indicates that the apparent associations may be influenced by confounding or limited statistical power. The only factor approaching significance was limited access to dental care (p = 0.05), suggesting a potential but not definitive relationship. Prosthetic heart valve implantation was linked to a two-fold increased risk (aOR = 2.05) which is in accordance with a study from Karachi, Pakistan that identified prosthetic valve endocarditis as a complex entity with higher morbidity and mortality (OR = 3.74) [44]. The trend observed with IVDU (aOR = 1.95), although less common in our cohort remains a biologically possible risk factor due to the potential for direct inoculation of oral flora in blood stream as supported by previous literature [45].
The high prevalence of region specific risk factors in our cohort, including limited dental care access (60%), low socioeconomic status (52%), and particularly the use of naswar (46.6%), likely plays a critical role in facilitating oral colonization and subsequent bacteremia. Poor oral health is a well-established risk factor for transient streptococcal bacteremia, especially in individuals with underlying valvular damage [46]. The common practice of naswar chewing a smokeless tobacco product is of particular concern in KP. Its use causes chronic mucosal irritation and damage to the oral mucosa thus disrupting the normal microflora and creating portals of entry for bacteria into the bloodstream and thereby predisposing users to infections [47, 48]. The persistently elevated, though non-significant, odds ratios for these factors in our multivariate model highlight their potential contributory role and warrant further investigation in larger, prospective studies.
Limitations
This study has various limitations. Its cross-sectional design impedes causal interpretation between risk factors and outcome. Although PCR was used for gene detection, the absence of whole-genome or Sanger sequencing, which couldn’t be performed due to the resource constraints of this PhD research project that limited our ability to explore novel mutations, perform detailed phylogenetic analysis or identify undiscovered resistance mechanisms. The recruitment of participants from tertiary care centers may introduce selection bias, potentially underrepresenting community-acquired cases or those managed in rural settings. Furthermore, despite the use of combined culture and PCR diagnostics and exclusion of participants who received prior antibiotic therapy, the true burden of IE may be miscalculated due to culture-negative cases, often resulting from antecedent antibiotic therapy. Additionally, the sample size, while adequate for prevalence estimates, may have been underpowered for robust multivariate risk factor analysis. The control group included both non-VGS IE cases and patients without confirmed IE, which may limit the specificity of risk factor associations for VGS-IE.
Conclusion
In conclusion, this study offers the first comprehensive evidence from Khyber Pakhtunkhwa, Pakistan on the molecular epidemiology of VGS-IE. We report a significant disease burden characterized by considerable multidrug resistance, the genetic basis of which including the prevalence of ermB, mefA, tetM, tetO, and pbp2x genes is reported for the first time in clinical VGS isolates from this region. Because the penicillin MIC₉₀ reached the CLSI resistance breakpoint, penicillin monotherapy may be inadequate for empirical management of VGS-IE in KP. The endemicity of VGS-IE in KP appears to be driven by regional factors, including inadequate dental care, a high burden of RHD, unregulated antibiotic use, and the common practice of naswar chewing. These findings emphasize at the urgent need for region-specific interventions including vigorous antibiotic stewardship programs, enhanced oral health infrastructure, and the development of context aware clinical guidelines to minimize AMR. Future research should be employ for genomic surveillance to fully explore the resistance profiles and transmission dynamics of these bacteria and to evaluate the impact of public health steps aimed at mitigating these unique, region-specific risk factors. We recommend the integration of routine molecular surveillance of resistance genes in VGS into regional antimicrobial stewardship programs.
Supplementary Information
Acknowledgements
authors extend their sincere appreciation to Taif University, Saudi Arabia, for supporting this work through project number (DSPP-2024-05). The authors are also profoundly grateful to the doctors, nurses, and laboratory staff at the participating hospitals Lady Reading Hospital (LRH), Hayatabad Medical Complex (HMC), Khyber Teaching Hospital (KTH), Peshawar Institute of Cardiology (PIC), and the district headquarters hospitals in Kohat, Hangu, Bannu, and Dera Ismail Khan for their invaluable assistance in patient recruitment and sample collection. Finally, we sincerely thank all the patients who participated in this study.
Authors’ contributions
Conceptualization, A.K. and M.H.; methodology, A.K., S.K., and M.H.; software, A.K. and H.N.; validation, N.M., A.B., and K.J.A.; formal analysis, A.K. and K.F.A.; investigation, A.K., S.K., and H.N.; resources, M.H., S.K., and F.M.A.; data curation, A.K. and A.B.; writing and original draft preparation, A.K.; writing, review and editing, M.H., S.K., K.J.A., and F.M.A.; visualization, A.K. and K.F.A.; supervision, M.H. and S.K.; project administration, M.H.; funding acquisition, K.J.A. and F.M.A.
Funding
This research was funded by Taif University, Taif, Saudi Arabia, grant number (TU-DSPP-2024-05).
Data availability
The data presented in this study is available on request from the corresponding author. The data is not publicly available due to privacy and ethical restrictions.
Declarations
Ethics approval and consent to participate
The study was approved by the Ethical and Research Committee of Kohat University of Science and Technology (KUST), Kohat, Pakistan (Approval No. KUST/Ethical Committee/1975, dated 02 December 2024). All procedures involving human participants were performed in accordance with the ethical standards of the institutional committee and with the Declaration of Helsinki. Written informed consent was obtained from all individual participants (or their legal guardians, where applicable) prior to sample collection.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Saadullah Khan, Email: saadkhanwazir@gmail.com.
Mubbashir Hussain, Email: mubbashir.hussain@kust.edu.pk.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data presented in this study is available on request from the corresponding author. The data is not publicly available due to privacy and ethical restrictions.