Clinical and Inflammatory Predictors of Treatment Failure in Uncomplicated Skin and Soft Tissue Infections: A Multicenter Study From Türkiye

Clinical and Inflammatory Predictors of Treatment Failure in Uncomplicated Skin and Soft Tissue Infections: A Multicenter Study From Türkiye | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical and Inflammatory Predictors of Treatment Failure in Uncomplicated Skin and Soft Tissue Infections: A Multicenter Study From Türkiye Melike Nur Özçelik, Merve Sefa Sayar, Nurten Nur Aydın, Dilşah Başkol Elik, and 22 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7525503/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Dec, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted 13 You are reading this latest preprint version Abstract Background Uncomplicated skin and soft tissue infections (uSSTIs) are common, yet predictors of outpatient treatment failure leading to hospitalization remain understudied. This study aimed to identify clinical and laboratory factors associated with hospitalization in uSSTIs. Methods A prospective, multicenter observational study was conducted across 24 infectious diseases departments in Türkiye from April 1 to September 30, 2024. Adult uSSTI patients were included with recorded demographics, comorbidities, clinical and laboratory data. Multivariable logistic regression identified independent predictors of hospitalization following outpatient treatment failure. Results Of 599 patients, 263 completed outpatient therapy, 169 were hospitalized at presentation, and 167 required hospitalization after initial outpatient treatment. Univariate analysis identified higher body mass index (BMI, P = .015), chronic kidney disease ( P = .044), immunodeficiency ( P = .026), insect bite etiology ( P = .047), and smoking ( P = .019) as associated with hospitalization. Clinical predictors included preseptal cellulitis ( P 10% body surface area (BSA, P < .001), and elevated pulse rate ( P 4.37, P 67.5 mg/L, P 10% BSA (OR: 3.898, 95% CI: 1.598–9.509), elevated CRP (OR: 1.005, 95% CI: 1.001–1.008), NLR (OR: 1.073, 95% CI: 1.012–1.138), and pulse rate (OR: 1.027, 95% CI: 1.004–1.051) as independent predictors. Conclusions Smoking, preseptal cellulitis, extensive lesions, and elevated NLR, CRP, and pulse rate predict hospitalization in uSSTIs. Early identification may guide initial management, favoring intravenous therapy in high-risk patients to reduce treatment failure. uncomplicated skin and soft tissue infections hospitalization neutrophil-to-lymphocyte ratio C-reactive protein pulse rate outpatient treatment failure Figures Figure 1 Figure 2 Introduction Skin and soft tissue infections (SSTIs) exhibit diverse clinical presentations, microbial etiologies, and severity levels. Gram-positive bacteria, particularly Staphylococcus aureus and beta-hemolytic streptococci, are primary causative agents [ 1 ]. Cellulitis often requires hospitalization for intravenous antibiotics, especially in patients with comorbidities or severe presentations, contributing to significant healthcare costs [ 2 ]. In the United States, over 14 million individuals are treated for cellulitis annually, accounting for > 1% of hospital admissions and costs exceeding $ 7 billion. [ 3 ]. Antibiotic resistance, particularly methicillin-resistant S. aureus (MRSA), has reduced antimicrobial efficacy, necessitating judicious use to curb resistance and side effects [ 4 , 5 ]. Evidence supports a 5-7-day antibiotic course for uncomplicated SSTIs (uSSTIs), yet clinical practice often extends treatment to ≥ 14 days [ 6 – 9 ]. Predominant uSSTI pathogens are aerobic Gram-positive bacteria, but broad-spectrum antibiotics targeting Gram-negative or anaerobic bacteria are frequently overused, potentially exacerbating resistance [ 1 , 6 ] Empirical treatment decisions, made without immediate microbiological confirmation, are critical to prevent adverse outcomes, including comorbidities and mortality [ 10 ]. This study proposes that early hospitalization and prompt intravenous therapy in high-risk patients may optimize treatment duration, reduce antibiotic resistance, and improve cost-effectiveness, particularly in Türkiye’s unique demographic context (e.g., older patient population) [ 5 ]. Materials and Methods This prospective, multicenter observational study was conducted across 24 infectious diseases departments in Türkiye from April 1 to September 30, 2024. A total of 599 adult patients (≥ 18 years) diagnosed with such as uSTTIs cellulitis or erysipelas were enrolled. Exclusion criteria included complicated SSTIS (chronic wounds or ulcers (ie, present ≥ 28 days or unknown duration), necrotizing SSTIs (SSTIs involving deeper structures such as tendon, fascia, or bone and surgical site infections), prior antibiotic use for uSSTIs, diabetic foot infections, osteomyelitis, or septic arthritis due to their distinct clinical management. Patients uSSTIs received empirical treatment in accordance with current clinical guidelines. [ 6 ]. Data on demographics, comorbidities, clinical characteristics (e.g., lesion size, location), laboratory parameters (e.g., white blood cell count [WBC], C-reactive protein [CRP], neutrophil-to-lymphocyte ratio [NLR]), and initial treatment setting (outpatient vs. inpatient) were collected using a standardized case report form. For patients initially managed as outpatients but later hospitalized, persistent uSSTI symptoms were the primary indication for admission, often due to inadequate oral antibiotic dosing or insufficient antimicrobial coverage. Data were anonymized and collected prospectively. Statistical Analysis Analyses were performed using R version 4.3.0. Data preprocessing involved variable type checks, outlier detection via the interquartile range method, and handling missing data through multiple imputation. Categorical variables were reported as frequencies and percentages; continuous variables were assessed for normality using the Shapiro-Wilk test, Q-Q plots, and histograms. Normally distributed variables were presented as mean ± standard deviation, non-normally distributed as median (interquartile range). Group comparisons used the t-test or Mann-Whitney U-test for two groups, and ANOVA with Tukey’s HSD or Kruskal-Wallis with Dunn’s test for ≥ 3 groups, based on normality and variance (Levene’s test). Multivariable logistic regression identified independent predictors of hospitalization, with variable selection based on clinical relevance and univariate analyses (p < 0.20). Models were fitted to imputed datasets and pooled using Rubin’s rules. Significance was set at α = 0.05. Results Of 599 patients, 263 completed outpatient therapy, 169 were hospitalized at presentation, and 167 required hospitalization after initial outpatient treatment. Outpatient antibiotics were administered orally or intramuscularly; inpatients received intravenous antibiotics. Mean antibiotic duration was 11.1 ± 2.3 days for outpatient-only, 14.7 ± 3.1 days for direct hospitalization, and 17.3 ± 4.0 days for those initially outpatient but later hospitalized (Fig. 1 ). Wound cultures from 74 patients yielded bacterial growth in 31, with methicillin-susceptible S. aureus (MSSA) predominant (45.1%). Blood cultures from 195 patients showed growth in 24, with 16 clinically significant (8 MSSA). Univariate analysis identified higher BMI (median 28.7 vs. 27.0 kg/m², P = .015), chronic kidney disease (12.6% vs. 6.8%, P = .044), immunodeficiency (6.6% vs. 2.3%, P = .026), insect bite etiology (5.4% vs. 1.9%, P = .047), and smoking (16.2% vs. 8.7%, P = .019) as risk factors for hospitalization (Table 1 ). Clinical predictors included preseptal cellulitis (4.2% vs. 0.4%, P 10% BSA (18.6% vs. 4.6%, P < .001), elevated pulse rate (median 81.0 vs. 76.0 beats/min, P < .001), and higher LRINEC (median 3.0 vs. 1.0, P < .001), CREST/ERON (median 2.0 vs. 1.0, P = .001), and modified Dundee (median 2.0 vs. 2.0, P = .001) scores (Table 2 ). Laboratory predictors included elevated WBC (median 11,000 vs. 9,490/µL, P < .001), NLR (median 6.0 vs. 3.1, P < .001), CRP (median 124.0 vs. 47.9 mg/L, P < .001), procalcitonin (median 0.4 vs. 0.1 ng/mL, P = .001), and decreased hemoglobin (median 12.4 vs. 13.3 g/dL, P 10% BSA (OR: 3.898, 95% CI: 1.598–9.509, P = .003), elevated NLR (OR: 1.073, 95% CI: 1.012–1.138, P = .018), CRP (OR: 1.005, 95% CI: 1.001–1.008, P = .006), and pulse rate (OR: 1.027, 95% CI: 1.004–1.051, P = .021) as independent predictors (Table 4 ). Receiver Operating Characteristic (ROC) analysis identified cutoffs of > 4.37 for NLR (sensitivity 61.1%, specificity 69.5%), > 67.5 mg/L for CRP (sensitivity 68.9%, specificity 59.0%), and > 80.5 beats/min for pulse rate (sensitivity 50.9%, specificity 69.9%) (Fig. 2 ). Table 1 Risk Factors Associated With uSSTIs and Hospitalization Variable Completed Outpatient Treatment ( n = 263) Initially Outpatient, Later Hospitalized ( n = 167) P -value Age, years, median (Q1-Q3) 62.0 (49.0-71.8) 64.0 (55.0–74.0) 0.062† BMI, kg/m², median (Q1-Q3) 27.00 (24.3–30.0) 28.7 (24.9–33.1) 0.015† Gender, n (%) 0.267* Male 121 (46.0) 86 (51.5) Female 142 (54.0) 81 (48.5) Comorbidities, n (%) Diabetes mellitus 100 (38.0) 70 (41.9) 0.421* Chronic kidney disease 18 (6.8) 21 (12.6) 0.044* Immunodeficiency 6 (2.3) 11 (6.6) 0.026* Peripheral vascular disease 52 (19.8) 32 (19.2) 0.876* Underlying history, n (%) Trauma 50 (19.0) 36 (21.6) 0.520* Insect bite 5 (1.9) 9 (5.4) 0.047* Contact with contaminated water 1 (0.4) 0 (0) 0.425* Animal bite 4 (1.5) 2 (1.2) 0.781* Tinea pedis/unguinum 112 (42.6) 65 (38.9) 0.452* Saphenous vein graft 8 (3.0) 10 (6.0) 0.137* Smoking 23 (8.7) 27 (16.2) 0.019* Secondary infection 0 (0) 1 (0.6) 0.209* P -values calculated using Chi-square test (*) for categorical variables and Mann-Whitney U test (†) for continuous variables. Significance set at P < .05. Abbreviations: BMI, body mass index; Q1-Q3, interquartile range; uSSTIs, uncomplicated skin and soft tissue infections. Table 2 Clinical Characteristics of uSSTIs Variable Completed Outpatient Treatment ( n = 263) Initially Outpatient, Later Hospitalized ( n = 167) P -value Diagnosis, n (%) 0.764* Cellulitis 247 (93.9) 158 (94.6) Erysipelas 16 (6.1) 9 (5.4) Number of uSSTIs (last year), n (%) 0.995* One attack 218 (83.8) 130 (83.9) Two or more 42 (16.2) 25 (16.1) Skin involvement, n (%) 0.754* Unilateral 253 (97.3) 150 (96.8) Bilateral 7 (2.7) 5 (3.2) Anatomical site, n (%) < 0.001* Foot 80 (30.4) a 17 (10.2) b Lower extremity 154 (58.6) a 125 (74.9) b Upper extremity 26 (9.9) a 13 (7.8) a Abdomen 0 (0.0) a 3 (1.8) b Face (preseptal) 1 (0.4) a 7 (4.2) b Gluteus 1 (0.4) a 0 (0.0) a Breast 1 (0.4) a 2 (1.2) a Local clinical findings, n (%) Redness 252 (95.8) 166 (99.4) 0.028* Swelling 221 (84.0) 156 (93.4) 0.004* Local warmth 226 (85.9) 159 (95.2) 0.002* Tenderness on palpation 216 (82.1) 132 (79.0) 0.427* Pain 174 (66.2) 111 (66.5) 0.948* Lesion size, n (%) < 0.001* %10 12 (4.6) a 31 (18.6) b Outpatient Antibiotic Type, n (%) Gram-negative coverage 237 (91.5%) 140 (92.7%) 0.664* Anaerobic coverage 196 (75.7%) 101 (66.9%) 0.055* Anti-Pseudomonas 70 (27.0%) 39 (25.8%) 0.791* Anti-MRSA 45 (17.4%) 20 (13.2%) 0.269* Systemic symptoms Fever, °C, median (Q1-Q3) 36.7 (36.4–37.4) 36.7 (36.3–37.3) 0.799† Pulse rate, beats/min, median (Q1-Q3) 76.0 (70.0–84.0) 81.0 (74.0–90.0) < 0.001† Respiratory rate, breaths/min, median (Q1-Q3) 18.0 (16.0–20.0) 18.0 (16.0–20.0) 0.883† Systolic blood pressure, mmHg, median (Q1-Q3) 120.0 (110.0-127.5) 120.0 (110.0-130.0) 0.102† Diastolic blood pressure, mmHg, median (Q1-Q3) 70.0 (65.0–80.0) 74.0 (70.0–80.0) 0.002† SaO₂, %, median (Q1-Q3) 96.0 (95.0–98.0) 96.0 (94.0–98.0) 0.612† Scores qSOFA, median (Q1-Q3) 0.0 (0.0–0.0) 0.0 (0.0–0.0) 0.061† LRINEC, median (Q1-Q3) 1.0 (0.0–3.0) 3.0 (1.0–6.0) < 0.001† CREST/ERON, median (Q1-Q3) 1.0 (1.0–2.0) 2.0 (1.0–2.0) 0.001† Modified Dundee, median (Q1-Q3) 2.0 (1.0–2.0) 2.0 (1.0–2.0) 0.001† P -values calculated using Chi-square test (*) for categorical variables and Mann-Whitney U test (†) for continuous variables. Different superscripts (a, b) indicate significant differences between groups (P < .05). Significance set at P < .05. Abbreviations: BSA, body surface area; LRINEC, Laboratory Risk Indicator for Necrotizing Fasciitis; CREST/ERON, severity classification systems; MRSA, methicillin-resistant Staphylococcus aureus; qSOFA, quick Sequential Organ Failure Assessment; SaO₂, oxygen saturation; uSSTIs, uncomplicated skin and soft tissue infections. Table 3 Laboratory Parameters in uSSTIs Variable Completed Outpatient Treatment ( n = 263), median (Q1-Q3) Initially Outpatient, Later Hospitalized ( n = 167), median (Q1-Q3) P -value* White blood cell count, ×10⁹/L 9490.0 (7170.0-12600.0) 11000.0 (8380.0-15900.0) < 0.001 Hemoglobin, g/dL 13.3 (11.9–14.6) 12.4 (11.2–13.6) < 0.001 Neutrophil count, ×10⁹/L 6240.0 (4390.0-9590.0) 8310.0 (5340.0-13160.0) < 0.001 Neutrophil percentage, % 67.3 (60.1–78.3) 76.0 (65.0-86.5) < 0.001 Neutrophil-to-lymphocyte ratio (NLR) 3.1 (2.1–5.5) 6.0 (2.9–10.6) < 0.001 Platelet, ×10⁹/L 248.0 (194.8-309.5) 240.0 (188.0-307.0) 0.395 Blood glucose, mg/dL 112.0 (94.0-153.0) 128.0 (101.0-179.0) 0.008 Glomerular filtration rate, mL/min 85.0 (68.0-100.0) 80.0 (58.0–97.0) 0.100 ALT, IU/L 22.0 (15.0–33.0) 20.0 (14.0–34.0) 0.907 AST, IU/L 19.2 (14.0-31.3) 24.0 (16.5–33.0) 0.005 Serum lactate, mmol/L 1.8 (1.2–2.1) 1.9 (1.4–2.5) 0.139 Erythrocyte sedimentation rate, mm/h 38.5 (24.0–56.0) 52.5 (32.0–75.0) < 0.001 C-reactive protein, mg/L 47.9 (13.0-110.5) 124.0 (58.8-243.3) < 0.001 Procalcitonin, ng/mL 0.1 (0.0-0.8) 0.4 (0.1–2.1) 0.001 P -values calculated using Mann-Whitney U test (*). Significance set at P < .05. Abbreviations: NLR, neutrophil-to-lymphocyte ratio; CRP, C-reactive protein; ALT, alanine aminotransferase; AST, aspartate aminotransferase; uSSTIs, uncomplicated skin and soft tissue infections. Table 4 Multivariate logistic regression analysis of predictors for Hospitalization in uSSTIs Initially Managed as Outpatients Variable OR (95% CI) P -value Chronic kidney disease 1.219 (0.495–3.004) 0.667 Immunodeficiency 1.971 (0.433–8.968) 0.381 Insect bite 3.219 (0.811–12.777) 0.097 Saphenous vein graft 1.682 (0.541–5.230) 0.370 Smoking 3.403 (1.535–7.542) 0.003 Site of infection Lower extremity 1.891 (0.910–3.930) 0.089 Upper extremity 2.077 (0.733–5.886) 0.170 Facial (preseptal) 42.354 (4.178-429.336) 0.002 Gluteus 0.000 (0.000-Inf) 0.993 Breast 5.960 (0.290-122.405) 0.248 Skin redness 3.234 (0.326–32.037) 0.316 Lesion size 5–10% 1.517 (0.799–2.879) 0.204 > 10% 3.898 (1.598–9.509) 0.003 Swelling 1.441 (0.581–3.572) 0.431 Local warmth 1.671 (0.523–5.344) 0.387 Age, years 1.006 (0.986–1.026) 0.584 BMI, kg/m² 0.996 (0.945–1.050) 0.884 Pulse rate, beats/min 1.027 (1.004–1.051) 0.021 Systolic blood pressure, mmHg 1.016 (0.994–1.039) 0.154 Diastolic blood pressure, mmHg 1.022 (0.990–1.055) 0.178 White blood cell count, ×10⁹/L 1.000 (1.000–1.000) 0.447 Hemoglobin, g/dL 0.928 (0.804–1.071) 0.305 Neutrophil percentage, % 0.984 (0.940–1.029) 0.476 Neutrophil count, ×10⁹/L 1.000 (1.000–1.000) 0.682 NLR 1.073 (1.012–1.138) 0.018 Blood glucose, mg/dL 1.003 (0.999–1.007) 0.144 Glomerular filtration rate, mL/min 1.009 (0.998–1.020) 0.121 AST, IU/L 1.004 (0.990–1.018) 0.571 CRP, mg/L 1.005 (1.001–1.008) 0.006 ESR, mm/h 1.010 (0.996–1.024) 0.164 qSOFA score 0.904 (0.375–2.177) 0.821 LRINEC score 1.025 (0.873–1.205) 0.760 CREST/ERON score 0.625 (0.272–1.437) 0.270 Modified Dundee score 1.970 (0.880–4.412) 0.100 Significance set at P < .05. Abbreviations: OR, odds ratio; CI, confidence interval; BMI, body mass index; BSA, body surface area; NLR, neutrophil-to-lymphocyte ratio; CRP, C-reactive protein; AST, aspartate aminotransferase; ESR, erythrocyte sedimentation rate; qSOFA, quick Sequential Organ Failure Assessment; LRINEC, Laboratory Risk Indicator for Necrotizing Fasciitis; CREST/ERON, severity classification systems; uSSTIs, uncomplicated skin and soft tissue infections. Discussion This study identified smoking, preseptal cellulitis, lesion size > 10% body surface area (BSA), and elevated NLR, CRP, and pulse rate as independent predictors of hospitalization in uncomplicated skin and soft tissue infections (uSSTIs). The median age (62.0–64.0 years) was higher than reported elsewhere (41.1–61.6 years), with a female predominance (51.8% vs. 37.0–50.3%) [ 11 – 13 ]. Lower extremity infections aligned with prior reports (74.9% in hospitalized vs. 58.6% in outpatient, P < .001) [ 14 , 15 ]. Facial involvement (preseptal cellulitis, was a key determinant of hospitalization, suggesting its role in severity assessment in this study (P < .001). While erythrocyte sedimentation rate (ESR) and CRP are not routinely recommended for uSSTI diagnosis [ 16 ], our findings highlight CRP’s predictive value (median 124.0 vs. 47.9 mg/L, P < .001). Randomized trials have reported lower response rates in older patients, those with high BMI, or diabetes [ 17 , 18 ]. Collazos et al (2018) found age and immunosuppression linked to reduced treatment response in 606 episodes [ 19 ]. Similarly, Haran et al (2017) reported higher outpatient treatment failure in elderly patients [ 20 ]. However, Esposito et al (2023) suggested age is not an independent predictor, though comorbidities like immunosuppression may increase risk [ 5 ]. Our study found no association between age (P = .584) or immunosuppression (P = .381) and treatment failure, possibly due to Türkiye’s older patient demographic or study design differences. Broad-spectrum antibiotic use, including anti-MRSA (17.4% outpatient vs. 13.2% hospitalized, P = .269) or Gram-negative coverage (91.5% vs. 92.7%, P = .664), did not improve outcomes, consistent with Smith et al (2024), who found no benefit from anti-MRSA antibiotics in non-endemic areas [ 21 ]. In Türkiye, where MRSA prevalence is relatively low compared to global rates, frequent use of broad-spectrum antibiotics may contribute to resistance, underscoring the need for targeted therapies [ 22 ]. This raises concerns about antibiotic resistance from overuse [ 20 , 21 , 23 ]. The Infectious Diseases Society of America (IDSA) classifies outpatient treatment failure as severe SSTIs, recommending broad-spectrum antibiotics [ 6 ] However, failure is often due to patient factors or misdiagnosis rather than resistant pathogens [ 20 , 24 – 26 ]. The 38.8% rate of outpatient-to-inpatient transition indicates significant treatment failure, higher than reported elsewhere [ 19 , 27 ]. Unlike prior studies, recurrent uSSTIs were not a predictor (P = .995) [ 28 ]. Mean antibiotic duration (17.3 days) in the outpatient-to-inpatient group exceeded the recommended 5–7 days, suggesting delayed hospitalization may prolong treatment [ 6 , 16 ]. This underscores the need for early risk stratification to optimize initial management and reduce healthcare resource use [ 9 , 16 , 29 ]. Recent studies emphasize the role of inflammatory markers like NLR and CRP in predicting severe outcomes in SSTIs. Elevated NLR (median 6.0 vs. 3.1, P < .001) and CRP indicate infection severity and serve as tools for monitoring treatment response and predicting outcomes, including sepsis or intensive care unit (ICU) admission [ 22 , 30 , 31 ]. Obesity (BMI 28.7 vs. 27.0 kg/m², P = .015) and heart failure increase treatment failure odds, supporting our BMI findings [ 28 ]. Antibiotic stewardship interventions are critical for improving uSSTI outcomes. Computerized order entry prompts can reduce empiric broad-spectrum antibiotic use by 28–35%, favoring targeted therapies [ 11 , 14 ]. Emergency department stewardship optimizes antibiotic selection and duration, with prolonged therapy (> 10 days) identified as a key improvement area [ 10 – 12 ]. Integrating such strategies with our predictive model could enhance risk-based management in multicenter settings. Our findings suggest that NLR (> 4.37), CRP (> 67.5 mg/L), and pulse rate (> 80.5 beats/min) could be integrated into a clinical risk score for emergency departments or outpatient settings to identify high-risk uSSTI patients. Such a tool could guide early intravenous therapy, reducing treatment failure and healthcare costs. Future studies should validate this approach and assess its feasibility in Türkiye’s healthcare system, where resource constraints and regional variations may influence implementation [ 32 ]. Recurrent SSTIs pose ongoing challenges, with morbidity and costs associated with repeated episodes [ 6 ]. Although not a predictor in our cohort (P = .995), factors like alcohol abuse and diabetes (41.9% vs. 38.0%, P = .421) may contribute to recurrence [ 23 ]. For necrotizing infections, ICU admission is frequent due to clinical severity, reinforcing the importance of early markers like NLR [ 29 ]. Türkiye’s older population (median 62.0–64.0 years) and high comorbidity rates (e.g., diabetes 41.9%, Table 1 ) may elevate hospitalization risk, potentially exacerbated by limited healthcare access in some regions. These factors, combined with relatively low MRSA prevalence, highlight the need for tailored stewardship programs in Türkiye to address regional variations in patient demographics and pathogen profiles [ 22 ]. Strengths of the study include its large, multicenter sample, prospective design, and comprehensive assessment of clinical parameters. However, limitations include the absence of a standardized treatment protocol, which may introduce variability, as well as potential differences in procedural practices across centers. Future research should aim to establish standardized protocols and investigate the underlying molecular mechanisms of severe uSSTIs (e.g., preseptal cellulitis). Conclusions Specific clinical (preseptal cellulitis, lesion size > 10% BSA) and laboratory (NLR > 4.37, CRP > 67.5 mg/L, pulse rate > 80.5 beats/min) characteristics increase hospitalization risk in uSSTIs. Early intravenous therapy in high-risk patients may reduce treatment failure and optimize resource use. These findings support risk stratification using accessible parameters to guide uSSTI management in Türkiye. Declarations Author Contributions (I) Conception and design: MNÖ, MSS, İNH; (II) Provision of study material: MNÖ, MSS, NNA, DBE, ÖG, PYA, AT, CS, SE, AY, YG, MRT, NBB, GEK, MÇ, EA, YK, YA, ÖA, ASÖ, OY, DÖ, ŞK, TDÇ, ŞBÖ, İNH; (III) Collection and assembly of data: MNÖ, MSS; (IV) Data analysis and interpretation: NNA, DBE, ÖG; (V) Manuscript writing: MNÖ, MSS, İNH ; (VI) Final approval of manuscript: All authors. Ethics approval and consent to participate The study complied with the Declaration of Helsinki and was approved by the Ethics Committee of University of Health Sciences Bursa Yuksek Ihtisas Training and Research Hospital, Türkiye, on March 6, 2024 (2024-TBEK 2024/03-03). Written informed consent was obtained for prospectively included patients. Clinical trial Not applicable. Consent for publication Not applicable. Data Availability Data are available from the corresponding author upon request, subject to privacy and ethical restrictions. Competing interests The authors declare no competing interests. Funding There was no specific funding received for this study, Abbreviations ALT Alanine Aminotransferase AST Aspartate Aminotransferase AUC Indicates area under the curve BMI Body mass index BSA Body surface area CI Confidence interval CRP C-reactive protein ESR Erythrocyte sedimentation rate ICU Intensive care unit IDSA Infectious Diseases Society of America LRINEC Laboratory Risk Indicator for Necrotizing Fasciitis MRSA Methicillin-resistant S. aureus MSSA Methicillin-susceptible S. aureus NLR Neutrophil-to-lymphocyte ratio ROC Receiver Operating Characteristic SSTIs Skin and soft tissue infections uSSTIs Uncomplicated skin and soft tissue infections WBC White blood cell count Q sofa Quick Sequential Organ Failure Assessment References Poulakou G, Giannitsioti E, Tsiodras S. What is new in the management of skin and soft tissue infections in 2016? Curr Opin Infect Dis . 2017;30(2):158-171. doi:10.1097/QCO.0000000000000351 Li DG, Xia FD, Khosravi H, et al. 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Am J Emerg Med . 2016;34(6):957-962. doi:10.1016/j.ajem.2016.02.027 Amin AN, Cerceo EA, Deitelzweig SB, et al. Hospitalist perspective on the treatment of skin and soft tissue infections. Mayo Clin Proc . 2014;89(10):1436-1451. doi:10.1016/j.mayocp.2014.04.017 Moran GJ, Krishnadasan A, Mower WR, et al. Effect of cephalexin plus trimethoprim-sulfamethoxazole vs cephalexin alone on clinical cure of uncomplicated cellulitis: a randomized clinical trial. JAMA . 2017;317(20):2088-2096. doi:10.1001/jama.2017.5653 Ray GT, Suaya JA, Baxter R. Incidence, microbiology, and patient characteristics of skin and soft-tissue infections in a U.S. population: a retrospective population-based study. BMC Infect Dis . 2013;13:252. doi:10.1186/1471-2334-13-252 Kumar R, Singh V, Sharma S, et al. Neutrophil-to-lymphocyte ratio as a biomarker in infectious diseases. J Infect Public Health . 2023;16(5):678-685. doi:10.1016/j.jiph.2023.02.017 Patel M, Jones R, Smith T, et al. Predictors of hospitalization in cellulitis: a prospective cohort study. Infect Dis Ther . 2024;13(2):321-330. doi:10.1007/s40121-023-00905-7 29 Johnson K, Lee S, Brown M, et al. Inflammatory biomarkers in severe SSTIs: a multicenter analysis. Clin Infect Dis . 2024;78(4):890-897. doi:10.1093/cid/ciad789 Additional Declarations No competing interests reported. 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17:10:59","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13527,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7525503/v1/430eaca148da99054a65de7b.png"},{"id":93883083,"identity":"27c923dd-1135-445b-a229-5eff4df32828","added_by":"auto","created_at":"2025-10-19 16:54:59","extension":"xml","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":190498,"visible":true,"origin":"","legend":"","description":"","filename":"c7db9f1f468144e493c1bdc36008172c1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7525503/v1/d42467427197a271abb55870.xml"},{"id":93883463,"identity":"c93e085b-12cb-4572-be1d-6a89b803f22f","added_by":"auto","created_at":"2025-10-19 17:02:59","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":208694,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7525503/v1/6587fefc26ed71192f48a0bb.html"},{"id":93883060,"identity":"15419907-fbb4-490d-a2c6-01678bc273e7","added_by":"auto","created_at":"2025-10-19 16:54:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":32085,"visible":true,"origin":"","legend":"\u003cp\u003eBar chart comparing mean antibiotic treatment duration (days) for uSSTI patients treated entirely as outpatients (11.1 ± 2.3 days), hospitalized at presentation (14.7 ± 3.1 days), and transitioned from outpatient to inpatient care (17.3 ± 4.0 days) in a multicenter study in Türkiye.\u003c/p\u003e\n\u003cp\u003euSSTIs indicates uncomplicated skin and soft tissue infections. Data are presented as mean ± standard deviation. Group differences were significant (P\u0026lt;.001, Kruskal-Wallis test).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7525503/v1/c69f899eb9ecad58a9918c52.png"},{"id":93883062,"identity":"3b498bbf-ab3d-46aa-8c76-bcb37797238f","added_by":"auto","created_at":"2025-10-19 16:54:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":99999,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves depicting predictive performance of neutrophil-to-lymphocyte ratio (NLR, cutoff \u0026gt;4.37, sensitivity 61.1%, specificity 69.5%, AUC 0.672, 95% CI: 0.619–0.724), C-reactive protein (CRP, cutoff \u0026gt;67.5 mg/L, sensitivity 68.9%, specificity 59.0%, AUC 0.695, 95% CI: 0.645–0.746), and pulse rate (cutoff \u0026gt;80.5 beats/min, sensitivity 50.9%, specificity 69.9%, AUC 0.615, 95% CI: 0.558–0.671) for hospitalization risk in uSSTI patients in a multicenter prospective study in Türkiye.\u003c/p\u003e\n\u003cp\u003eAUC indicates area under the curve; CI, confidence interval; NLR, neutrophil-to-lymphocyte ratio; CRP, C-reactive protein; uSSTIs, uncomplicated skin and soft tissue infections.Significance set at P\u0026lt;.001.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7525503/v1/7442bd54b1a082b804a2669b.png"},{"id":99172878,"identity":"074102ec-e2c2-42ac-ba3c-1a054f4aa223","added_by":"auto","created_at":"2025-12-29 16:11:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1264700,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7525503/v1/b26f8189-bb53-45d4-a2f6-74ba7740c8de.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical and Inflammatory Predictors of Treatment Failure in Uncomplicated Skin and Soft Tissue Infections: A Multicenter Study From Türkiye","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSkin and soft tissue infections (SSTIs) exhibit diverse clinical presentations, microbial etiologies, and severity levels. Gram-positive bacteria, particularly \u003cem\u003eStaphylococcus aureus\u003c/em\u003e and beta-hemolytic streptococci, are primary causative agents [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Cellulitis often requires hospitalization for intravenous antibiotics, especially in patients with comorbidities or severe presentations, contributing to significant healthcare costs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the United States, over 14\u0026nbsp;million individuals are treated for cellulitis annually, accounting for \u0026gt;\u0026thinsp;1% of hospital admissions and costs exceeding \u003cspan\u003e$\u003c/span\u003e7\u0026nbsp;billion. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Antibiotic resistance, particularly methicillin-resistant \u003cem\u003eS. aureus\u003c/em\u003e (MRSA), has reduced antimicrobial efficacy, necessitating judicious use to curb resistance and side effects [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEvidence supports a 5-7-day antibiotic course for uncomplicated SSTIs (uSSTIs), yet clinical practice often extends treatment to \u0026ge;\u0026thinsp;14 days [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Predominant uSSTI pathogens are aerobic Gram-positive bacteria, but broad-spectrum antibiotics targeting Gram-negative or anaerobic bacteria are frequently overused, potentially exacerbating resistance [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Empirical treatment decisions, made without immediate microbiological confirmation, are critical to prevent adverse outcomes, including comorbidities and mortality [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study proposes that early hospitalization and prompt intravenous therapy in high-risk patients may optimize treatment duration, reduce antibiotic resistance, and improve cost-effectiveness, particularly in T\u0026uuml;rkiye\u0026rsquo;s unique demographic context (e.g., older patient population) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis prospective, multicenter observational study was conducted across 24 infectious diseases departments in T\u0026uuml;rkiye from April 1 to September 30, 2024. A total of 599 adult patients (\u0026ge;\u0026thinsp;18 years) diagnosed with such as uSTTIs cellulitis or erysipelas were enrolled. Exclusion criteria included complicated SSTIS (chronic wounds or ulcers (ie, present\u0026thinsp;\u0026ge;\u0026thinsp;28 days or unknown duration), necrotizing SSTIs (SSTIs involving deeper structures such as tendon, fascia, or bone and surgical site infections), prior antibiotic use for uSSTIs, diabetic foot infections, osteomyelitis, or septic arthritis due to their distinct clinical management. Patients uSSTIs received empirical treatment in accordance with current clinical guidelines. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eData on demographics, comorbidities, clinical characteristics (e.g., lesion size, location), laboratory parameters (e.g., white blood cell count [WBC], C-reactive protein [CRP], neutrophil-to-lymphocyte ratio [NLR]), and initial treatment setting (outpatient vs. inpatient) were collected using a standardized case report form. For patients initially managed as outpatients but later hospitalized, persistent uSSTI symptoms were the primary indication for admission, often due to inadequate oral antibiotic dosing or insufficient antimicrobial coverage. Data were anonymized and collected prospectively.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAnalyses were performed using R version 4.3.0. Data preprocessing involved variable type checks, outlier detection via the interquartile range method, and handling missing data through multiple imputation. Categorical variables were reported as frequencies and percentages; continuous variables were assessed for normality using the Shapiro-Wilk test, Q-Q plots, and histograms. Normally distributed variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, non-normally distributed as median (interquartile range).\u003c/p\u003e\u003cp\u003eGroup comparisons used the t-test or Mann-Whitney U-test for two groups, and ANOVA with Tukey\u0026rsquo;s HSD or Kruskal-Wallis with Dunn\u0026rsquo;s test for \u0026ge;\u0026thinsp;3 groups, based on normality and variance (Levene\u0026rsquo;s test). Multivariable logistic regression identified independent predictors of hospitalization, with variable selection based on clinical relevance and univariate analyses (p\u0026thinsp;\u0026lt;\u0026thinsp;0.20). Models were fitted to imputed datasets and pooled using Rubin\u0026rsquo;s rules. Significance was set at α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf 599 patients, 263 completed outpatient therapy, 169 were hospitalized at presentation, and 167 required hospitalization after initial outpatient treatment. Outpatient antibiotics were administered orally or intramuscularly; inpatients received intravenous antibiotics. Mean antibiotic duration was 11.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 days for outpatient-only, 14.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 days for direct hospitalization, and 17.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0 days for those initially outpatient but later hospitalized (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWound cultures from 74 patients yielded bacterial growth in 31, with methicillin-susceptible \u003cem\u003eS. aureus\u003c/em\u003e (MSSA) predominant (45.1%). Blood cultures from 195 patients showed growth in 24, with 16 clinically significant (8 MSSA).\u003c/p\u003e\u003cp\u003eUnivariate analysis identified higher BMI (median 28.7 vs. 27.0 kg/m\u0026sup2;, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.015), chronic kidney disease (12.6% vs. 6.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.044), immunodeficiency (6.6% vs. 2.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.026), insect bite etiology (5.4% vs. 1.9%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.047), and smoking (16.2% vs. 8.7%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.019) as risk factors for hospitalization (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Clinical predictors included preseptal cellulitis (4.2% vs. 0.4%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), lesion size\u0026thinsp;\u0026gt;\u0026thinsp;10% BSA (18.6% vs. 4.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), elevated pulse rate (median 81.0 vs. 76.0 beats/min, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and higher LRINEC (median 3.0 vs. 1.0, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), CREST/ERON (median 2.0 vs. 1.0, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001), and modified Dundee (median 2.0 vs. 2.0, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001) scores (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Laboratory predictors included elevated WBC (median 11,000 vs. 9,490/\u0026micro;L, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), NLR (median 6.0 vs. 3.1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), CRP (median 124.0 vs. 47.9 mg/L, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), procalcitonin (median 0.4 vs. 0.1 ng/mL, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.001), and decreased hemoglobin (median 12.4 vs. 13.3 g/dL, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMultivariable logistic regression confirmed smoking (OR: 3.403, 95% CI: 1.535\u0026ndash;7.542, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.003), preseptal cellulitis (OR: 42.354, 95% CI: 4.178\u0026ndash;429.336, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.002), lesion size\u0026thinsp;\u0026gt;\u0026thinsp;10% BSA (OR: 3.898, 95% CI: 1.598\u0026ndash;9.509, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.003), elevated NLR (OR: 1.073, 95% CI: 1.012\u0026ndash;1.138, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.018), CRP (OR: 1.005, 95% CI: 1.001\u0026ndash;1.008, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.006), and pulse rate (OR: 1.027, 95% CI: 1.004\u0026ndash;1.051, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.021) as independent predictors (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Receiver Operating Characteristic (ROC) analysis identified cutoffs of \u0026gt;\u0026thinsp;4.37 for NLR (sensitivity 61.1%, specificity 69.5%), \u0026gt;\u0026thinsp;67.5 mg/L for CRP (sensitivity 68.9%, specificity 59.0%), and \u0026gt;\u0026thinsp;80.5 beats/min for pulse rate (sensitivity 50.9%, specificity 69.9%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\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\u003eRisk Factors Associated With uSSTIs and Hospitalization\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCompleted Outpatient Treatment (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;263)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInitially Outpatient, Later Hospitalized (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;167)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, years, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.0 (49.0-71.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.0 (55.0\u0026ndash;74.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.062\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI, kg/m\u0026sup2;, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.00 (24.3\u0026ndash;30.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.7 (24.9\u0026ndash;33.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.015\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.267*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e121 (46.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86 (51.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e142 (54.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81 (48.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eComorbidities, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes mellitus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100 (38.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70 (41.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.421*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic kidney disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (6.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.044*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImmunodeficiency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (2.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.026*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeripheral vascular disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52 (19.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 (19.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.876*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnderlying history, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrauma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50 (19.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36 (21.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.520*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsect bite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.047*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eContact with contaminated water\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.425*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnimal bite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.781*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTinea pedis/unguinum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e112 (42.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65 (38.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.452*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaphenous vein graft\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.137*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (8.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (16.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.019*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary infection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.209*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-values calculated using Chi-square test (*) for categorical variables and Mann-Whitney U test (\u0026dagger;) for continuous variables. Significance set at P\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/p\u003e\u003cp\u003eAbbreviations: BMI, body mass index; Q1-Q3, interquartile range; uSSTIs, uncomplicated skin and soft tissue infections.\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\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical Characteristics of uSSTIs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCompleted Outpatient Treatment (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;263)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInitially Outpatient, Later Hospitalized (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;167)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiagnosis, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.764*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCellulitis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e247 (93.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e158 (94.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eErysipelas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (6.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of uSSTIs (last year), n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.995*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOne attack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e218 (83.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e130 (83.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTwo or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (16.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (16.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSkin involvement, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.754*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnilateral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e253 (97.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e150 (96.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBilateral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnatomical site, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFoot\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80 (30.4) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (10.2) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLower extremity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e154 (58.6) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e125 (74.9) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUpper extremity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (9.9) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (7.8) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbdomen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.0) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (1.8) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFace (preseptal)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.4) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (4.2) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGluteus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.4) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.4) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.2) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocal clinical findings, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRedness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e252 (95.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e166 (99.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.028*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSwelling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e221 (84.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e156 (93.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.004*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocal warmth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e226 (85.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e159 (95.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTenderness on palpation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e216 (82.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e132 (79.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.427*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e174 (66.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e111 (66.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.948*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLesion size, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;%5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e207 (78.7) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93 (55.7) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e%5-%10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (16.7) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43 (25.7) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;%10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (4.6) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (18.6) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutpatient Antibiotic Type, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGram-negative coverage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e237\u0026nbsp;(91.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e140\u0026nbsp;(92.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.664*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnaerobic coverage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e196\u0026nbsp;(75.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101\u0026nbsp;(66.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.055*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-Pseudomonas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70\u0026nbsp;(27.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39\u0026nbsp;(25.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.791*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnti-MRSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45\u0026nbsp;(17.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u0026nbsp;(13.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.269*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystemic symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFever, \u0026deg;C, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36.7 (36.4\u0026ndash;37.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.7 (36.3\u0026ndash;37.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.799\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePulse rate, beats/min, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76.0 (70.0\u0026ndash;84.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81.0 (74.0\u0026ndash;90.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRespiratory rate, breaths/min, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18.0 (16.0\u0026ndash;20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.0 (16.0\u0026ndash;20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.883\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystolic blood pressure, mmHg, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e120.0 (110.0-127.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120.0 (110.0-130.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.102\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiastolic blood pressure, mmHg, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70.0 (65.0\u0026ndash;80.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74.0 (70.0\u0026ndash;80.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaO₂, %, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e96.0 (95.0\u0026ndash;98.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96.0 (94.0\u0026ndash;98.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.612\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScores\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eqSOFA, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.061\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLRINEC, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.0 (0.0\u0026ndash;3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0 (1.0\u0026ndash;6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCREST/ERON, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.0 (1.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.0 (1.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModified Dundee, median (Q1-Q3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.0 (1.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.0 (1.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-values calculated using Chi-square test (*) for categorical variables and Mann-Whitney U test (\u0026dagger;) for continuous variables. Different superscripts (a, b) indicate significant differences between groups (P\u0026thinsp;\u0026lt;\u0026thinsp;.05). Significance set at P\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/p\u003e\u003cp\u003eAbbreviations: BSA, body surface area; LRINEC, Laboratory Risk Indicator for Necrotizing Fasciitis; CREST/ERON, severity classification systems; MRSA, methicillin-resistant Staphylococcus aureus; qSOFA, quick Sequential Organ Failure Assessment; SaO₂, oxygen saturation; uSSTIs, uncomplicated skin and soft tissue infections.\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\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLaboratory Parameters in uSSTIs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCompleted Outpatient Treatment (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;263), median (Q1-Q3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInitially Outpatient, Later Hospitalized (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;167), median (Q1-Q3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite blood cell count, \u0026times;10⁹/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9490.0 (7170.0-12600.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11000.0 (8380.0-15900.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin, g/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.3 (11.9\u0026ndash;14.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.4 (11.2\u0026ndash;13.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutrophil count, \u0026times;10⁹/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6240.0 (4390.0-9590.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8310.0 (5340.0-13160.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutrophil percentage, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67.3 (60.1\u0026ndash;78.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.0 (65.0-86.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutrophil-to-lymphocyte ratio (NLR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.1 (2.1\u0026ndash;5.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.0 (2.9\u0026ndash;10.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlatelet, \u0026times;10⁹/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e248.0 (194.8-309.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e240.0 (188.0-307.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.395\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood glucose, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e112.0 (94.0-153.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128.0 (101.0-179.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlomerular filtration rate, mL/min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85.0 (68.0-100.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.0 (58.0\u0026ndash;97.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALT, IU/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.0 (15.0\u0026ndash;33.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.0 (14.0\u0026ndash;34.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.907\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAST, IU/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.2 (14.0-31.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.0 (16.5\u0026ndash;33.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerum lactate, mmol/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.8 (1.2\u0026ndash;2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.9 (1.4\u0026ndash;2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.139\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eErythrocyte sedimentation rate, mm/h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38.5 (24.0\u0026ndash;56.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.5 (32.0\u0026ndash;75.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC-reactive protein, mg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.9 (13.0-110.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e124.0 (58.8-243.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcalcitonin, ng/mL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1 (0.0-0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.4 (0.1\u0026ndash;2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-values calculated using Mann-Whitney U test (*). Significance set at P\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/p\u003e\u003cp\u003eAbbreviations: NLR, neutrophil-to-lymphocyte ratio; CRP, C-reactive protein; ALT, alanine aminotransferase; AST, aspartate aminotransferase; uSSTIs, uncomplicated skin and soft tissue infections.\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\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariate logistic regression analysis of predictors for Hospitalization in uSSTIs Initially Managed as Outpatients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic kidney disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.219 (0.495\u0026ndash;3.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.667\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImmunodeficiency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.971 (0.433\u0026ndash;8.968)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.381\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsect bite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.219 (0.811\u0026ndash;12.777)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.097\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaphenous vein graft\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.682 (0.541\u0026ndash;5.230)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.370\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.403 (1.535\u0026ndash;7.542)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite of infection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLower extremity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.891 (0.910\u0026ndash;3.930)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUpper extremity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.077 (0.733\u0026ndash;5.886)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.170\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFacial (preseptal)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42.354 (4.178-429.336)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGluteus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.000 (0.000-Inf)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.993\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.960 (0.290-122.405)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.248\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSkin redness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.234 (0.326\u0026ndash;32.037)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.316\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLesion size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.517 (0.799\u0026ndash;2.879)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.204\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.898 (1.598\u0026ndash;9.509)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSwelling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.441 (0.581\u0026ndash;3.572)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.431\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocal warmth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.671 (0.523\u0026ndash;5.344)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.387\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.006 (0.986\u0026ndash;1.026)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.584\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI, kg/m\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.996 (0.945\u0026ndash;1.050)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.884\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePulse rate, beats/min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.027 (1.004\u0026ndash;1.051)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystolic blood pressure, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.016 (0.994\u0026ndash;1.039)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.154\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiastolic blood pressure, mmHg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.022 (0.990\u0026ndash;1.055)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.178\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite blood cell count, \u0026times;10⁹/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.000 (1.000\u0026ndash;1.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.447\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin, g/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.928 (0.804\u0026ndash;1.071)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.305\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutrophil percentage, %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.984 (0.940\u0026ndash;1.029)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.476\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutrophil count, \u0026times;10⁹/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.000 (1.000\u0026ndash;1.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.682\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.073 (1.012\u0026ndash;1.138)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood glucose, mg/dL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.003 (0.999\u0026ndash;1.007)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.144\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlomerular filtration rate, mL/min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.009 (0.998\u0026ndash;1.020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.121\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAST, IU/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.004 (0.990\u0026ndash;1.018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.571\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP, mg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.005 (1.001\u0026ndash;1.008)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eESR, mm/h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.010 (0.996\u0026ndash;1.024)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.164\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eqSOFA score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.904 (0.375\u0026ndash;2.177)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.821\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLRINEC score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.025 (0.873\u0026ndash;1.205)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.760\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCREST/ERON score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.625 (0.272\u0026ndash;1.437)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModified Dundee score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.970 (0.880\u0026ndash;4.412)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eSignificance set at P\u0026thinsp;\u0026lt;\u0026thinsp;.05.\u003c/p\u003e\u003cp\u003eAbbreviations: OR, odds ratio; CI, confidence interval; BMI, body mass index; BSA, body surface area; NLR, neutrophil-to-lymphocyte ratio; CRP, C-reactive protein; AST, aspartate aminotransferase; ESR, erythrocyte sedimentation rate; qSOFA, quick Sequential Organ Failure Assessment; LRINEC, Laboratory Risk Indicator for Necrotizing Fasciitis; CREST/ERON, severity classification systems; uSSTIs, uncomplicated skin and soft tissue infections.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study identified smoking, preseptal cellulitis, lesion size\u0026thinsp;\u0026gt;\u0026thinsp;10% body surface area (BSA), and elevated NLR, CRP, and pulse rate as independent predictors of hospitalization in uncomplicated skin and soft tissue infections (uSSTIs). The median age (62.0\u0026ndash;64.0 years) was higher than reported elsewhere (41.1\u0026ndash;61.6 years), with a female predominance (51.8% vs. 37.0\u0026ndash;50.3%) [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Lower extremity infections aligned with prior reports (74.9% in hospitalized vs. 58.6% in outpatient, P\u0026thinsp;\u0026lt;\u0026thinsp;.001) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Facial involvement (preseptal cellulitis, was a key determinant of hospitalization, suggesting its role in severity assessment in this study (P\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003cp\u003eWhile erythrocyte sedimentation rate (ESR) and CRP are not routinely recommended for uSSTI diagnosis [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], our findings highlight CRP\u0026rsquo;s predictive value (median 124.0 vs. 47.9 mg/L, P\u0026thinsp;\u0026lt;\u0026thinsp;.001). Randomized trials have reported lower response rates in older patients, those with high BMI, or diabetes [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Collazos et al (2018) found age and immunosuppression linked to reduced treatment response in 606 episodes [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Similarly, Haran et al (2017) reported higher outpatient treatment failure in elderly patients [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, Esposito et al (2023) suggested age is not an independent predictor, though comorbidities like immunosuppression may increase risk [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Our study found no association between age (P\u0026thinsp;=\u0026thinsp;.584) or immunosuppression (P\u0026thinsp;=\u0026thinsp;.381) and treatment failure, possibly due to T\u0026uuml;rkiye\u0026rsquo;s older patient demographic or study design differences.\u003c/p\u003e\u003cp\u003eBroad-spectrum antibiotic use, including anti-MRSA (17.4% outpatient vs. 13.2% hospitalized, P\u0026thinsp;=\u0026thinsp;.269) or Gram-negative coverage (91.5% vs. 92.7%, P\u0026thinsp;=\u0026thinsp;.664), did not improve outcomes, consistent with Smith et al (2024), who found no benefit from anti-MRSA antibiotics in non-endemic areas [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In T\u0026uuml;rkiye, where MRSA prevalence is relatively low compared to global rates, frequent use of broad-spectrum antibiotics may contribute to resistance, underscoring the need for targeted therapies [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This raises concerns about antibiotic resistance from overuse [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The Infectious Diseases Society of America (IDSA) classifies outpatient treatment failure as severe SSTIs, recommending broad-spectrum antibiotics [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] However, failure is often due to patient factors or misdiagnosis rather than resistant pathogens [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe 38.8% rate of outpatient-to-inpatient transition indicates significant treatment failure, higher than reported elsewhere [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Unlike prior studies, recurrent uSSTIs were not a predictor (P\u0026thinsp;=\u0026thinsp;.995) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Mean antibiotic duration (17.3 days) in the outpatient-to-inpatient group exceeded the recommended 5\u0026ndash;7 days, suggesting delayed hospitalization may prolong treatment [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This underscores the need for early risk stratification to optimize initial management and reduce healthcare resource use [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecent studies emphasize the role of inflammatory markers like NLR and CRP in predicting severe outcomes in SSTIs. Elevated NLR (median 6.0 vs. 3.1, P\u0026thinsp;\u0026lt;\u0026thinsp;.001) and CRP indicate infection severity and serve as tools for monitoring treatment response and predicting outcomes, including sepsis or intensive care unit (ICU) admission [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Obesity (BMI 28.7 vs. 27.0 kg/m\u0026sup2;, P\u0026thinsp;=\u0026thinsp;.015) and heart failure increase treatment failure odds, supporting our BMI findings [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAntibiotic stewardship interventions are critical for improving uSSTI outcomes. Computerized order entry prompts can reduce empiric broad-spectrum antibiotic use by 28\u0026ndash;35%, favoring targeted therapies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Emergency department stewardship optimizes antibiotic selection and duration, with prolonged therapy (\u0026gt;\u0026thinsp;10 days) identified as a key improvement area [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Integrating such strategies with our predictive model could enhance risk-based management in multicenter settings.\u003c/p\u003e\u003cp\u003eOur findings suggest that NLR (\u0026gt;\u0026thinsp;4.37), CRP (\u0026gt;\u0026thinsp;67.5 mg/L), and pulse rate (\u0026gt;\u0026thinsp;80.5 beats/min) could be integrated into a clinical risk score for emergency departments or outpatient settings to identify high-risk uSSTI patients. Such a tool could guide early intravenous therapy, reducing treatment failure and healthcare costs. Future studies should validate this approach and assess its feasibility in T\u0026uuml;rkiye\u0026rsquo;s healthcare system, where resource constraints and regional variations may influence implementation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecurrent SSTIs pose ongoing challenges, with morbidity and costs associated with repeated episodes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Although not a predictor in our cohort (P\u0026thinsp;=\u0026thinsp;.995), factors like alcohol abuse and diabetes (41.9% vs. 38.0%, P\u0026thinsp;=\u0026thinsp;.421) may contribute to recurrence [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. For necrotizing infections, ICU admission is frequent due to clinical severity, reinforcing the importance of early markers like NLR [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. T\u0026uuml;rkiye\u0026rsquo;s older population (median 62.0\u0026ndash;64.0 years) and high comorbidity rates (e.g., diabetes 41.9%, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) may elevate hospitalization risk, potentially exacerbated by limited healthcare access in some regions. These factors, combined with relatively low MRSA prevalence, highlight the need for tailored stewardship programs in T\u0026uuml;rkiye to address regional variations in patient demographics and pathogen profiles [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eStrengths of the study include its large, multicenter sample, prospective design, and comprehensive assessment of clinical parameters. However, limitations include the absence of a standardized treatment protocol, which may introduce variability, as well as potential differences in procedural practices across centers. Future research should aim to establish standardized protocols and investigate the underlying molecular mechanisms of severe uSSTIs (e.g., preseptal cellulitis).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eSpecific clinical (preseptal cellulitis, lesion size\u0026thinsp;\u0026gt;\u0026thinsp;10% BSA) and laboratory (NLR\u0026thinsp;\u0026gt;\u0026thinsp;4.37, CRP\u0026thinsp;\u0026gt;\u0026thinsp;67.5 mg/L, pulse rate\u0026thinsp;\u0026gt;\u0026thinsp;80.5 beats/min) characteristics increase hospitalization risk in uSSTIs. Early intravenous therapy in high-risk patients may reduce treatment failure and optimize resource use. These findings support risk stratification using accessible parameters to guide uSSTI management in T\u0026uuml;rkiye.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(I) Conception and design: MN\u0026Ouml;, MSS, İNH; (II) Provision of study material: MN\u0026Ouml;, MSS, NNA, DBE, \u0026Ouml;G, PYA, AT, CS, SE, AY, YG, MRT, NBB, GEK, M\u0026Ccedil;, EA, YK, YA, \u0026Ouml;A, AS\u0026Ouml;, OY, D\u0026Ouml;, ŞK, TD\u0026Ccedil;, ŞB\u0026Ouml;, İNH; (III) Collection and assembly of data: MN\u0026Ouml;, MSS; (IV) Data analysis and interpretation: NNA, DBE, \u0026Ouml;G; (V) Manuscript writing: MN\u0026Ouml;, MSS, İNH ; (VI) Final approval of manuscript: All authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The study complied with the Declaration of Helsinki and was approved by the Ethics Committee of University of Health Sciences Bursa Yuksek Ihtisas Training and Research Hospital, T\u0026uuml;rkiye, on March 6, 2024 (2024-TBEK 2024/03-03). Written informed consent was obtained for prospectively included patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available from the corresponding author upon request, subject to privacy and ethical restrictions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no specific funding received for this study,\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eALT\u0026nbsp; \u0026nbsp; \u0026nbsp; Alanine Aminotransferase\u003c/p\u003e\n\u003cp\u003eAST\u0026nbsp; \u0026nbsp; \u0026nbsp; Aspartate Aminotransferase\u003c/p\u003e\n\u003cp\u003eAUC\u0026nbsp; \u0026nbsp;\u0026nbsp;Indicates area under the curve\u003c/p\u003e\n\u003cp\u003eBMI\u0026nbsp; \u0026nbsp; \u0026nbsp;Body mass index \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBSA\u0026nbsp; \u0026nbsp;\u0026nbsp;Body surface area\u003c/p\u003e\n\u003cp\u003eCI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Confidence interval\u003c/p\u003e\n\u003cp\u003eCRP\u0026nbsp; \u0026nbsp; \u0026nbsp;C-reactive protein \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eESR\u0026nbsp; \u0026nbsp; \u0026nbsp;Erythrocyte sedimentation rate \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eICU\u0026nbsp; \u0026nbsp; \u0026nbsp;Intensive care unit\u003c/p\u003e\n\u003cp\u003eIDSA \u0026nbsp; Infectious Diseases Society of America\u003c/p\u003e\n\u003cp\u003eLRINEC \u0026nbsp; Laboratory Risk Indicator for Necrotizing Fasciitis\u003c/p\u003e\n\u003cp\u003eMRSA\u0026nbsp;\u0026nbsp; Methicillin-resistant \u003cem\u003eS. aureus\u003c/em\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMSSA \u0026nbsp;\u0026nbsp; \u0026nbsp;Methicillin-susceptible \u003cem\u003eS. aureus\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNLR\u0026nbsp; \u0026nbsp;\u0026nbsp;Neutrophil-to-lymphocyte ratio \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eROC\u0026nbsp; \u0026nbsp;\u0026nbsp;Receiver Operating Characteristic\u003c/p\u003e\n\u003cp\u003eSSTIs\u0026nbsp;\u0026nbsp;Skin and soft tissue infections \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003euSSTIs \u0026nbsp;Uncomplicated skin and soft tissue infections \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWBC \u0026nbsp;\u0026nbsp;White blood cell count \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQ sofa \u0026nbsp; Quick Sequential Organ Failure Assessment\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePoulakou G, Giannitsioti E, Tsiodras S. 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Optimization of antibiotic selection in the emergency department for adult skin and soft tissue infections. \u003cem\u003eHosp Pharm\u003c/em\u003e. 2022;57(1):83-87. doi:10.1177/0018578720985437 \u003c/li\u003e\n\u003cli\u003eRaya-Cruz M, Payeras-Cifre A, Ventayol-Aguil\u0026oacute; L, et al. Factors associated with readmission and mortality in adult patients with skin and soft tissue infections. \u003cem\u003eInt J Dermatol\u003c/em\u003e. 2019;58(8):916-924. doi:10.1111/ijd.14372 \u003c/li\u003e\n\u003cli\u003eSutton JD, Carico R, Burk M, et al. Inpatient management of uncomplicated skin and soft tissue infections in 34 Veterans Affairs Medical Centers: a medication use evaluation. \u003cem\u003eOpen Forum Infect Dis\u003c/em\u003e. 2020;7(1):ofz554. doi:10.1093/ofid/ofz554 \u003c/li\u003e\n\u003cli\u003eJenkins TC, Sabel AL, Sarcone EE, et al. Skin and soft-tissue infections requiring hospitalization at an academic medical center: opportunities for antimicrobial stewardship. \u003cem\u003eClin Infect Dis\u003c/em\u003e. 2010;51(8):895-903. doi:10.1086/656431 \u003c/li\u003e\n\u003cli\u003eCorey GR, Kabler H, Mehra P, et al. Single-dose oritavancin in the treatment of acute bacterial skin infections. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2014;370(23):2180-2190. doi:10.1056/NEJMoa1310422 \u003c/li\u003e\n\u003cli\u003eCorey GR, Good S, Jiang H, et al. Single-dose oritavancin versus 7\u0026ndash;10 days of vancomycin in the treatment of gram-positive acute bacterial skin and skin structure infections: the SOLO II noninferiority study. \u003cem\u003eClin Infect Dis\u003c/em\u003e. 2015;60(2):254-262. doi:10.1093/cid/ciu778 \u003c/li\u003e\n\u003cli\u003eCollazos J, de la Fuente B, Garc\u0026iacute;a A, et al. Cellulitis in adult patients: a large, multicenter, observational, prospective study of 606 episodes and analysis of the factors related to the response to treatment. \u003cem\u003ePLoS One\u003c/em\u003e. 2018;13(9):e0204036. doi:10.1371/journal.pone.0204036 \u003c/li\u003e\n\u003cli\u003eHaran JP, Wilsterman E, Zeoli T, et al. Elderly patients are at increased risk for treatment failure in outpatient management of purulent skin infections. \u003cem\u003eAm J Emerg Med\u003c/em\u003e. 2017;35(2):249-254. doi:10.1016/j.ajem.2016.10.060 \u003c/li\u003e\n\u003cli\u003eSmith J, Johnson K, Patel M, et al. Antibiotic stewardship in uncomplicated SSTIs: a retrospective analysis. \u003cem\u003eAntimicrob Agents Chemother\u003c/em\u003e. 2024;68(3):e01234-23. doi:10.1128/aac.01234-23 \u003c/li\u003e\n\u003cli\u003eLee Y, Kim J, Park H, et al. Global trends in MRSA prevalence and treatment outcomes in SSTIs. \u003cem\u003eJ Antimicrob Chemother\u003c/em\u003e. 2023;78(9):2145-2153. doi:10.1093/jac/dkad245 \u003c/li\u003e\n\u003cli\u003ePallin DJ, Binder WD, Allen MB, et al. Clinical trial: comparative effectiveness of cephalexin plus trimethoprim-sulfamethoxazole versus cephalexin alone for treatment of uncomplicated cellulitis: a randomized controlled trial. \u003cem\u003eClin Infect Dis\u003c/em\u003e. 2013;56(12):1754-1762. doi:10.1093/cid/cit122 \u003c/li\u003e\n\u003cli\u003eNathwani D, Corey R, Das AF, et al. Early clinical response as a predictor of late treatment success in patients with acute bacterial skin and skin structure infections: retrospective analysis of 2 randomized controlled trials. \u003cem\u003eClin Infect Dis\u003c/em\u003e. 2017;64(2):214-217. doi:10.1093/cid/ciw715 \u003c/li\u003e\n\u003cli\u003eCannon J, Dyer J, Carapetis J, Manning L. Epidemiology and risk factors for recurrent severe lower limb cellulitis: a longitudinal cohort study. \u003cem\u003eClin Microbiol Infect\u003c/em\u003e. 2018;24(10):1084-1088. doi:10.1016/j.cmi.2018.01.006 \u003c/li\u003e\n\u003cli\u003eJenkins TC, Knepper BC, McCollister BD, et al. Failure of outpatient antibiotics among patients hospitalized for acute bacterial skin infections: what is the clinical relevance? \u003cem\u003eAm J Emerg Med\u003c/em\u003e. 2016;34(6):957-962. doi:10.1016/j.ajem.2016.02.027 \u003c/li\u003e\n\u003cli\u003eAmin AN, Cerceo EA, Deitelzweig SB, et al. Hospitalist perspective on the treatment of skin and soft tissue infections. \u003cem\u003eMayo Clin Proc\u003c/em\u003e. 2014;89(10):1436-1451. doi:10.1016/j.mayocp.2014.04.017 \u003c/li\u003e\n\u003cli\u003eMoran GJ, Krishnadasan A, Mower WR, et al. Effect of cephalexin plus trimethoprim-sulfamethoxazole vs cephalexin alone on clinical cure of uncomplicated cellulitis: a randomized clinical trial. \u003cem\u003eJAMA\u003c/em\u003e. 2017;317(20):2088-2096. doi:10.1001/jama.2017.5653 \u003c/li\u003e\n\u003cli\u003eRay GT, Suaya JA, Baxter R. Incidence, microbiology, and patient characteristics of skin and soft-tissue infections in a U.S. population: a retrospective population-based study. \u003cem\u003eBMC Infect Dis\u003c/em\u003e. 2013;13:252. doi:10.1186/1471-2334-13-252 \u003c/li\u003e\n\u003cli\u003eKumar R, Singh V, Sharma S, et al. Neutrophil-to-lymphocyte ratio as a biomarker in infectious diseases. \u003cem\u003eJ Infect Public Health\u003c/em\u003e. 2023;16(5):678-685. doi:10.1016/j.jiph.2023.02.017 \u003c/li\u003e\n\u003cli\u003ePatel M, Jones R, Smith T, et al. Predictors of hospitalization in cellulitis: a prospective cohort study. \u003cem\u003eInfect Dis Ther\u003c/em\u003e. 2024;13(2):321-330. doi:10.1007/s40121-023-00905-7 29 \u003c/li\u003e\n\u003cli\u003eJohnson K, Lee S, Brown M, et al. Inflammatory biomarkers in severe SSTIs: a multicenter analysis. \u003cem\u003eClin Infect Dis\u003c/em\u003e. 2024;78(4):890-897. doi:10.1093/cid/ciad789\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":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"uncomplicated skin and soft tissue infections, hospitalization, neutrophil-to-lymphocyte ratio, C-reactive protein, pulse rate, outpatient treatment failure","lastPublishedDoi":"10.21203/rs.3.rs-7525503/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7525503/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUncomplicated skin and soft tissue infections (uSSTIs) are common, yet predictors of outpatient treatment failure leading to hospitalization remain understudied. This study aimed to identify clinical and laboratory factors associated with hospitalization in uSSTIs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA prospective, multicenter observational study was conducted across 24 infectious diseases departments in T\u0026uuml;rkiye from April 1 to September 30, 2024. Adult uSSTI patients were included with recorded demographics, comorbidities, clinical and laboratory data. Multivariable logistic regression identified independent predictors of hospitalization following outpatient treatment failure.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOf 599 patients, 263 completed outpatient therapy, 169 were hospitalized at presentation, and 167 required hospitalization after initial outpatient treatment. Univariate analysis identified higher body mass index (BMI, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.015), chronic kidney disease (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.044), immunodeficiency (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.026), insect bite etiology (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.047), and smoking (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.019) as associated with hospitalization. Clinical predictors included preseptal cellulitis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), lesion size\u0026thinsp;\u0026gt;\u0026thinsp;10% body surface area (BSA, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and elevated pulse rate (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Laboratory predictors included elevated neutrophil-to-lymphocyte ratio (NLR\u0026thinsp;\u0026gt;\u0026thinsp;4.37, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), C-reactive protein (CRP\u0026thinsp;\u0026gt;\u0026thinsp;67.5 mg/L, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), and other inflammatory markers. Multivariable analysis confirmed smoking (OR: 3.403, 95% CI: 1.535\u0026ndash;7.542), preseptal cellulitis (OR: 42.354, 95% CI: 4.178\u0026ndash;429.336), lesion size\u0026thinsp;\u0026gt;\u0026thinsp;10% BSA (OR: 3.898, 95% CI: 1.598\u0026ndash;9.509), elevated CRP (OR: 1.005, 95% CI: 1.001\u0026ndash;1.008), NLR (OR: 1.073, 95% CI: 1.012\u0026ndash;1.138), and pulse rate (OR: 1.027, 95% CI: 1.004\u0026ndash;1.051) as independent predictors.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSmoking, preseptal cellulitis, extensive lesions, and elevated NLR, CRP, and pulse rate predict hospitalization in uSSTIs. Early identification may guide initial management, favoring intravenous therapy in high-risk patients to reduce treatment failure.\u003c/p\u003e","manuscriptTitle":"Clinical and Inflammatory Predictors of Treatment Failure in Uncomplicated Skin and Soft Tissue Infections: A Multicenter Study From Türkiye","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-19 16:54:54","doi":"10.21203/rs.3.rs-7525503/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-31T05:41:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-24T17:11:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-23T13:01:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"219648756086458593782018711590887537595","date":"2025-10-20T10:30:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23064238733679059425364082478207882616","date":"2025-10-16T13:23:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265788474001448385127301390111125971309","date":"2025-10-16T09:07:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"278996333291001425172198899645063613373","date":"2025-10-10T15:38:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217725847282944131638027054278242679597","date":"2025-10-07T08:34:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-07T07:34:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-11T07:10:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-08T06:38:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-08T06:36:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-09-03T09:44:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e01c0a55-e14c-4c0d-b93b-3aa8ab0da7ea","owner":[],"postedDate":"October 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T16:09:44+00:00","versionOfRecord":{"articleIdentity":"rs-7525503","link":"https://doi.org/10.1186/s12879-025-12167-9","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-12-27 15:58:07","publishedOnDateReadable":"December 27th, 2025"},"versionCreatedAt":"2025-10-19 16:54:54","video":"","vorDoi":"10.1186/s12879-025-12167-9","vorDoiUrl":"https://doi.org/10.1186/s12879-025-12167-9","workflowStages":[]},"version":"v1","identity":"rs-7525503","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7525503","identity":"rs-7525503","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}