Abstract
Background
Necrotizing Fasciitis (NF) is a life-threatening infection characterized by rapid tissue destruction and high mortality. The role of timely diagnosis and surgical intervention in improving patient outcomes remains debated. This study investigates the impact of “time to diagnosis” (TTD) and “time to surgical treatment” (TTS) on the outcomes of NF patients, with a specific focus on the first six hours of critical diagnosis.
Methods
A retrospective analysis was conducted for patients hospitalized with NF between June 2016 and June 2023. Demographic data, comorbidities, clinical features, treatment, and outcomes were analyzed. The study stratified patients based on TTD (early (≤ 6 h) vs. delayed (> 6 h) and TTS (≤ 6 vs. > 6 h). Outcomes included severity scores, intensive care unit admission, length of stay (LOS), and mortality.
Results
One hundred and twenty-one patients were diagnosed with NF with a mortality rate of 10%. Early diagnosis (≤ 6 h) was associated with lower mortality (5.7% vs. 13.2%) and shorter LOS (17 vs. 27 days) compared to delayed diagnosis. Early diagnosis was associated with a lower Sequential Organ Failure Assessment (SOFA) score compared to delayed diagnosis (p = 0.02). A combined analysis of TTD and TTS revealed that the group with early diagnosis and early treatment (TTD and TTS were ≤ 6 h) had a 3% mortality rate, and 7% of them had a SOFA score > 9. In contrast, delayed diagnosis (TTD > 6 h) was significantly associated with increased mortality, regardless of the TTS.
Conclusion
Timely diagnosis within 6 h is crucial for improving outcomes in NF. While early surgical intervention is vital, our findings suggest that the time to diagnosis and subsequent resuscitation efforts may significantly impact survival. This study highlights the importance of optimizing early recognition and diagnosis in the emergency room to reduce delays and improve patient prognosis in NF. Further multicenter studies are needed to validate these findings and refine clinical protocols.
Supplementary Information
The online version contains supplementary material available at 10.1007/s00068-025-02816-8.
Keywords: Necrotizing fasciitis, Time to diagnosis, Time to intervention
Introduction
Necrotizing Fasciitis (NF) is a rare but fatal infection. It is characterized by progressive subcutaneous tissue and fascia destruction with severe systemic inflammatory response. Because of its aggressive character, it is frequently called a “flesh-eating disease” [1]. The etiology of NF is not well understood, but it is often preceded by trivial trauma, such as a superficial burn, insect bite, or even intramuscular injection [2, 3]. NF is not very common; there are 0.3 to 15 instances of NF in every 100,000 people [4].
NF has been recognized as an emergency surgical clinical condition. Despite the evolution of medical treatment, diagnosis is still challenging, and the associated mortality rate remains high at 24–34% [5, 6]. The rapid progression of NF and its subtle early symptoms are significant factors that often delay diagnosis and treatment [4]. It is also frequently misdiagnosed as cellulitis, further delaying appropriate care and contributing to high mortality rates [7].
Several tools, such as the Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score, have been developed to aid in diagnosis and prognosis. Still, no single test can definitively diagnose NF without clinical correlation [8, 9, 10]. A high index of clinical suspicion remains paramount in the diagnosis of NF. Early diagnosis and treatment of NF are crucial to stopping disease progression and preventing severe consequences. Therefore, improving clinical outcomes involves recognizing and managing factors that predict adverse results for patients with NF. One key modifiable factor that affects disease outcomes is the time between a patient’s initial presentation, diagnosis, and surgery [11].
Several studies have reported conflicting findings regarding the impact of time to surgical intervention as an independent predictor of outcomes in NF. Hadeed et al. [12] identified time to surgery as a predictor of prolonged Intensive Care Unit (ICU) and hospital length of stays (LOS). In contrast, prior studies reported that delayed surgery independently predicted mortality [13–14]. However, other studies failed to demonstrate a significant association between time to surgery and outcomes [15, 16], indicating the presence of additional independent predictors of mortality. Among these, the Sequential Organ Failure Assessment (SOFA) score stands out as a reliable mortality predictor, particularly in NF cases involving the perineum, as shown by Azmi et al. [17]. Moreover, age, seasonal variation, and comorbidities such as diabetes mellitus and renal failure have been evaluated as predictors of morbidity and mortality following NF in several studies [6, 18, 19, 20, 21, 22, 23, 24, 25, 26].
There is still a lack of a clear definition of ‘How early should intervention be?’ In the literature, most studies use “time to surgery or time to intervention” as a predictor of morbidity and mortality, and this is a general term to apply. The time spent in the emergency room (ER) before diagnosis is crucial and does impact the clinical outcome. However, the time to intervene needs more elaboration as well. This study aims to explore the impact of early diagnosis and early treatment of NF on the patient’s outcomes.
Patients and methods
We retrospectively reviewed all NF adult male and female patients who were admitted from June 2016 until June 2023. We analyzed demographic data, medical history (comorbidities), infection distribution, microbiological characteristics, clinical features, hospital course, and outcomes. The diagnosis was based on clinical suspicion and confirmed by intraoperative findings [27]. A combination of clinical evaluation, laboratory tests, and imaging studies is needed for NF diagnosis. It tends to present with a triad of swelling, severe pain, and erythema. Key diagnostic criteria include severe pain out of proportion to physical findings extending beyond the involved skin and rapidly spreading, erythema, skin discoloration and swelling of the affected area, palpable crepitus and paraesthesia over the affected area, blistering or skin necrosis, systemic manifestation [28, 29]. The intraoperative description includes foul “dishwasher” discharge and easily dissected tissue by finger fraction [28, 29]. Histological examination shows necrotizing inflammation with vascular thrombosis. Though not entirely specific, frozen sections can confirm fascial necrosis, vessel thrombosis, and acute inflammation [30].
Patients with intraoperative findings inconsistent with NF diagnosis were excluded. Also, pediatric patients and adults with incomplete information about the timings of presentation, diagnosis, and treatment were excluded. A comparative analysis of demographic, clinical, and laboratory parameters and outcomes in patients with NF was performed. The severity and mortality based on time to diagnosis (TTD) in association with time to surgical treatment (TTS) were also analyzed. In this study, patients were stratified based on TTD and TTS, emphasizing the critical period spent in the ER before surgical intervention. We hypothesized that early TTD and TTS are associated with better outcomes in NF patients. This initial period significantly impacts patients’ outcomes, with a specific focus on the first six hours as a crucial cut-off point for comparison, in alignment with existing literature [12].
Definitions
TTD is the time for the presentation at the emergency department until the surgical team diagnoses the patient. TTS is the time elapsed between diagnosis and surgical intervention (it does not reflect the time from presentation to treatment). The Sequential Organ Failure Assessment (SOFA) score is a clinical tool used to assess the extent of a patient’s organ dysfunction and predict the risk of severe sepsis and mortality. For instance, during an intensive care unit stay, the estimated risk of mortality may reach 25% for a maximum SOFA score of 0–9 and 40–60% for a score of 10–14 [31]. It is calculated using parameters such as the ratio of partial pressure arterial oxygen and a fraction of inspired oxygen (PaO2/FiO2), platelets count, bilirubin level, Glasgow coma score, mean arterial pressure, use of vasopressors, creatinine level, and urine output [32, 33]. The LRINEC score is a diagnostic scoring tool developed to help differentiate necrotizing fasciitis from other soft tissue infections, such as cellulitis. It uses a set of laboratory values to assess the likelihood of NF as well as the prognosis [10]. LRINEC score ≥ 6 was associated with a risk of sepsis and mortality. At presentation, it was calculated using laboratory results of six variables: C-reactive protein, white blood cell count, hemoglobin, sodium level, creatinine, and glucose.
Statistical analysis
This study did not require pre-set sample size calculation as we intended to include all the hospitalized cases of NF over a specific period. Data were presented as counts (percentages), mean (standard deviation), or medians (interquartile range) whenever appropriate. Patients were classified and compared based on TTD and TTS. The chi-square test was performed to compare categorical variables in two groups, whereas the Student-t test was used for continuous variables. Mann–Whitney U-test was used for non-parametric data whenever applicable. A two-tailed p-value < 0.05 was considered for statistical significance. Data analysis was carried out using the Statistical Package for Social Sciences version 21 (SPSS Inc., Chicago, IL).
Results
Demographics and predisposing factors
One hundred twenty-one (121) cases of NF were included in the study. There were 109 males (90.1%) and 12 females (9.9%) with a mean age of 49.4 ± 12.9 years.
The most common comorbidity associated with NF was DM, found in 75 patients (62%), and hypertension was the second in 43 patients (35.5%). Also, chronic kidney disease and coronary artery disease were found in 25 (20.7%) and 24 (19.8%), respectively. Eleven of the patients (9.1%) had recent surgery in the last two months before illness, and 8 (6.6%) had trauma, either blunt or penetrating. One patient developed NF after an insect bite and one after an Intramuscular injection (0.8%). Table 1 summarizes demographics and the clinical findings. Of the 121 patients reported, 109 (90.1%) survived and 12 (9.9%) died. Sixty-five (65) patients (53.7%) were admitted to the ICU, including all the deceased (12 patients). The median LOS ranged between 14 and 46 days, averaging 26 days.
Table 1.
Demographic, medical history, infection sites, clinical features and hospital course of patients with necrotizing fasciitis (N = 121)
| Mean Age | 49.4 ± 12.9 |
| Male | 109 (90.1) |
| Shock Index ≥ 1 | 41 (33.9) |
| Medical History (n,%) | |
| Diabetes Mellitus | 75 (62.0) |
| Coronary Artery Disease | 24 (19.8) |
| Hypertension | 43 (35.5) |
| Chronic Kidney disease | 25 (20.7) |
| Congestive Heart Failure | 5 (4.1) |
| Recent Medical History (n,%) | |
| Recent Surgery within 2 months | 11 (9.1) |
| Liver disease | 3 (2.5) |
| Trauma | 8 (6.6) |
| Insect bite | 1 (0.8) |
| History of Intramuscular Injection | 1(0.8) |
| Distribution of Infection Site (n, %) | |
| Lower limb/thigh | 49 (40.5) |
| Perineum/Gluteus/Sacral region | 59 (48.8) |
| Abdominal/Groin | 12 (9.9) |
| Upper Limb | 7 (5.8) |
| Neck/Facial | 3 (2.5) |
| Clinical Features (n, %) | |
| Pain/Tenderness | 115 (95.0) |
| Swelling | 113 (93.4) |
| Fever | 61 (50.4) |
| Hospital Course | |
| ICU admission (n,%) | 65 (53.7) |
| Hospital LOS (days) (median, IQR) | 26 (14–46) |
| Mortality (n,%) | 12 (9.9) |
| Recurrence (n,%) | 6 (5.0) |
Distribution of infection and clinical features
The most common site of infection was the perineal, gluteal, and sacral region in 59 patients (48.8%), followed by the lower limb/thigh in 49 patients (40.5%). Twelve patients (9.9%) had an infection in the abdomen or groin, seven patients (5.8%) had an upper limb infection, and only three cases in the neck or face (2.5%). Pain/tenderness in 115 (95%), local swelling in 113 (93.4%), and fever in 61 (50.4%) were the most common clinical features at presentation.
Microbiology and cultures
Table 2 summarizes isolated microorganisms. Wound culture was positive in 114 patients (94.2%), while blood culture was positive in only 16 (13.2%). Poly-bacterial infection was isolated in 68 patients (56.2%); the rest were mono-bacterial.
Table 2.
Microbiological characteristics of necrotizing fasciitis patients (N = 121)
| Wound culture positive (n,%) | 114 (94.2) |
| Blood culture positive | 16 (13.2) |
| Fungus positive | 17 (14.1) |
| Poly-bacterial infection | 68 (56.2) |
| Gram-positive bacteria | 84 (69.4) |
| Gram-negative bacteria | 37 (30.6) |
| Both Gram-positive and Gram-negative | 11 (9.1) |
| Anaerobic bacteria | 13 (10.7) |
| Streptococcus | 47 (38.8) |
| Staphylococcus | 31 (25.6) |
| Escherichia coli | 22 (18.2) |
| Pseudomonas | 21 (17.4) |
| Klebsiella (Kelebsiella) | 12 (9.9) |
| Aeromonas | 8 (6.6) |
| Enterococcus | 8 (6.6) |
| Clostridium | 1 (0.8) |
| Proteus | 2 (1.7) |
| Morganella | 4 (3.3) |
| Prevotella | 8 (6.6) |
The most common Gram-positive bacteria were group A Streptococcus and Staphylococcus in 47 (38.8%) and 31 (25.6%), respectively. Escherichia coli was isolated in 22 patients (18.2%), and it was the most common Gram-negative bacteria, followed by Pseudomonas in 21 patients (17.4%). Fungus in the wound was positive in 17 patients (14.1%), and four patients died.
Comparative analysis of necrotizing fasciitis by time to diagnosis
Analysis of patients with necrotizing is based on the time to diagnosis is demonstrated in Table 3. Patients diagnosed within 6 h were more likely to be male (98.1% vs. 83.8%, p = 0.02), present with perineum infections (56.6% vs. 36.8%, p = 0.047), and show evident swelling (100.0% vs. 88.2%, p = 0.02) compared to those diagnosed after 6 h. Early diagnosis was linked to higher blood glucose levels (15.91 vs. 11.26 mmol/L, p = 0.001), while delayed diagnosis was associated with higher creatinine levels (136 vs. 108 µmol/L, p = 0.01). Patients diagnosed within 6 h had a median time to treatment of 4 h, while those diagnosed after 6 h had a median time to treatment of 7 h. This difference is statistically significant (p = 0.01), indicating that earlier diagnosis is associated with quicker initiation of therapy. No significant differences between groups were found in LRINEC score ≥ 6 (11.3% vs. 7.4%, p = 0.70). On the other hand, a larger proportion of patients in the early diagnosis group had lower SOFA scores, with 83.0% scoring below 7, compared to 67.6% in the delayed diagnosis group (p = 0.02). Conversely, higher SOFA scores (above 9) were more prevalent in the delayed diagnosis group, with 30.9% of these patients scoring above 9, compared to only 11.3% in the early diagnosis group. Mortality was higher in the delayed group (13.2% vs. 5.7%, p = 0.24), though not statistically significant but clinically it is. The length of stay (LOS) was shorter in the early group (17 vs. 27.5 days, p = 0.05). ICU admission rates were similar (54.7% vs. 52.9%, p = 0.99).
Table 3.
Comparative analysis of demographic, clinical and laboratory parameters, and outcomes in patients with necrotizing fasciitis by time to diagnosis (TTD)
| TTD < 6 h. (n = 53) | TTD ≥ 6 h. (n = 68) | P-value | |
|---|---|---|---|
| Age | 47.7 ± 11.5 | 50.7 ± 13.7 | 0.199 |
| Male | 52 (98.1) | 57 (83.8) | 0.021 |
| Shock index ≥ 1 | 20 (37.7) | 21 (31.0) | 0.356 |
| Diabetes Mellitus | 35 (66.0) | 40 (58.8) | 0.387 |
| Lower limb/thigh infection | 16 (30.2) | 33 (48.5) | 0.064 |
| Perineum infection | 30 (56.6) | 25 (36.8) | 0.047 |
| Pain/Tenderness | 52 (98.1) | 63 (92.7) | 0.341 |
| Swelling | 53 (100.0) | 60 (88.2) | 0.027 |
| Fever | 28 (52.8) | 33 (48.5) | 0.775 |
| White Blood Cell count (mean ± SD) | 20.27 ± 8.48 | 20.75 ± 9.51 | 0.774 |
| Platelet count (mean ± SD) | 304.00 ± 209.36 | 277.06 ± 129.96 | 0.392 |
| Hemoglobin (mean ± SD) | 11.43 ± 2.25 | 11.09 ± 2.72 | 0.466 |
| Sodium level (mean ± SD) | 131.77 ± 5.36 | 132.48 ± 6.67 | 0.533 |
| C-Reactive Protein (mean ± SD) | 290.52 ± 140.00 | 300.61 ± 129.73 | 0.69 |
| Glucose (mean ± SD) | 15.91 ± 8.96 | 11.26 ± 6.08 | 0.001 |
| Creatinine level (median, IQR) | 108 (76–144) | 136.00 (90.00–305.00) | 0.011 |
| Total Bilirubin (median, IQR) | 13.00 (10.00–27.00) | 17.00 (10.00–30.00) | 0.31 |
| Procalcitonin (median, IQR) | 3.04 (0.48–8.07) | 4.00 (1.02–23.70) | 0.264 |
| LRINEC ≥ 6 | 6 (11.3) | 5 (7.4) | 0.707 |
| SOFA score | |||
| • < 7 | 44 (83.0) | 46 (67.6) | 0.021 |
| • 7–9 | 3 (5.7) | 1 (1.5) | |
| • > 9 | 6 (11.3) | 21 (30.9) | |
| Wound culture positive (n,%) | 51 (96.2) | 63 (92.7) | 0.657 |
| Blood culture positive | 7 (13.2) | 9 (13.2) | 0.962 |
| Fungus positive | 5 (9.4) | 12 (17.7) | 0.305 |
| Gram-positive bacteria | 38 (71.7) | 46 (67.7) | 0.779 |
| Gram-negative bacteria | 14 (26.4) | 23 (33.8) | 0.497 |
| Gram-positive and Gram-negative | 3 (5.7) | 8 (11.7) | 0.401 |
| Number of debridement (median, IQR) | 2 (1–3) | 2 (2–3) | 0.968 |
| Septic shock | 14 (26.4) | 19 (28.0) | 0.916 |
| ICU admission (n,%) | 29 (54.7) | 36 (52.9) | 0.992 |
| Hospital LOS (days) (median, IQR) | 17.00 (10.00–42.00) | 27.50 (16.00–46.00) | 0.051 |
| Mortality (n,%) | 3 (5.7) | 9 (13.2) | 0.24 |
| Time to treatment median, IQR | 4 (3–7) | 7 (4–12) | p 0.01 |
SOFA: Sequential Organ Failure Assessment; IQR: Interquartile range; LRINEC: Laboratory Risk Indicator for Necrotizing Fasciitis; LOS: Length of stay
Comparative analysis of necrotizing fasciitis by TTS
Analysis of patients with necrotizing based on the TTS is shown in Table 4. Lower limb infections were more common in the < 6 h group (52.5% vs. 34.9%, p = 0.046), whereas perineum infections were more prevalent in the ≥ 6 h group (60.0% vs. 31.2%, p = 0.003). The levels of glucose (12.85 ± 7.32 vs. 13.74 ± 8.29, p = 0.53) and creatinine (117.00 vs. 116.00, p = 0.77) did not significantly differ between early or delayed treatment. Patients treated within 6 h had a significantly shorter time to diagnosis (median of 5 h vs. 8 h, p = 0.02). A high LRINEC score (≥ 6) was observed in both groups at comparable rates, 82.0% versus 85.0%, with p = 0.69. Patients who received treatment within 6 h had lower SOFA scores overall, with 81.7% of these patients scoring below 7, compared to 67.2% in the delayed treatment group (p = 0.04). In contrast, a significantly higher proportion of patients in the delayed treatment group had SOFA scores above 9 (31.1% vs. 13.3%, p = 0.04). ICU admission (55.7% vs. 51.7%, p = 0.96), LOS (33.00 vs. 21.50 days, p = 0.10), and mortality rates (11.5% vs. 8.3%, p = 0.99) were comparable between the two groups.
Table 4.
Comparative analysis of demographic, clinical and laboratory parameters, and outcomes in patients with necrotizing fasciitis by time to treatment (TTS)
| TTS < 6 h. (n = 60) | TTS ≥ 6 h. (n = 61) | P-value | |
|---|---|---|---|
| Age | 50.2 ± 14.2 | 48.6 ± 11.3 | 0.515 |
| Male | 52 (85.3) | 57 (95.0) | 0.136 |
| Shock index ≥ 1 | 16 (26.2) | 17 (28.3) | 0.405 |
| Diabetes Mellitus | 40 (65.6) | 35 (58.3) | 0.527 |
| Hypertension | 23 (37.1) | 20 (33.9) | 0.713 |
| cardiovascular disease | 15 (24.3) | 14 (21.8) | 0.892 |
| Chronic Kidney Disease | 14 (22.6) | 11 (18.6) | 0.593 |
| Lower limb/thigh infection | 32 (52.5) | 21 (34.9) | 0.046 |
| Perineum infection | 19 (31.2) | 36 (60.0) | 0.003 |
| Pain/Tenderness | 56 (91.8) | 59 (98.3) | 0.217 |
| Swelling | 54 (88.5) | 59 (98.3) | 0.071 |
| Fever | 31 (50.8) | 30 (50.0) | 0.802 |
| White Blood Cell count (mean ± SD) | 20.88 ± 8.89 | 20.19 ± 9.25 | 0.676 |
| Platelet count (mean ± SD) | 301.45 ± 211.04 | 276.46 ± 113.88 | 0.424 |
| Hemoglobin (mean ± SD) | 11.06 ± 2.89 | 11.42 ± 2.09 | 0.437 |
| Sodium level (mean ± SD) | 132.75 ± 6.28 | 131.56 ± 5.92 | 0.286 |
| C-Reactive Protein (mean ± SD) | 288.57 ± 142.30 | 303.84 ± 125.52 | 0.543 |
| Glucose (mean ± SD) | 12.85 ± 7.32 | 13.74 ± 8.29 | 0.535 |
| Creatinine level (median, IQR) | 117 (77–239) | 116 (90–190) | 0.779 |
| Total Bilirubin (median, IQR) | 16.50 (11.00–27.75) | 13 (10–29.75) | 0.749 |
| Procalcitonin (median, IQR) | 2.41 (0.58–15.50) | 4.77 (1.02–15.80) | 0.352 |
| Time to diagnosis: median, IQR | 5 (2–10) | 8 (5–12) | 0.02 |
| LRINEC ≥ 6 | 50 (82.0) | 51 (85.0) | 0.691 |
| SOFA score | |||
| • < 7 | 49 (81.7) | 41 (67.2) | 0.04 |
| • 7–9 | 3 (5.0) | 1 (1.6) | |
| • > 9 | 8 (13.3) | 19 (31.1) | |
| Wound culture positive (n,%) | 57 (93.4) | 57 (95.0) | 0.995 |
| Blood culture positive | 8 (13.1) | 8 (13.3) | 0.995 |
| Fungus positive | 8 (13.1) | 9 (15.0) | 0.81 |
| Gram-positive bacteria | 43 (70.5) | 41 (68.3) | 0.995 |
| Gram-negative bacteria | 21 (34.4) | 16 (26.7) | 0.274 |
| Gram-positive and Gram-negative | 8 (13.1) | 3 (5.0) | 0.283 |
| Number of debridement (median, IQR) | 2.00 (1.00–4.00) | 2.00 (2.00–3.00) | 0.765 |
| Septic shock | 16 (26.2) | 17 (28.3) | 0.706 |
| ICU admission (n,%) | 34 (55.7) | 31 (51.7) | 0.964 |
| Hospital LOS (days) (median, IQR) | 33.00 (16.00–46.00) | 21.50 (11.00–42.75) | 0.107 |
| Mortality (n,%) | 7 (11.5) | 5 (8.3) | 0.995 |
SOFA: Sequential Organ Failure Assessment; IQR: Interquartile range; LRINEC: Laboratory Risk Indicator for Necrotizing Fasciitis; LOS: Length of stay
Severity and mortality based on time to diagnosis in association with TTS
Table 5 highlights the relationship between TTD, TTS, and patient outcomes. The entirely delayed group (TTD > 6 h & TTS > 6 h) had the poorest outcomes, with 39% of patients presenting with a SOFA score > 9, 79% with a LRINEC score > 6, and a hospital mortality rate of 13.2%. The delayed diagnosis with the early treatment group (TTD > 6 h & TTS < 6 h) showed slightly lower severity, with 20% having SOFA > 9 and 70% an LRINEC score > 6, yet had a similar mortality rate of 13.3%. These findings highlight that early treatment alone does not compensate for the impact of delayed diagnosis on mortality.
Table 5.
Severity of NF and mortality based on time to diagnose in association with time to treat
| TTD < 6 h&TTS < 6 h | TTD < 6 h&TTS > 6 h | TTD > 6 h&TTS < 6 h | TTD > 6 h&TTS > 6 h | |
|---|---|---|---|---|
| Number of patients | 30 (24.8%) | 23 (19%) | 30 (24.8%) | 38 (31.4%) |
| SOFA > 9 | 7% | 17% | 20% | 39% |
| LRINEK > 6 | 90% | 70% | 70% | 79% |
| Hospital mortality | 3% | 8.7% | 13.3% | 13.2% |
TTD: time to diagnose, TTS: time to surgical treat
In contrast, the group with early diagnosis and treatment (TTD < 6 h & TTS < 6 h) demonstrated SOFA > 9 in 7% and 3% mortality rate. The early diagnosis but delayed treatment group (TTD < 6 h & TTS > 6 h) exhibited intermediate outcomes, with 17% having SOFA > 9 and a mortality rate of 8.7%.
NF over the years
The incidence of NF fluctuated slightly over the years. Supplementary file 1 shows the frequency and deaths of necrotizing fasciitis by year (2016–2022). In 2016, 11 NF cases were reported with 2 fatalities, while in 2018, 27 NF cases were reported with no mortality.
Discussion
NF is a surgical emergency with high morbidity and mortality rates that pose significant challenges in diagnosis and treatment. This study presents the clinical, laboratory, and microbiological characteristics and outcomes of 121 patients diagnosed and hospitalized with NF over six years in a rapidly developing Middle Eastern country. The study’s outcome was based on the time to diagnosis and the time to surgical intervention.
In existing medical literature, it has been noted that NF can develop at any age, although it is most reported in individuals between the ages of 32 and 57, with the average age observed in the current study being 49 years [34, 35]. The areas of the body most frequently affected by NF include the extremities, perineum, head & neck, and truncal regions, with the perineum and lower limbs being the most infected sites in the current study [36].
Symptoms typically associated with NF, such as pain, tender local swelling, and fever, were commonly observed in the current group, consistent with earlier reports [19, 37]. Moreover, the frequent co-morbidities related to NF encompass diabetes mellitus, malignancy, chronic cardiac disease, peripheral vascular disease, chronic renal disease, and immune suppression [7]. Notably, among these co-morbidities, diabetes mellitus, hypertension, and renal impairment were the most encountered in the current study group.
Previous studies on NF have addressed a variety of potential predictive factors. El-Menyar et al. [10] included 294 NF patients and focused on the utility of LRINEC scores, dividing patients into those with scores < 6 and ≥ 6. Age and LRINEC scores were significantly associated with mortality and septic shock in univariable analyses. However, the time from presentation and diagnosis to surgery is the most important modifiable element in the outcomes of patients with NF [11, 12]. Most studies focused on the impact of time to surgery or time to intervention on the outcome of NF patients. However, published reports remain inconsistent about which time cut-off for surgical intervention is a significant independent predictor. Two meta-analyses by Gelbard et al. and Nawjin et al. [38, 39] found that time to surgery was associated with decreased mortality “if” surgery was done within 12 h of presentation. Nawjin et al. described the 12-hour golden period as the “minimal” golden period for intervention but recommended an earlier 6-hour period. Our study and others [12, 15, 16, 40] have failed to find time for surgery to be significant in multivariable modeling to define the predictors of mortality. We believe that the time spent in the emergency room before diagnosis (TTD) is crucial, impacts the outcome, and goes side by side with time to treatment. Initially, we studied the impact of early versus late diagnosis and early versus late treatment on the outcomes of NF, including ICU admission, mortality, and length of stay (LOS). We found that early diagnosis (within 6 h) was associated with better outcomes, including lower mortality rates (3% vs. 13.2%) and shorter LOS (17 days vs. 27 days), compared to delayed diagnosis. In terms of time to treatment, for those who received treatment within 6 h, the outcomes were worse, which suggests that early diagnosis may play a more critical role in improving outcomes than early treatment alone. When examining the combined effect of TTD and TTS, we found that the group with both early diagnosis and early treatment (TTD < 6 h & TTS < 6 h) had the best outcomes, with only 7% presenting with a SOFA score > 9 and a 3% mortality rate. In contrast, among groups with delayed diagnosis (TTD > 6 h), mortality rates were similar regardless of whether treatment was early or late, with 13.3% in the early treatment group (TTD > 6 h & TTS < 6 h) and 13.2% in the late treatment group (TTD > 6 h & TTS > 6 h). These findings suggest that delayed diagnosis significantly impacts mortality outcomes. Notably, the SOFA score, an established predictor of mortality in NF [6, 18], demonstrated a clear relationship with delays in diagnosis and treatment. The percentage of patients with SOFA scores > 9 increased progressively across groups, ranging from 7% in the early diagnosis and treatment group to 39% in the group with both delayed diagnosis and treatment (TTD > 6 h & TTS > 6 h). This underscores the critical impact of delayed diagnosis on the severity of organ dysfunction, which directly correlates with increased mortality. Thus, the critical factors may be the time to surgery, the time to diagnosis, and the time to decide to perform surgery. We also believe that better outcomes observed in patients with early diagnosis may be attributed to timely identification and NF-directed resuscitation, including appropriate antibiotics and aggressive fluid management. A study by Tsai et al. [41]. emphasizes the critical role of early and appropriate antibiotic therapy in improving patient outcomes. While it may seem common sense that targeting early antimicrobial administration may also impact the outcome, we couldn’t show this in our study as it needs more precise information about the type of antibiotics used and the timing, and this is one of the limitations.
The period spent in the ER before the patient is labeled as NF is the golden period with a cut-off of 6 h. This constituted the effect of resuscitation done in the ER before surgery. Sometimes, stabilizing the hemodynamic status of a patient with severe NF preoperatively takes more time, and thus, it delays the on-time definitive treatment and negatively impacts the patient’s outcome [42]. In the current study, earlier diagnosis showed better outcomes in terms of mortality (5.7% vs. 13.2%) and LOS (17 vs. 27 days) in the earlier group. Thus, time to diagnosis is of the essence.
The limitations of the present study included the retrospective design, small sample size, single-center data, and lack of reasons for diagnosis delay. However, several issues frequently impede the clinical application of the intended early diagnosis and debridement. Patient delay is a problem that medical personnel cannot easily influence. Many clinical, financial, and social factors affect how long a patient waits to seek medical attention [43]. So, delay in presentation may also have an impact, which we didn’t include in our study, and this is another limitation. Next, hospital delays and poor experiences with NF due to its low incidence may delay or even misdiagnose NF with other soft tissue infections. Moreover, the improved outcomes in patients with early diagnosis can be attributed to timely surgical intervention and the implementation of NF-directed resuscitation measures, including appropriate antimicrobial therapy and aggressive fluid management. These findings stress the importance of optimizing emergency room protocols to prioritize early recognition and stabilization of patients suspected of having NF.
Though we could not elaborate on the impact of time to surgery on clinical outcomes, we believe this should continue to be examined in future studies with multicenter collaboration aiming for a bigger sample and power to explore the impact of time on the clinical outcome of this important and serious disease. Therefore, enhancing diagnostic protocols and training to achieve earlier diagnosis should be a primary focus in the clinical management of this life-threatening condition. Further research is needed to explore strategies for reducing diagnostic delays and to confirm these findings in larger patient cohorts. Although its retrospective design and single-center scope limit this study, it introduces the concept of “time to diagnosis” as an independent predictor of outcomes, which warrants further exploration. The study may have inadequate power in post hoc analysis because of the limited sample size. Therefore, the findings need further investigation in a larger population. This will also allow for conducting robust multivariate logistic regression analysis to assess the independent predictors of the study outcomes. Future research with larger, multicenter cohorts is essential to validate these findings, refine diagnostic protocols, and develop strategies to minimize delays in both diagnosis and treatment. By addressing these challenges, we can improve survival rates and reduce the morbidity associated with necrotizing fasciitis. Lastly, this study has gender-biased findings as most cases are males. However, previous work from the same group reported a higher percentage of males with NF in Qatar with a male-to-female ratio of 3:1 [5]. The influx of male laborers (80% of the population in Qatar are expatriates with a South Asian predominance) has skewed the gender balance, and women represent just one-quarter of the population.
Conclusion
This study highlights the critical importance of timely diagnosis in improving outcomes for patients with necrotizing fasciitis. Early diagnosis, defined as within six hours of presentation, was associated with significantly lower mortality rates and shorter hospital stay, emphasizing its pivotal role in managing this life-threatening condition. While early surgical intervention is often emphasized, our findings suggest that the time to diagnosis and subsequent resuscitation efforts may have a greater impact on patient outcomes. The strong correlation between delayed diagnosis and higher SOFA scores further underscores the role of early and accurate diagnosis in mitigating disease severity and reducing mortality.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
The authors thank the Medical Research, HMC, Doha, Qatar.
Author contributions
All authors contributed to the study design, the analysis and interpretation of data, and manuscript writing and approved the final manuscript, AE supervised and edited the manuscript.
Funding
Open Access funding provided by the Qatar National Library.
None.
Data availability
All data are presented in the manuscript, further access needs approval from the medical research center at Hamad medical corporation, after reasonable research request and signed data share agreement.
Declarations
Ethics approval and consent to participate
Ethical approval was obtained from the institutional review board (MRC-01-23-531) at the Medical Research Center, Hamad Medical Corporation (HMC), Doha, Qatar. Data were collected retrospectively and anonymously with no direct contact with the patients; therefore, a waiver of consent was granted.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
This study will be presented partly at the ECTES: 24th European Congress of Trauma and Emergency Surgery; 13–15 April 2025, Aachen, Germany.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Puvanendran R, Huey JC, Pasupathy S. Necrotizing fasciitis. Can Fam Physician. 2009;55(10):981–7. [PMC free article] [PubMed] [Google Scholar]
- 2.Fontes RA Jr, Ogilvie CM, Miclau T. Necrotizing soft-tissue infections. J Am Acad Orthop Surg. 2000 May-Jun;8(3):151–8. 10.5435/00124635-200005000-00002. [DOI] [PubMed]
- 3.Abbate A, Almasio PL, Mongitore M, Di Vita G, Patti R. Necrotizing soft tissue fasciitis after intramuscular injection. Case Rep Surg. 2018;2018:3945497. 10.1155/2018/3945497. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Chen LL, Fasolka B, Treacy C. Necrotizing fasciitis: A comprehensive review. Nursing. 2020;50(9):34–40. 10.1097/01.NURSE.0000694752.85118.62. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Shaikh N, El-Menyar A, Mudali IN, Tabeb A, Al-Thani H. Clinical presentations and outcomes of necrotizing fasciitis in males and females over a 13-year period. Ann Med Surg (Lond). 2015;4(4):355–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Jabbour G, El-Menyar A, Peralta R, Shaikh N, Abdelrahman H, Mudali IN, Ellabib M, Al-Thani H. Pattern and predictors of mortality in necrotizing fasciitis patients in a single tertiary hospital. World J Emerg Surg. 2016;11:40. 10.1186/s13017-016-0097-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Goh T, Goh LG, Ang CH, Wong CH. Early diagnosis of necrotizing fasciitis. Br JSurg. 2014;101:e119–25. 10.1002/bjs.937. [DOI] [PubMed] [Google Scholar]
- 8.Al-Thani H, El-Menyar A, Shaikh N, Mudali IN, Mekkodathil A, Asim M, Gameil A, Tabeb A. Risk stratification of necrotizing fasciitis based on the initial procalcitonin concentration: A single center observational study. Surg Infect (Larchmt). 2015;16(6):806–12. [DOI] [PubMed] [Google Scholar]
- 9.Fernando SM, et al. Necrotizing soft tissue infection: diagnostic accuracy of physical examination, imaging, and LRINEC score: A systematic review and Meta-Analysis. Annals Surg Vol. 2019;269(1):58–65. 10.1097/SLA.0000000000002774. [DOI] [PubMed] [Google Scholar]
- 10.El-Menyar A, Asim M, Mudali IN, Mekkodathil A, Latifi R, Al Thani H. The laboratory risk indicator for necrotizing fasciitis (LRINEC) scoring: the diagnostic and potential prognostic role. Scand J Trauma Resusc Emerg Med. 2017;25(1):28. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Latifi R, Patel AS, Samson DJ, Tilley EH, Gashi S, Bergamaschi R, El-Menyar A. The roles of early surgery and comorbid conditions on outcomes of severe necrotizing soft-tissue infections. Eur J Trauma Emerg Surg. 2019;45(5):919–26. 10.1007/s00068-018-0958-z. [DOI] [PubMed] [Google Scholar]
- 12.Hadeed GJ, Smith J, O’Keeffe T, et al. Early surgical intervention and its impact on patients presenting with necrotizing soft tissue infections: a single academic center experience. J Emerg Trauma Shock. 2016;9(1):22–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Holena DN, Mills AM, Carr BG, et al. Transfer status: a risk factor for mortality in patients with necrotizing fasciitis. Surgery. 2011;150(3):363–70. [DOI] [PubMed] [Google Scholar]
- 14.Wong C-H, Chang H-C, Pasupathy S, Khin L-W, Tan J-L, Low C-O. Necrotizing fasciitis: clinical presentation, microbiology, and determinants of mortality. J Bone Jt Surg Am. 2003;85(8):1454–60. [PubMed] [Google Scholar]
- 15.Gunter OL, Guillamondegui OD, May AK, Diaz JJ. Outcome of necrotizing skin and soft tissue infections. Surg Infect. 2008;9(4):443–50. [DOI] [PubMed] [Google Scholar]
- 16.Keung EZ, Liu X, Nuzhad A, Adams C, Ashley SW, Askari R. Immunocompromised status in patients with necrotizing softtissue infection. JAMA Surg. 2013;148(5):419–26. [DOI] [PubMed] [Google Scholar]
- 17.Azmi YA, Alkaff FF, Renaldo J, Wirjopranoto S, Prasetiyanti R, Soetanto KM, Salamah S, Purba AKR, Postma MJ. Comparison of different scoring systems for predicting in-hospital mortality for patients with Fournier gangrene. World J Urol. 2023;41(10):2751–7. 10.1007/s00345-023-04552-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.MULLA ZD, GIBBS SG, ARONOFF DM. Correlates of length of stay, cost of care, and mortality among patients hospitalized for necrotizing fasciitis. Epidemiol Infect. 2007;135(5):868–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Dworkin MS, Westercamp MD, Park L, McIntyre A. The epidemiology of necrotizing fasciitis including factors associated with death and amputation. Epidemiol Infect. 2009;137:1609–14. [DOI] [PubMed] [Google Scholar]
- 20.Anaya DA, Bulger EM, Kwon YS, Kao LS, Evans H, Nathens AB. Predicting death in necrotizing soft tissue infections: a clinical score. Surg Infect. 2009;10(6):517–22. [DOI] [PubMed] [Google Scholar]
- 21.Mekkodathil A, El-Menyar A, Natesa Mudali I, Al-Sulaiti M, Shaikh N, Al-Thani H. Temporal and seasonal trends of hospitalization and mortality associated with necrotizing fasciitis: A retrospective study of 12 years (2002–2013). Qatar Med J. 2020;2020(3):37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Kao LS, Knight MT, Lally KP, Mercer DW. The impact of diabetes in patients with necrotizing soft tissue infections. Surg Infect (Larchmt). 2005 Winter;6(4):427–38. 10.1089/sur.2005.6.427. [DOI] [PubMed]
- 23.Frazee BW, Fee C, Lynn J, et al. Community-acquired necrotizing soft tissue infections: a review of 122 cases presenting to a single emergency department over 12 years. J Emerg Med. 2008;34(2):139–46. [DOI] [PubMed] [Google Scholar]
- 24.Huang K-F, Hung M-H, Lin Y-S, et al. Independent predictors of mortality for necrotizing fasciitis: a retrospective analysis in a single institution. J Trauma. 2011;71(2):467–73. [DOI] [PubMed] [Google Scholar]
- 25.Kao LS, Lew DF, Arab SN, et al. Local variations in the epidemiology, microbiology, and outcome of necrotizing soft-tissue infections: a multicenter study. Am J Surg. 2011;202(2):139–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Megas IF, Delavari S, Marti Edo A, Habild G, Billner M, Reichert B, Breidung D. Prognostic factors in necrotizing fasciitis: insights from a Two-Decade, Two-Center study involving 209 cases. Infect Dis Rep. 2024;16(3):472–80. 10.3390/idr16030035. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Abdalla TSA, Grotelüschen R, Abdalla ASA, Melling N, Izbicki JR, Bachmann K. Prognostic factors for intraoperative detection of necrotizing fasciitis in severe soft tissue infections. PLoS ONE. 2023;18(5):e0285048. 10.1371/journal.pone.0285048. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Andreasen TJ, Green SD, Childers BJ. Massive infectious soft-tissue injury: diagnosis and management of necrotizing fasciitis and purpura fulminans. Plast Reconstr Surg. 2001;107(4):1025–35. [DOI] [PubMed] [Google Scholar]
- 29.Allaw F, Wehbe S, Kanj SS. Necrotizing fasciitis: an update on epidemiology, diagnostic methods, and treatment. Curr Opin Infect Dis. 2024;37(2):105–11. [DOI] [PubMed] [Google Scholar]
- 30.Solomon IH, Borscheid R, Laga AC, Askari R, Granter SR. Frozen sections are unreliable for the diagnosis of necrotizing soft tissue infections. Mod Pathol. 2018;31(4):546–52. [DOI] [PubMed] [Google Scholar]
- 31.Reducing bacterial resistance with IMPACT– Interhospital Multi-disciplinary Program on Antimicrobial Chemotherapy. https://impact.chp.gov.hk/calculator_9_2.php. Accessed 30 January 2025.
- 32.Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, Reinhart CK, Suter PM, Thijs LG. The SOFA (Sepsis-related organ failure Assessment) score to describe organ dysfunction/failure. On behalf of the working group on Sepsis-Related problems of the European society of intensive care medicine. Intensive Care Med. 1996;22(7):707–10. [DOI] [PubMed] [Google Scholar]
- 33.Do SN, Dao CX, Nguyen TA, Nguyen MH, Pham DT, Nguyen NT, et al. Sequential organ failure assessment (SOFA) score for predicting mortality in patients with sepsis in Vietnamese intensive care units: a multicentre, cross-sectional study. BMJ Open. 2023;13(3):e064870. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.McHenry CR, Piotrowski JJ, Malangoni MA. Determinants of mortality for necrotizing soft tissue infection. Ann Surg. 1995;221:558–65. 10.1097/00000658-199505000-00013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Lille ST, Sato TT, Engrav LH, Foy H, Jurkovich GJ. Necrotizing soft tissue infections: Obstacles in diagnosis. J Am CollSurg. 1996;182:7–11. [PubMed] [Google Scholar]
- 36.Hasham S, Matteucci P, Stanley PR, Hart NB. Necrotizing fasciitis. BMJ. 2005;330:830–3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Wang JM, Lim HK. Necrotizing fasciitis: eight-year experience and literature review. Braz J Infect Dis. 2014;18:137–43. 10.1016/j.bjid.2013.08.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Gelbard RB, Ferrada P, Yeh DD, Williams BH, Loor M, Yon J, et al. Optimal timing of initial debridement for necrotizing soft tissue infection: a practice management guideline from the Eastern association for the surgery of trauma. J Trauma Acute Care Surg. 2018;85(1):208–14. [DOI] [PubMed] [Google Scholar]
- 39.Nawijn F, Smeeing DPJ, Houwert RM, Leenen LPH, Hietbrink F. Time is of the essence when treating necrotizing soft tissue infections: a systematic review and meta-analysis. World J Emerg Surg. 2020;15:4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Golger, Alexander MD, Ching, Shim MD, Goldsmith CH, Ph D, Pennie RAMD, Bain JR. M.D. Mortality in patients with necrotizing fasciitis. Plast Reconstr Surg 119(6):p 1803–7. [DOI] [PubMed]
- 41.Tsai YH, Huang TY, Chen JL, Hsiao CT, Kuo LT, Huang KC. Bacteriology and mortality of necrotizing fasciitis in a tertiary coastal hospital with comparing risk indicators of methicillin-resistant Staphylococcus aureus and Vibrio vulnificus infections: a prospective study. BMC Infect Dis. 2021;21(1):771. 10.1186/s12879-021-06518-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Childers BJ, Potyondy LD, Nachreiner R, et al. Necrotizing fasciitis: a fourteen-year retrospective study of 163 consecutive patients. Am Surg. 2002;68(2):109–16. [PubMed] [Google Scholar]
- 43.Rucker DW, Brennan TA, Burstin HR. Delay in seeking emergency care. Acad Emerg Med. 2001;8(2):163–9. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data are presented in the manuscript, further access needs approval from the medical research center at Hamad medical corporation, after reasonable research request and signed data share agreement.