Burn assessment, severity scoring, and depth diagnosis

Overview

Assessment is the gating step of acute burn care. Burn size estimation is a crucial component of acute burn management that guides referral to burn centers, fluid resuscitation parameters, hospital resource distribution, and mortality-based interventions ^[1]. Accurate assessment of burn depth and healing potential is essential to treatment decision-making and to comparing treatment modalities ^[2][3]. Three measurements drive the rest of the care: total body surface area burned, burn depth, and the composite mortality risk that integrates size, depth, age, and inhalation injury. None of the three is straightforward in practice.

The clinical reality is that all three measurements are observer-dependent and improve with serial reassessment. Early clinical assessment of burn depth and associated healing potential remains extremely challenging, even for experienced surgeons ^[13]. The accuracy ceiling of unaided clinical depth assessment, and whether it reflects an intrinsic limit or a closable training gap, is taken up below in the Controversies section. Rule of Nines estimation shows systematic errors that overestimate the contribution of the head and arms while underestimating the trunk and legs across BMI groups, and these errors are magnified as BMI increases ^[4]. Severity scoring layered on top of these noisy inputs inherits their noise.

The literature has moved in two directions. First, digital and three-dimensional tools (smartphone applications, 3D stereophotogrammetry, computer-aided programs, and machine-learning models) show consistent accuracy and inter-rater reliability advantages over paper methods in head-to-head comparison ^[8][9]. Second, reliable and valid assessment of burn wound depth or healing potential remains essential to treatment decision-making and to comparing studies that evaluate different treatment modalities, and accurate burn depth assessment is critical for determining appropriate treatment and optimizing patient outcomes ^[3][2]. The composite mortality scores (ABSI, Baux, revised Baux, FLAMES) translate the three primary inputs into a single number that supports triage and prognostic counseling, with the caveats that any score is only as good as the inputs and that no single score wins on every patient subgroup ^[30][31][32].

Epidemiology

The patient population for burn assessment is broad. In a 30-year Tokyo Burn Unit Association cohort of 1092 pediatric home-burn patients, flame burns decreased from 7.7% to 1.6% and burn area decreased from a median of 10% to 7% TBSA, with in-hospital mortality at 0.4-0.5% in the last decade ^[45]. Adult burns concentrate in working-age and elderly populations, with assessment difficulty increasing at extremes of age. The dataset used to derive any mortality score reflects its source population, which is one of the reasons no single model generalizes perfectly across all burn centers and all geographies.

Pathophysiology

The biological basis of burn depth is the depth of thermal injury into the dermis and subcutaneous tissue, with three concentric zones described by Jackson: a central zone of coagulation that is irreversibly damaged, a surrounding zone of stasis with reduced perfusion that is potentially salvageable, and an outer zone of hyperemia with increased perfusion that recovers. In a thermal-injury model using fibre-optic confocal imaging combined with laser Doppler flowmetry, the zone of stasis showed an initial reduction in blood flux and confocal imaging of the area indicated significant vessel leakage during the first 2 hours which later improved ^[42]. The zone of hyperaemia showed an initial increase in total blood flux and confocal imaging of the area showed initial blood vessel dilatation ^[42]. Findings from comparative depth-assessment studies report that day-3 and day-5 measurements outperform day-0 measurements; LDI accuracy was significantly higher than clinical accuracy on days 3 and 5 in 40 patients with intermediate-depth burns ^[18].

The visible epidermal and dermal architecture is the basis for in vivo confocal-laser-scanning microscopy differentiation. In vivo confocal-laser-scanning microscopy can differentiate superficial-partial versus deep-partial thickness burns on a histomorphological level ^[43]. The granular-layer in partial thickness burns was destroyed in observed wounds ^[43].

Classification

Burn depth is classified by the dermal layer involved: superficial (epidermis only), superficial partial-thickness (epidermis plus superficial dermis), deep partial-thickness (epidermis plus deep dermis), and full-thickness (epidermis, full dermis, and possibly subcutaneous tissue). The distinction between superficial and deep partial-thickness burns is the surgically decisive one, because deep partial-thickness wounds typically require excision and grafting whereas superficial partial-thickness wounds re-epithelialize.

Healing-potential classification overlaps depth classification but is more clinically actionable. The laser Doppler imager classifies burns into three estimated healing potentials as follows: high, less than 14 days; intermediate, 14-21 days; and low, more than 21 days ^[19]. Wounds with low healing potential (those not expected to heal within 21 days) are the operative candidates. This three-tier scheme aligns better with surgical decision-making than the four-tier depth scheme because it directly answers the operative question.

Severity classification at the patient level integrates burn extent (TBSA), depth (full-thickness component), age, and presence of inhalation injury. The Abbreviated Burn Severity Index assigns weighted points across five components (age, sex, inhalation injury, full-thickness burn presence, and TBSA) to produce a single survival probability. The modified Baux score sums age plus percent TBSA plus 17 points for inhalation injury ^[34]. The FLAMES model exhibited the largest AUC (0.875), followed by Zhou et al. (0.853) and the ABSI model (0.802) ^[32].

Assessment

TBSA estimation methods

Three traditional methods dominate clinical TBSA estimation, with digital and 3D tools moving into routine use at well-resourced centers. The Rule of Nines and the Lund-Browder chart are commonly used to calculate the BSA involved ^[4]. Significant errors were found when comparing all groups with the Rule of Nines, which overestimated the contribution of the head and arms to the TBSA while underestimating the trunk and legs for all BMI groups ^[4]. The Lund-Browder chart subdivides the body into smaller regions and adjusts head and lower-extremity proportions for age, which is the design rationale for its standard use in pediatric burns. Improper use of TBSA estimation tools (palm, hand, Rule of 9s) without considering patient body mass index, race, age, and sex standards contributes to TBSA misestimation ^[1]. Current modalities used to determine BSA burned are subject to significant errors, which are magnified as BMI increases ^[4]. The accuracy of determining initial fluid rate has been shown to be low when the Parkland formula and Rule of Nines are applied from memory ^[6]. No statistical difference was demonstrated between serial halving and the Rule of Nines as an initial assessment tool when determining disposal ^[10].

Digital and 3D tools show consistent accuracy and reliability advantages over paper methods. The Mersey Burns App can facilitate quicker and more accurate calculations than Lund and Browder charts in studied populations ^[7]. A 2026 systematic review of 36 studies of emerging technologies grouped tools into 3D programs, mobile applications, 3D stereophotogrammetry, and machine learning models; 3D stereophotogrammetry showed the highest accuracy (mean ICC 0.988) and excellent inter-rater reliability (ICC 0.989) ^[8]. Mobile applications improved accuracy and consistency, particularly among non-specialists, and offered practical benefits in prehospital settings ^[8]. A 2026 systematic review of digital tools against an established standard found that digital tools demonstrated superior accuracy over traditional methods (mean error: digital -5.47% to +4%; traditional -0.47% to +19.7%), with EasyTBSA achieving the closest agreement to the established reference (-0.01 ± 3.59%) compared with Lund and Browder (4.42 ± 5.52%), Rule of Palms (3.92 ± 10.71%), and Rule of Nines (5.05 ± 6.87%) ^[9]. The methods detail at the subtopic page TBSA estimation methods covers the underlying body-habitus correction work and head-to-head comparisons.

Depth-diagnosis modalities

Clinical examination remains the most consistent standard of practice for partial-thickness burn depth despite its accuracy ceiling of 67% ^[11]. Adjunct imaging modalities (laser Doppler imaging, thermography, optical coherence tomography, spectral imaging, and AI-guided image assessment) exist to push that ceiling.

Laser Doppler imaging (LDI) is the best-validated adjunct. LDI produces a colour-coded image of dermal blood flow, which can be used to quantify the inflammatory response in a burn ^[14]. The conventional LDI imager scans up to 2500 cm² within 2 minutes; a faster Laser Doppler Line Scanner (LDLS) scans 300 cm² in 4 seconds with accuracy comparable to the original LDI imager (94.2% versus 94.4%) ^[15]. In meta-analysis, the overall pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of the included studies on LDI in diagnosing deep or superficial partial-thickness burn wound were 95%, 96%, 9.75, 0.11, and 257.93, respectively ^[17]. A separate systematic review found that LDI in burn depth assessment was identified as an accurate measurement tool in this meta-analysis, with the caveat that careful clinical assessment should be performed along with LDI in patients with deep burns ^[16]. In direct comparison with clinical assessment, LDI accuracy was significantly higher than clinical accuracy on day 3 (p<0.001) and day 5 (p=0.005); the prospective study evaluated 40 patients with intermediate-depth burns on days 0, 1, 3, 5, and 8 ^[18]. A blue-coded LDI<140 perfusion units showed very high association with non-healing at day 21 ^[14].

Thermography quantifies the residual perfusion of a burn wound by surface temperature. Initial thermographic assessment correctly predicted the outcome (whether healed or excised and grafted) in 33 of 36 burns ^[21]. A 2016 clinimetric study of 50 burns with two independent observers found thermography to be a reliable and valid technique in the assessment of burn wound healing potential, with an ICC of 0.99 expressing excellent correlation between two measurements ^[22]. Moderate evidence was found for adequate construct validity of thermography, videomicroscopy, and spatial frequency domain imaging (SFDI) in a 2019 measurement-techniques review ^[3]. In head-to-head comparison, accuracies of LDI on post-burn days 0 and 3 were 80.8% and 92.3% compared to 55.8% and 71.2% for thermal imaging and 62.5% and 71.6% for photographic clinical assessment ^[23].

Optical coherence tomography (OCT) is a structural imaging modality with promise for quantitative depth assessment. Polarization-sensitive optical coherence tomography (PS-OCT) is a noninvasive technique that might eventually provide the physician with a quantitative estimate of actual burn depth ^[20].

Spectral imaging including multispectral imaging and hyperspectral imaging has emerged as a promising non-invasive modality to improve burn depth evaluation ^[2]. The integration of machine learning, particularly convolutional neural networks and support vector machines, improved classification accuracy, with some models achieving over 95% sensitivity and specificity ^[2]. Spectral imaging, especially when combined with machine learning, shows strong potential as an effective tool for burn depth assessment, offering high diagnostic accuracy and reproducibility ^[2].

Photographic assessment is reliable for size in expert hands but not for depth. Using photographs, burn size could be assessed reliably and validly by experts (ICCs of 0.83 and 0.87), but not by referrers (ICCs of 0.68 and 0.78) ^[29]. Photographic assessment of burn depth was neither reliable nor valid, with ICCs respectively of 0.38 and 0.28 for experts and 0.24 and 0.13 for referrers ^[29].

Machine-learning models estimate both size and depth from images. A 2021 systematic review of 30 ML-and-burn studies found that nine studies used machine learning and automation to estimate percent TBSA burned, four calculated fluid estimations, 19 estimated burn depth, five estimated need for surgery, and two evaluated scarring ^[24]. Machine learning provides an objective adjunct that may improve diagnostic accuracy in evaluating burn wound severity ^[24]. A convolutional neural network model trained for real-time burn depth assessment achieved diagnostic accuracy of about 80% for three burn types in a multicenter dataset ^[25]. A 2026 PRISMA-DTA systematic review of AI burn-depth models across imaging modalities raised deployment-readiness concerns including possible modality-related variation and lower specificity in darker skin, with sparse and non-confirmatory subgroup evidence and pediatric evidence limited to a single within-study stratum ^[40].

Histologic biopsy remains the closest clinical reference standard. A burn biopsy algorithm based on histologic analysis has been iteratively developed and informed by the largest burn wound biopsy repository in the literature ^[26]. The biopsy approach is invasive and slow, which limits its utility as a point-of-care decision aid, but it serves as the calibration reference for imaging-modality validation work.

Inhalation-injury severity grading

When inhalation injury is suspected, bronchoscopy is the diagnostic modality of record. Using histologic findings as the gold standard, bronchoscopy proved to be sensitive (sensitivity 0.79) and highly specific (specificity 0.94) for the diagnosis of inhalation injury ^[27]. Bronchoscopic grading of inhalation injury moderately correlates with early indices of impaired gas exchange and may be a promising tool for staging lower airway injury ^[28]. Modified Baux adds 17 points for inhalation injury (age + %TBSA + 17 if present), giving confirmation and grading prognostic weight beyond respiratory management implications ^[34]. The full inhalation-injury workup is covered at a separate inhalation-injury topic page (forthcoming).

Pre-burn-center estimation and transfer

The single largest accuracy gap in burn assessment is at the pre-burn-center handoff. A meta-analysis of preburn-center care found a pooled mean absolute error in percent total body surface area burn of 6.28 (95% CI 4.72-7.85), with the average relative percent error in burn size estimation by referring providers ranging between 75% and 3500% and the ratio of overestimation to underestimation in burn size ranging between 2.2:1 and 19:1 ^[5]. From 3768 initially identified titles, 37 studies were included in that systematic review ^[5]. Inaccurate burn size estimation might lead to inaccurate fluid resuscitation and inappropriate transfer of patients to specialized burns units ^[36]. A systematic approach with telemedicine-facilitated computer-based burn assessments is required to close the pre-burn-center accuracy gap ^[1].

Management

Assessment outputs drive five immediate management decisions: airway and inhalation-injury management, initial fluid resuscitation rate, burn-center referral and transfer timing, surgical timing and approach, and prognostic counseling. This page covers the assessment-to-decision chain; the downstream management content lives at the relevant treatment-modality pages.

Referral and transfer. A regional outcomes analysis from Australia and New Zealand found that mortality risk in patients with inhalation injury increased when transfer to definitive burn care exceeded 16 hours, prompting the study's recommendation to stabilise and transfer such patients within 16 hours of burn ^[44]. Inconsistencies in TBSA estimation between referring hospitals and tertiary referral centres remain a problem in pediatric patients and may lead to inappropriate resuscitation ^[37]. Estimation of size in pediatric burns, in particular scalds, is challenging and the importance of early transfer to a specialist service cannot be overemphasized ^[38].

Initial fluid resuscitation. TBSA and weight are the two inputs to the modified Parkland formula and to ABA Consensus targets. The accuracy of determining initial fluid rate was low when the Parkland formula and Rule of Nines were applied from memory ^[6]. Using the Burn Resuscitation Index, 56% of surgeons and 77% of emergency medicine physicians were able to calculate the fluid rate correctly (P < .01 and P < .001, respectively) ^[6]. Fluid resuscitation work is covered at the fluid resuscitation in burns topic page.

Surgical timing. Depth diagnosis determines whether early excision and grafting is indicated. Wounds with low healing potential (LDI prediction of >21 days to heal) are the operative candidates ^[19]. Deep partial-thickness and full-thickness wounds require excision; the depth-assessment timing question is at which post-burn day the diagnosis becomes reliable enough to schedule operative management.

Prognostic counseling. Severity scores translate assessment inputs into mortality estimates. The revised Baux score offers a relatively easy means to quickly assess mortality risk in a broad range of patient populations ^[30]; ABSI is among the eight composite burn-mortality models meeting methodological standards in a systematic review of 45 composite scores ^[35]. Communication with families uses these scores as a starting point, with the score caveats (population calibration, performance at age extremes, and the integrated noise of TBSA and depth inputs) folded in.

Severity and mortality scoring

Severity scoring exists because no single clinical variable predicts mortality well in isolation. A systematic review of 45 composite mortality-prediction models published between 1949 and 2010 found that only 8 met published methodological standards for construction and validation: the Modified Baux Score, Abbreviated Burn Severity Index, Total Burn Surface Index, and prediction models described by Coste et al., Ryan et al., McGwin et al., Galeiras et al., and the Belgian Outcome of Burn Injury (BOBI) study group ^[35].

Revised Baux score. The original Baux score (age + percent TBSA) was extended to the modified or "revised" Baux by adding 17 points for inhalation injury ^[34]. In a 2023 systematic review and meta-analysis, the area under the curve (AUC) values of the rBaux score ranged from 0.682 to 0.99, with a summary AUC of 0.93 for all included studies (CI 0.91-0.95) ^[30]. This summary value demonstrates that the rBaux equation is a reliable predictor for mortality risk in heterogeneous populations ^[30]. The same analysis identified that the rBaux equation has a diminished ability to predict mortality risk when applied to patients at both extremes of age, highlighting an important area for future research ^[30]. The rBaux equation offers a relatively easy means to quickly assess the mortality risk from burn injury in a broad range of patient populations ^[30].

Abbreviated Burn Severity Index (ABSI). ABSI assigns weighted points across five components (age, sex, inhalation injury, full-thickness burn presence, and TBSA) and translates the sum to a survival probability. A 2025 meta-analysis demonstrated that an elevated ABSI was significantly related to an increased risk of mortality (OR 1.72, 95% CI 1.48-2.00; P < 0.001) ^[31]. The ABSI serves as a reliable prognostic indicator in severely burned patients, and patients with an elevated ABSI are at increased risk of death ^[31].

FLAMES and high-TBSA composite models. Newer composite scores target the high-TBSA subgroup, where established scores plateau. For patients with burns to ≥50% of the TBSA, the FLAMES model exhibited the largest area under the ROC curve (AUC 0.875), followed by the models of Zhou et al. (0.853) and the ABSI model (0.802) ^[32]. For patients with burns to ≥50% of the TBSA, the Zhou et al. and FLAMES models demonstrate relatively high predictive ability for mortality ^[32]. Whether FLAMES displaces ABSI in this niche depends on external validation and on workflow integration; the original score remains the most-cited clinical tool.

Generic ICU mortality models versus burn-specific models. Burn ICUs operate within general critical care infrastructure, and the relative performance of generic versus burn-specific models is a live question. The discrimination and calibration of the generic Intensive Care National Audit and Research Centre model was superior to the revised Baux and Belgian Outcome in Burn Injury burn-specific models for patients managed on burn-specialist intensive care units in a UK casemix comparison ^[33]. This finding does not displace burn-specific scores from prognostic counseling, but it suggests that ICU-level risk-adjustment work in burn populations cannot rely on burn-specific scores alone.

Complications

Assessment errors propagate into management errors. Inaccurate burn size estimation might lead to inaccurate fluid resuscitation and inappropriate transfer of patients to specialized burns units ^[36]. The relationship between overestimation and over-resuscitation is more nuanced than the simple linear assumption: in a pediatric cohort, overestimation led to overprescription of fluid volumes, but this did not translate into over-resuscitation, and in most cases was in fact associated with inadequate fluid administration ^[38]. Inconsistencies with the estimation of TBSA burn between referring hospitals and tertiary referral centers remain a problem in pediatric patients and may lead to inappropriate resuscitation ^[37].

Misdiagnosis of burn depth has its own complication signature. Underestimation of depth delays excision and grafting, prolongs the inflammatory window, and worsens scar outcome. Overestimation of depth subjects superficial partial-thickness wounds that would have healed conservatively to unnecessary excision and donor-site morbidity. Serial reassessment over the first post-burn week is the operational defense against single-time-point misdiagnosis, and adjunct imaging modalities (LDI, thermography, spectral imaging) raise the floor on day-3 to day-5 diagnostic confidence.

Special Considerations

Pediatric burns. The pediatric chest, head, and lower-extremity proportions differ from adults, which is the design rationale for the Lund-Browder chart's age-adjusted columns. Even with age adjustment, accuracy remains a problem. Burn-size estimation in children is especially challenging and needs to take into account the growing proportions and the age of a paediatric patient ^[39]. In a single-center Sydney pediatric series referred to a burn unit over one calendar year, inaccurate estimation of burn area was noted in 48 out of 61 patients (79%) ^[36]. Pediatric assessment work is detailed at the TBSA estimation methods subtopic page.

Self-inflicted burns. Suicide attempted by self-inflicted burns is associated with lower survival rates compared to accident-related burns ^[41]. In analysis using the five ABSI components as covariates, patients with self-inflicted burns showed a 6.8 percentage-point lower survival rate, suggesting that current ABSI calibration may under-call mortality in this population ^[41]. Recently proposed modifications of the ABSI score can improve the accuracy of survival rate prediction for self-inflicted burns ^[41].

Darker skin tones. Imaging-modality performance varies with skin pigmentation. A 2026 PRISMA-DTA systematic review found that exploratory descriptive analyses suggested possible modality-related variation and lower specificity in darker skin, although subgroup evidence was sparse and non-confirmatory and pediatric evidence was limited to a single within-study stratum ^[40].

Inhalation injury and combined burn-trauma. The modified Baux score adds 17 points for inhalational injury ^[34]. Bronchoscopy is the diagnostic modality of record, with sensitivity 0.79 and specificity 0.94 against histologic findings ^[27]. Combined burn-and-trauma patients have additional injury-severity considerations that interact with burn severity scoring and that will be handled at a separate inhalation-injury topic page (forthcoming).

Outcomes

The outcomes literature for burn assessment is the validation literature for the methods. For TBSA, accuracy and inter-rater reliability are the primary validation endpoints; the 2026 digital-tools systematic review reported digital-tool mean error of -5.47% to +4% versus traditional-method -0.47% to +19.7%, with inter-rater ICC 0.986-0.998 versus 0.886-0.910 ^[9]. For depth-diagnosis modalities, sensitivity and specificity against a histologic or healing-time reference standard are the primary endpoints. LDI achieves pooled sensitivity 95% and specificity 96% for partial-thickness depth diagnosis ^[17]; spectral imaging combined with machine learning reaches over 95% sensitivity and specificity in selected models ^[2]. For severity scoring, AUC against in-hospital or 28-day mortality is the primary endpoint. The revised Baux summary AUC is 0.93 across heterogeneous populations ^[30]; FLAMES achieves AUC 0.875 in the ≥50% TBSA niche ^[32]; ABSI shows OR 1.72 per unit increase against mortality in the most recent meta-analysis ^[31].

A meta-analytic synthesis of LDI evidence found pooled sensitivity and specificity were similarly high across enrolled studies and subgroups ^[16]; the same systematic review noted that the sensitivity of LDI in that meta-analysis was not as high as that identified in previous studies, which is an honest reminder that performance metrics drift across cohorts, settings, and reference standards ^[16]. The pattern across the assessment-validation literature is consistent: adjunct modalities outperform clinical examination alone, no single modality dominates every burn type and depth, and the strongest performers couple a structural or perfusion imaging signal with serial timing and clinical correlation.

Controversies and Evidence Gaps

Whether digital tools displace paper methods at the point of care. The 2026 systematic review of digital tools found measurable accuracy and reliability improvements over conventional methods, warranting consideration for broader clinical integration as digital health technologies continue to advance ^[9]. The 2026 review of emerging technologies concluded that 3D stereophotogrammetry provided more consistent and reliable estimates of TBSA while mobile applications offered practical and scalable solutions ^[8]. The signal points toward digital tools; the evidence quality remains observational and heterogeneous. Whether digital displacement is now or in the next 5-10 years remains contested.

Whether AI-guided depth assessment is ready for clinical deployment. Spectral imaging especially when combined with machine learning shows strong potential as an effective tool for burn depth assessment ^[2]. A 2026 PRISMA-DTA systematic review raised deployment-readiness concerns including possible modality-related variation and lower specificity in darker skin, with sparse and non-confirmatory subgroup evidence ^[40]. The literature is split between optimism on aggregate accuracy and caution on subgroup performance and local-validation requirements.

Which severity score wins on which patient subgroup. The revised Baux equation has a diminished ability to predict mortality risk when applied to patients at both extremes of age, highlighting an important area for future research ^[30]. FLAMES and the Zhou et al. model outperform ABSI in the ≥50% TBSA niche ^[32]. ICNARC outperforms rBaux and BOBI for general-ICU risk adjustment ^[33]. Whether a single composite "burn score" should win or whether subgroup-specific scores should coexist is unsettled.

Whether referring-hospital TBSA estimates ought to be re-calculated at the burn unit before triage decisions. The over-to-under-estimation ratio ranges between 2.2:1 and 19:1 ^[5]. A systematic approach with telemedicine-facilitated computer-based burn assessments is required ^[1]. Adoption is not standardized and varies widely by region.

Whether clinical examination of depth can be improved with structured training, or whether the accuracy ceiling demands imaging adjuncts. Clinical assessment, which assesses partial-thickness burn depth with 67% accuracy, currently remains the most consistent standard of practice ^[11]. Although clinical assessment is commonly used, its accuracy ranges only between 50% and 70% ^[12]. Early clinical assessment of burn depth and associated healing potential remains extremely challenging, even for experienced surgeons ^[13]. Whether the 67% ceiling reflects an intrinsic limit of unaided visual examination or a training gap that could be closed with structured education and feedback is not directly answered by the cited evidence base.

Whether ABSI calibration ought to be modified for self-inflicted burns. Recently proposed modifications of the ABSI score can improve the accuracy of survival rate prediction for self-inflicted burns ^[41]. Adoption of population-specific recalibrations versus a single uniform score is contested.

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