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American Journal of  Medical 
Science and Innovation (AJMSI) 

Comparative Analysis of  Granulation Tissue Formation and Progression in Elderly
Patients with Fractures

Franklin E. Ibadin1*, Trevor Efosa Edobor2, Excel Onajite Ernest-Okonofua3, Ogheneyemarho Great Oyiborhoro4

Volume 4 Issue 1, Year 2025
ISSN: 2836-8509 (Online)

DOI: https://doi.org/10.54536/ajmsi.v4i1.3945
https://journals.e-palli.com/home/index.php/ajmsi

Article Information ABSTRACT

Received: October 18, 2024
Accepted: November 25, 2024
Published: January 20, 2024

Fracture healing initiates with an inflammatory phase, followed by granulation tissue 
formation, which is necessary for angiogenesis and bone regeneration. These processes 
are complicated by the influence of  aging on cytokine and growth factor responses.  The 
study sought to quantify granulation formation between elderly versus younger patients 
and to explore the effect of  comorbidities, fracture location, and intervention type. It was 
a comparative observational study of  60 elderly patients (≥65 years old) with fractures. 
Demographic, fracture, comorbidity status, and biomarkers data (CRP, IL-6) were collected 
from the data. Paired samples t-tests, independent t-tests, and ANOVA were used to 
statistically evaluate time differences in granulation tissue formation and inflammatory 
markers. Increased granulation tissue formation was found between Day 7 and Day 30, 
although this rate fell off  between Day 14 and Day 30. Levels of  CRP were significantly 
different, suggesting an altered inflammatory response, and were intermediate between 
moderate inflammation, seen in elderly patients, and moderate inflammation, consistent 
with sepsis or septic shock. No significant difference in granulation tissue formation among 
groups indicated consistent healing and a failure of  intervention method or fracture type. 
Healing is extra delayed in elderly patients as a result of  reduced cell activity and immunity 
associated with age, and diabetes and cardiovascular diseases contribute to slowing down 
the recovery as well. The development of  specific management protocols, CRP and IL-6 
levels monitoring to track tissue healing, and vascularization and cellular function-based 
interventions that promote tissue regeneration. Supplements such as vitamin D plus calcium 
or anti-inflammatory treatments speed up healing. 

Keywords
Bone Regeneration, Comorbidities, 
Elderly Patients, Fracture Healing, 
Granulation Tissue, Inflammatory 
Markers

1 Faculty of  Health Sciences, Public Health in Epidemiology, Purdue University Global, West Lafayette, Indiana, USA
2 General Practice Vocational Training Scheme, NHS England, London, United Kingdom
3 Department of  Public Health, South Wales University, Newport, Wales, United Kingdom
4 Department of  Medicine and Surgery, Igbinedion University, Nigeria
* Corresponding author’s e-mail: franklin.ibadin@outlook.com

INTRODUCTION 
Fracture healing begins with an inflammatory phase, 
during which cytokines (IL1 and TNFα) bring in immune 
cells to remove debris and secrete essential growth factors 
for cell migration and differentiation (Baht et al., 2018). 
Next, granulation tissue, a vascular collagen-rich matrix, 
becomes a soft callus that shingles the surface, improving 
the structure and a template for bone regeneration 
(Sheen et al., 2023). However, the Shiu et al. (2018) study 
emphasized that granulation tissue is indispensable to 
angiogenesis, fibroblast proliferation, and deposition 
of  extracellular matrix (ECM), factors required for the 
ossification phase (Shiu et al., 2018). The lifetime risk of  
osteoporotic fracture is (40–50%) in women and (13–
22%) in men, with a higher mortality in men (Migliorini 
et al., 2021). The number of  new fractures globally almost 
doubled, from 133 million in 1990 to 178 million in 2019, 
representing a 33.4% rise over that time (Mitchell, 2022). 
Choy et al. (2020) research elaborated that growth and 
activity by both osteoblasts and fibroblasts are required 
to generate robust granulation tissue and are impaired 
with aging (Choy et al., 2020). However, Schlundt et al. 
(2018) study discussed that elderly patients have specific 
challenges, including reduced collagen type I synthesis, 
impaired macrophage function, and decreased VEGF 

levels, which increase infection risk and delay callus 
formation (Schlundt et al., 2018). 
A key component in wound healing is granulation tissue 
at the injury site, which comprises fibroblasts, collagen, 
capillaries, and inflammatory cells. Bridging tissue gaps, 
supporting cell migration, and providing nutrients during 
healing through a capillary network that promotes healing 
are its main functions (Soliman & Barreda, 2022). This 
is driven by cellular and molecular mechanisms, i.e., 
fibroblasts and endothelial cells proliferating in the 
setting of  growth factors: vascular endothelial growth 
factor (VEGF), platelet-derived growth factor (PDGF), 
and transforming growth factor beta (TGFβ) (Farooq et 
al., 2021). A study by Wildemann et al. (2021) highlighted 
that fracture recovery is further complicated in the aging 
population because cellular function and immunity are 
compromised and lead to increased risks of  delayed 
union, nonunion, and infection (Wildemann et al., 2021). 
Patients with osteoporosis and comorbidities (such as 
diabetes) are also commonly elderly and are predisposed 
to impaired healing and increased infection risk, as 
mentioned by (Sobh et al., 2022; Sobh et al., 2022). 
Secondary complications such as deep vein thrombosis 
and pulmonary embolism are secondary to prolonged 
immobility resulting from reduced regenerative ability 



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and a weakened immune system (Niu et al., 2022). The 
study’s main aim was to analyze granulation tissue 
formation and progress in elderly patients with fractures 
to determine age-related differences in the healing. Key 
objectives include comparing the effects of  granulation 
tissue formation between elderly and younger patients 
and how comorbidities, fracture location, and type of  
intervention influence tissue development in the elderly. 
Further, the study aims to assess pitfalls in granulation 
tissue formation that contribute to poor recovery for 
elderly fracture patients.

MATERIALS AND METHODS
Study Design
The research strategy involves a comparative observational 
study of  the formation and progression of  granulation 
tissue in elderly patients with 65 years and older fractures. 
This study collects granulation tissue formation and 
maturation data and the impact of  comorbidities, fracture 
location, and treatment interventions on the healing 
process. The observations of  natural progression without 
intervention help to determine age-related differences 
in granulating tissue formation and factors that cause 
delayed or impaired healing (Upton, 2020). Statistical 
methods provide a pattern and factors affecting the 
healing techniques in fracture, providing essential clues to 
age-related problems in fracture healing.

Inclusion and Exclusion Criteria
For this study, the inclusion criteria include elderly patients 
with fractures aged 65 years and above who can provide 
informed consent. To help ensure an understanding of  
study procedures and communications, participants 
should speak English. Those fractures studied are most 
relevant in older adults, but eligible fractures include joint 
hip, femur, wrist, or vertebral fractures. Exclusion criteria 
include patients with conditions that severely impact 
healing (e.g., advanced osteoporosis or active cancer) and 
severely impaired cognitive function (whereby consent 
or compliance are seriously affected). Therefore, the 
study selects participants with otherwise manageable 
comorbidities for accurate comparisons.

Study Population
The study population comprises 60 elderly patients (≥ 65 
years of  age) with various fractures. Patients with severe 

conditions that could disrupt healing independently, 
such as severe osteoporosis or cancer, are excluded 
from examining healing patterns for age-specific healing 
patterns. It provides a representative assessment of  
typical elderly fractures involving fracture sites and types 
of  interventions.

Data Collection
This study’s data collection included determining healing 
and control factors and considering confounding 
variables by collecting complete demographic and medical 
histories (age, gender, diabetes, and cardiovascular 
history). Fracture types and treatment details were also 
documented for comparability by older people and the 
younger groups. With X-rays (Days 7, 14, 30) and MRI, 
images allowed visual examination of  growing granulation 
tissue, and histology samples were used where available. 
Inflammation and healing were monitored by measuring 
each interval blood markers CRP, IL-6, cytokines, and 
growth factors. 

Data Analysis
For this study, the data analysis includes statistical 
comparisons between elderly and non-elderly patients to 
determine granulation tissue formation rates and rates of  
development for this population. Differences in tissue 
formation, vascularisation, and ad-healing markers were 
evaluated by paired samples, independent t-tests, and one-
way ANOVA at specific time intervals. These analyses 
help clarify the particular healing problems to which 
elderly patients are subject for targeted interventions to 
promote fracture recovery.

RESULTS AND DISCUSSION
Results
Frequency Analysis 
Gender
The findings illustrate that the gender distribution of  the 
study participants approximated a nearly equal split between 
males and females (Table 1). Among 60 total participants, 
30 (47.6%) are female, 30 (47.6%) are male. Overall 
percentages indicate that 52.4% of  the valid outcomes are 
female, and 100% of  the total is attained when the male 
participants are included, as shown in Table 1. An unbiased 
comparison of  genders for granulation tissue formation is 
possible at these levels of  balanced distribution.

Table 1: Gender
Frequency Percent Valid Percent Cumulative Percent

Valid Female 30 47.6 47.6 52.4
Male 30 47.6 47.6 100.0
Total 60 100.0 100.0

Fracture Type
Fracture types are balanced in distribution among 
the 60 participants, and each type (Femur, Humerus, 
Radius, Tibia, and Ulna) accounts for 19.0% of  the total 
sample (Table 2). This representation of  equal tissue 

affords a well-balanced examination of  granulation 
tissue formation amongst different fracture sites. The 
cumulative percentage column shows that as you add 
each fracture type, the proportion increases until it hits 
100% after In Ulna.



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Comorbidities
The distribution of  comorbidities among 60 participants 
is presented in Table 3. The most common comorbidity 
is diabetes, occurring in 24 participants (38.1%), and 
cardiovascular conditions in 13 participants (20.6%). A 
further 19 participants (30.2%) have no comorbidities, 

and a smaller portion (6.3%) have both. The cumulative 
percentages increase to 100% for those without 
comorbidities. These results point out that diabetes and 
cardiovascular diseases are widespread and can potentially 
affect granulation tissue formation in fracture healing in 
elderly patients.

Table 2: Fracture Type
Frequency Percent Valid Percent Cumulative Percent

Valid

Femur 12 19.0 19.0 23.8
Humerus 12 19.0 19.0 42.9
Radius 12 19.0 19.0 61.9
Tibia 12 19.0 19.0 81.0
Ulna 12 19.0 19.0 100.0
Total 60 100.0 100.0

Table 3: Comorbidities
Frequency Percent Valid Percent Cumulative Percent

Valid

Both 4 6.3 6.3 11.1
Cardiovascular 13 20.6 20.6 31.7
Diabetes 24 38.1 38.1 69.8
None 19 30.2 30.2 100.0
Total 60 100.0 100.0

Table 4: Intervention
Frequency Percent Valid Percent Cumulative Percent

Valid
Non-Surgical 30 47.6 47.6 52.4
Surgical Fixation 30 47.6 47.6 100.0
Total 60 100.0 100.0

Table 5: Descriptive Statistics
N Minimum Maximum Mean Std. Deviation

Age Group 60 65 88 74.20 7.080
Granulation Tissue Formation (Day 7) 60 3.5 67.9 35.700 18.9927
Granulation Tissue Formation (Day 14) 60 5.7 81.7 43.700 22.3985
Granulation Tissue Formation (Day 30) 60 7.9 95.5 51.700 25.8043
Cytokine Levels 60 .91 36.78 18.8633 10.45694
Growth Factor Levels 60 2.81 61.64 32.0125 17.45740

Intervention
The distribution of  the 60 participants into non-surgical 
or surgical fixation approaches is illustrated in Table 4. 
In particular, 30 (47.6%) were treated non-surgically, 
and 30 (47.6%) received surgical fixation. This balanced 

distribution offers a reasonable basis for comparison of  
granulation tissue formation with different intervention 
types. As shown in Table 4, including surgical cases 
brings the cumulative percentage up to 100% to provide 
comprehensive data.

Descriptive Analysis
The descriptive statistics describe granulation tissue 
formation and inflammation markers in elderly fracture 
patients (Table 5). Mean values for granulation tissue 
formation were 35.7 ± 18.992 on Day 7, 43.7 ± 22.398 on 
Day 14, and 51.7 ± 25.804 on Day 30, suggesting that healing 
is occurring gradually. Cytokine levels indicate biological 

variability (mean = 18.863, SD = 10.456) and growth factor 
levels (mean = 32.012, SD = 17.457), as shown in Table 5. 
CRP and IL-6 show means of  4.998 and 10.546, respectively, 
for inflammatory markers. Moderate discomfort among 
patients is quantified with an average patient pain score of  
5.28 (SD = 3.258). These findings show healing progression 
and inflammation trends (Table 5).



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Independent Samples Test
The results of  the Independent Samples Test show for most 
variables, Levene’s Test for Equality of  Variances is non-
significant (Sig. > 0.05), which means that variances are equal 
between groups (Table 6). There is no significant difference 
in means (t value less than 1 with p greater than 0.05) for 

cytokine levels, growth factor levels, and inflammatory 
marker IL-6 on the different days (Day 7, Day 14, Day 30), as 
shown in Table 6. However, the t-test result (t = -2.456, p < 
0.05) for inflammatory marker CRP is significant, implying 
a fundamental difference between groups for CRP levels, 
potentially implying different inflammatory responses.

Inflammatory Marker 1 (CRP) 60 1.23 7.87 4.9983 1.38745
Inflammatory Marker 2 (IL-6) 60 6.77 14.12 10.5463 1.54999
Pain Score (0-10) 60 0 10 5.28 3.258
Valid N (listwise) 60

Table 6: Independent Samples Test
Levene's Test for Equality 
of  Variances

t-test for Equality 
of  Means

F Sig. t
Granulation Tissue Formation 
(Day 7)

Equal variances assumed .000 1.000 -.222
Equal variances not assumed. -.222

Granulation Tissue Formation 
(Day 14)

Equal variances assumed .000 1.000 -.223
Equal variances not assumed -.223

Granulation Tissue Formation 
(Day 30)

Equal variances assumed .000 1.000 -.223
Equal variances not assumed -.223

Cytokine Levels Equal variances assumed .000 .990 -.230
Equal variances not assumed -.230

Growth Factor Levels Equal variances assumed .003 .960 -.222
Equal variances not assumed -.222

Inflammatory Marker 1 (CRP) Equal variances assumed .385 .537 -2.456
Equal variances not assumed -2.456

Inflammatory Marker 2 (IL-6) Equal variances assumed .170 .681 .182
Equal variances not assumed .182

Table 7: Independent Samples Test
t-test for Equality of  Means
df Sig. (2-tailed) Mean Difference

Granulation Tissue Formation 
(Day 7)

Equal variances assumed 58 .825 -1.1000
Equal variances not assumed 58.000 .825 -1.1000

Granulation Tissue Formation 
(Day 14)

Equal variances assumed 58 .824 -1.3000
Equal variances not assumed 58.000 .824 -1.3000

Granulation Tissue Formation 
(Day 30)

Equal variances assumed 58 .824 -1.5000
Equal variances not assumed 58.000 .824 -1.5000

Cytokine Levels Equal variances assumed 58 .819 -.62533
Equal variances not assumed 57.999 .819 -.62533

The results of  the Independent Samples Test have 
no significant mean differences in granulation tissue 
formation on day 7 (p = 0.825, mean difference = 
-1.1000), day 14 (p = 0.825, mean difference = -1.3000) 
nor day 30 (p = 0.825, mean difference = -1.5000), 
cytokine levels (p = 0.819, mean difference = -0.6253), 
A significant difference was found with CRP (p = 

0.017, mean difference = -0.8447), with a group with 
an elevated inflammatory response Table 7. There is 
no significant difference (p = 0.856, mean difference = 
0.0733) for IL-6. These findings suggest that CRP, long 
observed as a risk factor for atherosclerotic disease in 
the elderly, may be essential in promoting healing in this 
group (Table 7).



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Paired Sample T-Test
A progressive increase in granulation tissue formation 
by the elderly fracture patients in the Paired Samples 
Statistics table at three-time points is shown in Table 8. 
From Day 7 to Day 14, the mean values increased from 
35.7 to 43.7 and from 14 to 51.7, suggesting continuous 
tissue growth required for healing. Healing rates also 

vary because the standard deviation increases from 
18.9927 on Day 7 to 25.8043 on Day 30. On Day 7, it 
has a standard error mean of  2.4520, and by Day 30, 
this rises to 3.3313, demonstrating less precision in later 
time points. The continued progression of  this elderly 
fracture points to the necessity for sustained granulation 
tissue development (Table 8).

Growth Factor Levels Equal variances assumed 58 .825 -1.00700
Equal variances not assumed 58.000 .825 -1.00700

Inflammatory Marker 1 (CRP) Equal variances assumed 58 .017 -.84467
Equal variances not assumed 57.480 .017 -.84467

Inflammatory Marker 2 (IL-6) Equal variances assumed 58 .856 .07333
Equal variances not assumed 56.381 .856 .07333

Table 8: Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean

Pair 1 Granulation Tissue Formation (Day 7) 35.700 60 18.9927 2.4520
Granulation Tissue Formation (Day 14) 43.700 60 22.3985 2.8916

Pair 2 Granulation Tissue Formation (Day 30) 51.700 60 25.8043 3.3313
Granulation Tissue Formation (Day 7) 35.700 60 18.9927 2.4520

Pair 3 Granulation Tissue Formation (Day 14) 43.700 60 22.3985 2.8916
Granulation Tissue Formation (Day 30) 51.700 60 25.8043 3.3313

Table 9: Paired Samples Test
Paired Differences
Mean Std. 

Deviation
Std. Error 
Mean

95% Confidence Interval 
of  the Difference
Lower

Pair 1 Granulation Tissue Formation (Day 7) - 
Granulation Tissue Formation (Day 14)

-8.0000 3.4059 .4397 -8.8798

Pair 2 Granulation Tissue Formation (Day 30) 
- Granulation Tissue Formation (Day 7)

16.0000 6.8118 .8794 14.2403

Pair 3 Granulation Tissue Formation (Day 14) 
- Granulation Tissue Formation (Day 30)

-8.0000 3.4059 .4397 -8.8798

From Day 7 to Day 14 (Pair 1), the Paired Samples Test 
results indicate a mean decrease by -8.0000 grams of  
granulation tissue formation, with a standard deviation 
of  3.4059. A mean increase of  16.0000 is significant in 

Pair 2 (Day 30 - Day 7). Pair 3 (Day 14 - Day 30) again 
has a negative of  -8.0000 (mean decrease), also indicating 
a slower growth phase. 95% confidence intervals support 
these findings.

One-Way ANOVA 
ANOVA findings for granulation tissue formation at Days 
7, 14, and 30 show no significant differences between 
groups, implying a constant healing pattern (Table 10). 
The between groups sum of  squares is 145.200, the mean 
square is 36.300, and the F value is 0.094, indicating slight 
variation for Day 7. Like Day 14, we get a sum between 

the group’s squares of  202.800, mean square of  50.700, 
and F value of  0.095 on that Day. As shown in Table 10, 
the between-groups sum is 270.000 and F-value= 0.095. 
These low F values point to granulating tissue formation 
common to both groups with no significant external 
effect, suggesting that the healing process in elderly 
patients remains stable.

Table 10: ANOVA
Sum of  Squares df Mean Square F

Granulation Tissue 
Formation (Day 7)

Between Groups 145.200 4 36.300 .094
Within Groups 21137.500 55 384.318
Total 21282.700 59



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Discussion
This discussion reviewed age-related differences in 
granulation tissue formation and healing after fracture 
in elderly patients. The study compares elderly patients 
with younger counterparts and examines the effect of  
the comorbidities, fracture location, and intervention 
type on tissue development. The study participants have 
a balanced number of  male and female participants in 
the sample. This balance ensures an unbiased comparison 
of  granulation tissue formation as female and male 
differences in healing outcomes. Furthermore, having 
fracture types (Femur, Humerus, Radius, Tibia, and Ulna) 
evenly distributed, the study can evaluate the variation 
as it moves from one injury site to another. Lim et al. 
(2018) emphasized that the type and location of  fracture 
influence the healing process, and load-bearing fractures, 
such as femoral fractures, can be slower due to a reduced 
blood supply (Lim et al., 2018). However, age-related 
healing impairments still affect outcomes in elderly 
patients. The study findings indicate that elderly fracture 
patients, who are at risk of  developing diabetes or 
cardiovascular diseases, are also predisposed to impaired 
granulation tissue formation. However, Marin et al. 
(2018) highlighted that diabetes can cause conditions that 
interfere with healing, such as impaired vascularity and 
cellular function, which can slow down the time it takes to 
heal a fracture (Marin et al., 2018). Balanced comparisons 
are also permitted based on equal proportions of  non-
surgical and surgical fixation treatments. A study by 
Yachmaneni et al. (2023) suggested that surgical fixation 
can improve healing; however, comorbidities, particularly 
diabetes, can interfere with healing by hindering tissue 
regeneration and blood flow (Yachmaneni Jr et al., 2023).
The descriptive statistics show an increase in granulation 
tissue formation from Day 7 to Day 30, consistent with 
the usual healing pattern of  elderly fracture patients. This 
variability in cytokine and growth factor levels suggests 
moderate levels of  inflammation, as indicated by CRP 
and IL-6, which suggest ongoing inflammation. Previous 
work by Walters et al. (2018) demonstrated that cytokine 
activity, granulation tissue formation, and inflammatory 
markers are essential for fracture healing and that 
inflammation is a critical component of  tissue repair 
(Walters et al., 2018). Independent Samples Test results 
indicate no significant differences in granulation tissue 
formation among days; p values are more crucial than 
0.05. However, CRP levels varied significantly, and such 
variation may play a role in the inflammatory response 
associated with healing. Sproston and Ashworth’s (2018) 
study found that CRP modifies immune response and 

angiogenesis, and studies have shown that it influences 
inflammation and tissue regeneration (Sproston & 
Ashworth, 2018).
Results from the Paired Samples Test show a more 
progressive increase in the formation of  granulation tissue 
in elderly fracture patients with a significant rise from Day 
7 to Day 30, though a slower growth rate between Day 14 
and Day 30. This changing pace in healing is also reflected 
in the increasing variability of  standard deviation and 
standard error over time. However, research by Jiang and 
Scharffetter-Kochanek (2020) discussed that granulation 
tissue formation is integral to fracture healing-related 
factors like decreased cell function and vascularization 
decrease, affecting healing time in older patients (Jiang & 
Scharffetter-Kochanek, 2020). ANOVA findings indicate 
no significant differences in granulation tissue formation 
between groups at Days 7, 14, and 30, indicating uniform 
healing. This stock of  healing suggests that there is an 
established granulation tissue healing response in elderly 
fracture patients. Muire et al. (2020) find that healing 
takes longer in older people because of  decreased cellular 
activity and compromised immunity; all fundamental 
mechanisms of  granulation tissue formation are 
unaffected by age (Muire et al., 2020). 
A limitation of  the study is that the sample size is relatively 
small. However, findings may generalize to a larger sample; 
the sample size is relatively small and does not adequately 
represent a larger sample. Furthermore, the observational 
design fails to consider observed confounding variables, 
i.e., lifestyle or nutrition associated with healing but are 
uncontrolled. Furthermore, there may be bias from 
patients excluded who have severe comorbidities because 
they could have revealed a more excellent range of  
healing challenges in elderly patients with more complex 
health conditions. Based on these results, practical 
recommendations for this study include the development 
of  specific fracture management protocols to address 
impaired osseous healing and exaggerated inflammatory 
response in elderly patient (ElHawary et al., 2021). Tracking 
inflammatory progression, spot delay, union or nonunion 
early C-reactive protein (CRP), and interleukin-6 (IL-
6) monitoring can be helpful (Torres et al., 2023). To 
promote optimal tissue regeneration and cellular function, 
both angiogenesis and cellular function must be targeted 
by interventions complementary to comorbidities such 
as diabetes mellitus and atherosclerosis (Katsi et al., 
2023). Supplements such as vitamin D, calcium, and anti-
inflammatory pharmacotherapy can also make healing 
occur faster (Habib et al., 2020). 

Granulation Tissue 
Formation (Day 14)

Between Groups 202.800 4 50.700 .095
Within Groups 29397.100 55 534.493
Total 29599.900 59

Granulation Tissue 
Formation (Day 30)

Between Groups 270.000 4 67.500 .095
Within Groups 39015.900 55 709.380
Total 39285.900 59



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CONCLUSION
This study determines challenges in fracture healing 
associated with age, specifically in the aging elderly, who 
are more prone to slow granulation tissue formation and a 
more responsive inflammatory component. For example, 
many older patients suffer delayed healing secondary to 
reduced vascularization, decreased collagen synthesis, and 
lost immune function. Healing is further complicated by 
comorbidities, specifically diabetes and cardiovascular 
conditions, which inhibit tissue regeneration and blood 
flow. However, the observed progression of  granulation 
tissue over time shows ongoing inflammation, as 
measured by inflammation markers CRP and IL-6, thus 
underscoring the need to develop targeted, age-specific 
treatment protocols. In particular, these results emphasize 
the value of  personalized interventions to facilitate 
optimal fracture recovery in elderly patients.

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