Отправить письмо автору 
Написать комментарий 
Ustyantsev D.D., Milyukov A.Yu., Agadzhanyan V.V., Gilev Ya.Kh., Vlasov S.V.
Regional Clinical Center of
Miners’ Health Protection, Leninsk-Kuznetsky, Russia,
Tsyvyan Novosibirsk Research Institute of Traumatology
and Orthopedics, Novosibirsk, Russia
ESTIMATION OF CLINICAL USE OF PREDICTIVE MODEL OF RISK OF COMPLICATIONS FOR EFFICIENT SURGICAL TREATMENT OF PATIENTS WITH PROXIMAL FEMORAL FRACTURES
The
population of older and senile persons has been increasing in the world [1, 2].
As result, the amount of hospital admissions of older patients with traumatic
injuries has been increasing [3]. Proximal femoral fractures are annually
registered in 2 million people each year [4, 5]. The International Fund of
Osteoporosis predicts about 6 million patients with proximal femoral fractures
in 2050 [3, 4, 5].
In
Russia, this diagnosis is confirmed in 100-150 thousand persons per 100,000 of
population, with increasing rate [5, 6]. Mainly, the amount of patients with
proximal femoral fractures has been growing simultaneously with increasing
amount of older patients since more than a half of such injuries happens in
persons older 60 [6, 7, 8].
Patients
older 65 are characterized with high risk of complications in postsurgical
period [8, 9], with higher post-injury mortality as compared to younger people
[9, 10]. It is associated with comorbid diseases [11, 12] and decreasing
physiologic reserves of the body [13].
Considering
the increasing risk of complications and mortality in older patients with
proximal femoral fractures, it is obligatory to discuss the issues of surgical
treatment with consideration of comorbid status [6, 8, 11]. Although some
well-known indicators of unfavorable prognosis are available for this age group
[9, 10, 12, 13], there are not any generally accepted predictive criteria in
relation to clinical estimation of the risk of postsurgical complications at
the background of concurrent diseases in patients with proximal femoral
fractures. Therefore, it is necessary to develop a prediction model, which can
be used during treatment of such patients.
The
previous studies present our prediction model for estimation of the risk of
postsurgical complications in proximal femoral fractures with consideration of
5 parameters (gender, age, a comorbidity category, ASA condition severity
class, a fracture type according to the nomogram) [14, 15]. Subsequently, we
offered a surgical technique for patients with proximal femoral fractures as a
tool for decreasing the potential and actual risk of postsurgical complications
[16]. As result, the next stage should include the objective comparison and
analysis of clinical results after surgical treatment of patients with proximal
femoral fractures with consideration of possible complications.
Objective – to estimate the clinical use of predictive model of
risk of postsurgical complications for efficient surgical treatment
(osteosynthesis and primary total endoprosthetics) for patients with proximal
femoral fractures by means of analysis of complications, treatment duration,
functional results and mortality.
PATIENTS AND METHODS
The
study was conducted in compliance with World Medical Association Declaration of
Helsinki – Ethical Principles for Medical Research Involving Human Subjects,
2013, and the Rules for Clinical Practice in the Russian Federation (the Order
by RF Health Ministry, 19 June 2003, No.266), with written consent for
participation in the study and the approval from the local ethical committee of
the center. 90 patients (the main group) with proximal femoral fractures were
operated in Regional Clinical Center of Miners’ Health Protection from January
2017 till December 2018. The control group included 145 patients with proximal
femoral fractures who were in the center in the period of retrospective studies
from January 2013 till December 2016.
The
inclusion criteria were the age ≥ 18, ISS ≤ 15 [17], no transfer to other
clinics, more than 24 hours of stay in the clinic).
The
table 1 presents the findings of demographic, clinical and physiological
parameters in patients with proximal femoral fractures after hospital
admission.
The
following parameters were considered for each patient: age ((18-64 years) –
young; (65+) – older), gender, comorbid status (0, 1-2, 3+ concurrent
diseases), ASA severity class [18], a fracture type, a surgery type (internal
fixation or joint replacement), hospital stay before (1 day or 2, 3 or more
days) and after surgery.
The
objective estimation of adequate preparation for surgery was realized with our
prediction model of postsurgical complications with use of nomograms for men
and women [14, 15]. The predictive risk of complications was estimated in
relation to increasing age, comorbidity categories, ASA severity class, a
fracture type (intraarticular medial fractures or femoral neck fractures: subcapital,
transcervical, basicervical; extraarticular lateral or trochanteric fractures –
transtrochanteric, subtrochanteric) for men and women [14].
In
compliance with ICD-10, proximal femoral fractures were verified on the basis
of complaints, physical examination and X-ray examination in two standard
planes. A type of proximal femoral fracture was confirmed according to the
classification by A.V. Kaplan [19].
The
patients with proximal femoral fractures were distributed into groups of low
(< 10 %), average (10-30 %) and high risk (> 30 %) of postsurgical
complications on the basis of our model [14].
The
surgical treatment included fixation with PFN, cannulated screws, and primary
total hip replacement according to the modern guidelines [20]. A fixation type
(screws or PFN) was selected according to fracture pattern.
A
possibility of surgery (fixation or endoprosthetics) for proximal femoral
fractures was estimated with consideration of risks of postsurgical
complications relating to the age, concurrent pathology, ASA severity class
according to our technique [16]. If risks were estimated as moderate, the
surgical treatment was conducted.
Mobilization
of patients was initiated in the first day after surgery. The walking frame and
crutches were used. The dosed (30 % of body weight) load to the operated
extremity was allowed in dependence on individual level of rehabilitation and
intensity of pain.
In
the postsurgical period, the types and amount of complications, treatment
duration and mortality were registered.
Estimation
of functional results of surgical treatment of patients with proximal femoral
fractures was conducted 1 year after surgery with use of the descriptive scale
from American Academy of Orthopedic
Surgeons Assessment, developed by R.A. Goodwin in 1968 [21], and Harris
Evaluation System of the Hip [22]. These techniques allow estimating the
clinical outcomes after fixation of proximal femoral fractures and hip
replacement.
Goodwin
score for estimation of hip surgery outcomes includes the qualitative
estimation of criteria (pain, volume of motions, walking), with estimated
results as fine, good, satisfactory or unsatisfactory [21].
Harris Evaluation System of the Hip supposes the estimation of four
categories: pain, function, deformation, range of motions. Each category is
characterized by specific number of points. The maximal number of points is
100. 90-100 points present excellent function, 80-89 – good, 70-79 – satisfactory,
< 70 – unsatisfactory [22].
Statistical analysis
The
statistical analysis of the data was conducted with IBM SPSS Statistics 21 (Statistical
Product and Service Solutions – SPSS).
The qualitative signs are presented as absolute and relative (%) values.
The quantitative variables are presented as mean arithmetic (M) and standard
deviation (SD) of mean arithmetic in view of Me (LQ-UQ), where Me – median,
(LQ-UQ) – interquartile range (IQR) (LQ – 25 %, UQ – 75 % quartiles). Depending
on type of distribution of variables, Student’s test or Mann-Whitney’s U-test
were used for estimation of reliability of differences in the groups. χ2 (chi-square)
test was used for estimation of significance of differences in incidence of the
studied values. The critical level of significance (α) during testing the statistical hypotheses was 0.05.
Differences were considered as statistically significant with p < 0.05.
RESULTS
The table 1 shows the high degree of matching between the characteristics of demographic, clinical and physiological parameters in patients with proximal femoral fractures at admission in the main (n = 90) and comparison (n = 145) groups. Proximal femoral fractures were presented by intraarticular medial or femoral neck fractures in 76 %, and by extraarticular lateral or trochanteric fractures in 24 % in the main and comparison groups (the table 1).
Table 1. Characteristics of demographic, clinical and physiological parameters in patients with proximal femoral fractures at admission to the clinic
|
Parameters |
Main
group |
Comparison group |
p |
|
Age: |
|
|
|
|
Gender: |
|
|
|
|
Injury severity (ISS)2, M (SD), points |
12 (9.1) |
13 (8.9) |
0.873 |
|
Fracture
type3: Lateral
trochanteric fractures (extraarticular): |
21 (24) |
34 (24) |
0.863 |
|
Comorbidity (concurrent diseases before injury): |
|
|
|
|
ASA severity
class4: |
|
|
|
Note: 1percentage correlation was calculated with consideration of all patients in the groups. 2ISS – Injury Severity Score [17]. 3Fracture type according to classification by A.V. Kaplan [19]. 4Severity class according to classification of objective status of American Society of Anesthesiologists (ASA) [18]. M (SD) – mean (standard deviation); p – probability of absence of intergroup differences.
Initially,
our prediction model was used for estimation of the risk of possible
postsurgical complications in the main group [14]. After distribution of the
patients (treated from January 2017 till December 2018) into the risk groups, 4
patients (4.4 %) were in the low risk group (< 10 %); the average risk group
(10-30 %) included 56 patients (62.2 %); 30 patients (33.4 %) were in the high
risk group (> 30 %) (the table 2).
The
comparison of values of initial estimation of predictive risk of complications
at admission did not find any significant differences in distribution of
patients into the risk group in the main and comparison groups (the table 2).
Table 2. Comparative characteristics of demographic predictive risk of complications in patients with proximal femoral fractures in the studied groups
|
Parameters |
Main
group |
Comparison group |
p |
|
Predictive risk of complications2
at admission to hospital, n (%): |
|
|
|
|
Predictive risk of complications2
before surgery |
|
|
|
|
Surgery type, abs.
(%): |
|
|
|
|
Days before surgery: |
|
|
|
|
Type of complication before surgery1,
|
8 (8.8) |
22 (15.2) |
0.009 |
|
ICU stay, Me (IQR), days: |
0.7 (0.6 – 1.0) |
0.9 (0.6 – 1.2) |
0.11 |
|
Hospital stay after surgery, Me (IQR), days: |
11.3 (9.2 – 15.0) |
14.5 (9.2 – 23.0) |
0.04 |
Note: 1Percentage correlation was calculated with consideration of all patients in the groups. 2Predictive risk of postsurgical complications (low (0-10 %), middle (11-30 %), high (> 30 %)) was calculated with use of the model considering the age, gender, comorbidity status, ASA severity class and fracture type with nomogram for men and women individually.
The
patients of the main group with high risks of surgical intervention (n = 30) relating
to concurrent pathology and severity of condition received the conservative
symptomatic treatment of cardiovascular, therapeutic and surgical diseases
under supervision of cardiologist, therapeutist and surgeon within 7 days (on
average, 6.8 (2.40 days before surgery)). After correction of somatic
pathology, the recurrent estimation of the risk of postsurgical complications
was conducted in the main group.
The
recurrent presurgical use of the prediction model of the risk of complications
with use of the nomogram showed the low, average and high risk of postsurgical
complications correspondingly in 10 (11 %), 58 (64 %) and 22 (25 %) patients
with proximal femoral fractures (the table 2). In the main group, the number of
patients with high risk of postsurgical complications decreased 1.34 times (χ2 =
36.2, p < 0.01) in relation to the initial value by means of redistribution
into the groups of average and low risk (2.5-fold increase in the number of
patients with low risk as compared to the initial estimation, χ2 =
23.2, р < 0.01) (table 2).
Our
method for selection of management techniques for proximal femoral fractures
[16] was taken as the basis for the surgical management algorithm with use of the
prediction model of the risk of postsurgical complications (Fig. 1).
Figure. Surgical
treatment algorithm (osteosynthesis or primary total hip replacement) for
patients with proximal femoral fractures with consideration of predictive risk
of postsurgical complications
The
potential risk of complications (more or less 30 %) was estimated with the
nomogram (combination of parameters) with consideration of the age (young
(18-64 years) and older (65+)), a comorbidity category (0 – absence, 1-2, 3 and
more concurrent diseases), a severity class according to ASA classification of
objective status of patient, a type of fracture in men and women separately
[14, 15].
If
ASA severity class 4 with potential risk of complications > 30 % was found,
surgical interventions were not performed on the admission day, and the
patients were transferred to the profile units (cardiology, neurology, therapy
and surgery) for condition stabilization. Subsequently, the potential risk of
complications was estimated again, and a possibility of surgical treatment was
estimated. For ASA severity class 3 with potential risk of complications <
30 %, low invasive fixation was conducted for proximal femoral fractures in
medial or lateral region. A fixation method was selected according to a
fracture type (screws or PFN): closed reposition and cannulated screws for
medial fractures; closed reposition and intramedullary fixation with PFN for
lateral injuries.
For
ASA severity classes 1 or 2 with potential risk of complications < 30 %, the
principle of unlimited (required) degree of surgical invasion was used. For
medial fractures (subcapital and transcervical), total hip replacement was
carried out.
For
basicervical fractures of femoral neck, the quantitative analysis of X-ray
images was conducted for estimation of peripheral index of structural changes
(cortical index) with measurement of thickness of cortical layer of the femoral
bone according to Barnett-Nordin [23]. Total hip replacement was conducted if
cortical index was < 54 %. If cortical index was ≥ 54 %, the patient's
physical activity was measured with Rivermead Mobility Index (RMI) [24]. For
high mobility index (7-15 points), closed reposition and intramedullary locked
fixation with PFN were performed. For low level of physical activity (≤ 7 points),
closed reposition and fixation with cannulated screws were performed.
For
lateral proximal femoral injuries, namely for subtrochanteric fractures, closed
reposition and locked fixation with PFN were used. For trochanteric fractures,
the intensity of peripheral structural changes was measured with cortical index
according to Barnett-Nordin. If cortical index was ≥ 54 %, closed reposition
and PFN fixation were conducted. If Barnett-Nordin index was < 54 %, the
condition of bone tissue was estimated with Singh index [25] for qualitative
estimation of intensity of osteoporosis in the femoral head and neck, and in
greater trochanter with 7-point scale. If Singh index was ≤ 2 (i.e. full
disappearance of archy trabecules), total hip replacement was conducted.
The
table 2 presents the types of surgeries and their amount according to types of
proximal femoral fractures in the patients of the study groups.
Primary
total hip replacement and osteosynthesis were conducted for 71.1 % and 28.9 %
correspondingly. It is necessary to note that only 25 % of the patients of the
main group showed high risk (> 30 %) of postsurgical complications in
comparison with 37.9 % of patients in the comparison group (p = 0.03). It is
associated with adequate preparation before surgery (the table 2).
84.5
% of patients in the main group showed longer hospital stay before surgery
(> 3 days) in comparison with 74.5 % in the comparison group (p = 0.04) (the
table 2). It was determined by preliminary correction of somatic pathology in
the profile unit.
The
following complications of intramedullary fixation were identified in the
postsurgical period: thrombophlebitis and thrombosis of deep veins of lower
extremities were identified in 3 and 10 cases, with 2 cases with embolism
danger (the table 2). It required for vascular surgical interventions. After
osteosynthesis, one case in each group was associated with metal construct
migration, and migration of one cannulated screw among three implanted ones.
With consideration of estimation of intrasurgical compression, the patients
received recurrent installment of the screw. Contact dermatitis was registered
in 1 case in the comparison group.
After
hip replacement, thrombophlebitis and thrombosis of lower extremity veins were
registered in 4 and 7 cases (with 1 case of embolism-threatening condition,
which required for vascular surgical intervention) in the main and comparison
groups correspondingly.
The
high incidence of thrombophlebitis and thrombosis was determined by total
control with use of duplex scanning, which was included into the postsurgical
management algorithm for patients with proximal femoral fractures.
In
the comparison group, one patient had a dislocation of head of the hip joint
endoprosthesis. Closed reduction of the endoprosthesis dislocation was
conducted after additional X-ray examination.
A
local infection in the surgical wound was registered in one case in the
comparison group. Contact dermatitis was in one case. The patients received the
conservative treatment. Its results were positive.
The
total number of postsurgical complications in the patients with proximal
femoral fractures was 8.8 % and 15.2 % in the main and comparison groups
correspondingly (the table 2). Therefore, the patients of the main group showed
1.7 times less registered postsurgical complications (p = 0.009) as compared to
the comparison group.
There
were not any statistically significant differences in the values of ICU stay of
patients with proximal femoral fractures after surgery in the compared groups
(the table 2).
In
the study group, the hospital stay was 1.3 times shorter (p = 0.04) in relation
to this value in the comparison group. One should note that duration of the
postsurgical period in the groups allowed partial removal of suture and
teaching the patients to walk with crutches.
All
patients (100 %) were discharged for outpatient treatment. Their condition was
satisfactory, without complications and lethal outcomes at the moment of
discharge.
Clinical
estimation of functional outcomes of surgical management of proximal femoral
fractures was conducted one year after surgery in 84 (93 %) patients in the
main group and in 135 available (93 %) patients in the comparison group. The
functional outcomes of osteosynthesis and hip replacement were estimated in 35
% and 57 % of patients with proximal femoral fractures in each group
correspondingly.
The
comparative analysis of functional results of treatment of proximal femoral
fractures after Goodwin osteosynthesis showed the most favorable outcomes of
function recovery in the main group. It was manifested by increasing number of
fine and good results – 2.8 times (χ2 = 12.8,
p = 0.0025) and 2 times (χ2 = 3.8,
p = 0.05), whereas the comparison group showed the highest satisfactory
result (the table 3).
Table 3. Estimation of functional results of treatment of patients with proximal femoral fractures 1 year after osteosynthesis (R.A. Goodwin, 1968) [19]
|
Estimation of results |
Main group |
Comparison
group * |
χ2 (p) |
||
|
n |
% |
n |
% |
||
|
Fine |
14 |
43.8 |
8 |
15.7 * |
12.8 (0.025) |
|
Good |
11 |
34.4 |
9 |
17.6 * |
3.8 (0.05) |
|
Satisfactory |
5 |
15.6 |
29 |
56.9 * |
30.1 (0.05) |
|
Poor |
1 |
3.1 |
4 |
7.8 |
0.02 (0.89) |
|
Unsatisfactory |
1 |
3.1 |
1 |
2.0 |
0.00016 (0.89) |
|
Total |
32 |
100 |
51 |
100 |
|
Note: * – comparison of groups with χ2, p < 0.05.
The highest quantitative values of improvement in function of the lower extremity and the hip joint (Harris score) were identified in the main group of patients with proximal femoral fractures who received hip joint replacement. The results of treatment of 49 patients of the main group were considered as fine and good (the table 4). Harris score showed more fine and good results – 1.5 times (χ2 = 12.6, p = 0.05) and 1.2 times (χ2 = 6.0, p = 0.05) higher correspondingly than in the comparison group. One should note that the best functional result was received in patients of the main group by means of decreasing potential and actual risk of complications. It allowed active rehabilitation in early postsurgical period. Higher rate of fine and good postsurgical values of Harris score in the main group shows earlier and more full recovery of function of the injured lower extremity and the joint, resulting in faster return to daily life.
Table 4. Estimation of functional results of treatment of patients with proximal femoral fractures 1 year after hip surgery (W.H.Harris, 1969) [20]
|
Estimation of results |
Main group |
Comparison group* |
χ2 (p) |
||||
|
Estimation |
Points |
n |
% |
n |
% |
|
|
|
Fine |
90-100 |
19 |
36.5 |
20 |
23.8* |
12.6 (0.05) |
|
|
Good |
80-89 |
30 |
58.0 |
40 |
47.6* |
6.0 (0.05) |
|
|
Satisfactory |
70-79 |
3 |
5.5 |
24 |
28.6* |
31.5 (0.025) |
|
|
Unsatisfactory |
less than 70 |
- |
- |
- |
- |
|
|
|
Total |
100 |
52 |
100 |
84 |
100 |
|
|
Note: * – comparison of groups with χ2, p < 0.05.
DISCUSSION
The study
confirmed the possibility of clinical administration of the prediction model of
the risk of postsurgical complications in patients with proximal femoral
fractures. Our model accurately predicts the risk of postsurgical complications
for each patient with consideration of such parameters as age, gender, comorbid
status, ASA severity class, type of proximal femoral fracture (the table 1).
The study showed that the estimation system in view of the nomogram [14] allows
efficient differentiation of subgroups into of different risk (low, average and
high) and fast and easy identification of high risk patients during hospital
stay.
One should
note that our efforts for development of the model of prediction of
complications in patients with injuries are not unprecedented. For the last 30
years, Trauma and Injury
Severity Score (TRISS) [23] was the main technique for estimation of trauma
outcome. TRISS model, which was developed with logistic regression, was
developed for prediction of probability of post-injury survival with
consideration of age, ISS [17] and Revised Trauma Score (RTS). Whereas TRISS
was widely used for estimation and comparison of trauma outcomes, it was
criticized for important disadvantages in traumatology literature. For the last
20 years, it was highly criticized for that fact that it is based on the data
basis of 80s, on Major Trauma Outcomes Study. Since the trauma management
system has significantly changed during this period, the modern predictive
significance of TRISS was called into question. It was partially associated
with development of the new indices in 1990 and in 1995, but necessity for
continuous and multiple updates limited their practical administration [26].
Another disadvantage of TRISS is its inability to predict the risk of
postsurgical complications. A Severity Characterization of Trauma (ASCOT) [27]
was acknowledged as the improved predictor of complications and outcomes, but
the complexity of calculations limits its wide use. Other attempts of
prediction of risk of post-injury complications were made [28], but,
unfortunately, there is not easy and statistically accurate modern model of
potential risk of complications after femoral fractures. The advantage of use
of our prediction model of risk of postsurgical complications in patients with
proximal femoral fractures with consideration of age, gender, comorbid status
and condition severity consists in receive of more objective information on a
patient before surgical treatment and correct optimization of surgical
treatment with minimal risks.
One
should acknowledge the disadvantages of our prediction model. Possibly, the
main disadvantage is the fact that model was developed and tested in relation
to index (inhospital) admission. The period of follow-up of clinical and
functional results within one year after surgery is insufficient for the fullest
estimation of treatment outcomes. There is an unexplored fact: is it possible
to use the prediction model for estimation of intermediate and remote results
of surgical treatment of proximal femoral fractures at the outpatient stage?
The model is only the predictor of probability of complications, and it does
not estimate the return to previous functional status and does not predict it
and quality of patient’s life in the future. But this disadvantage only means
that this information has to be tested in further prospective studies with collection
and analysis of data on outcomes of femoral bone fractures that can be
important for making a decision of preventive and rehabilitation measures.
CONCLUSION
The
results of the study show higher efficiency of surgical treatment (fixation or
primary total hip replacement) in patients with proximal femoral fractures with
consideration of potential estimation of risk of postsurgical complications.
The
clinical use of the prediction model of risk of postsurgical complications for
efficient surgical treatment (osteosynthesis or primary total replacement) of
patients with proximal femoral fractures was accompanied by 1.7-fold decrease
(p = 0.009) in complications, 1.3- fold decrease (p = 0.04) in time of
treatment, the increase in fine and good functional results 2 times (p = 0.001)
and 1.4 times (p = 0.05) correspondingly.
Our
prediction model of the risk of postsurgical complications in patients with
proximal femoral fractures with use of combination of parameters (age, gender,
a comorbidity category, ASA severity class, a fracture type) allows precise
prediction of development of possible complications in the postsurgical period.
Moreover, the estimation system with the nomogram allows efficient
differentiation of patients into subgroups of different risk (low, average,
high), and fast and easy identification of patients with high risk during
admission period. Owing to continuous prediction of a probability of
complications with use of small range of parameters, it can be used as a tool
of dynamic observation of patients’ condition.
Our
surgical management algorithm (osteosynthesis or primary total hip replacement)
for patients with proximal femoral fractures with consideration of predictive
risk of postsurgical complications is a simple and easy for understanding and
daily practical use, with high potential for development of guidelines for
treatment of proximal femoral fractures.
Information on financing and conflict of interests
The
study was conducted without sponsorship.
The
authors declare the absence of any clear or potential conflicts of interests
relating to publication of this article.
REFERENCES:
1. Keller
JM. Sciadini MF, Sinclair E, O’Toole RV. Geriatric trauma: demographics,
injuries, and mortality. J Orthop Trauma. 2012; 26(9): el61-e165
2. Werner CA. The Older
Population: 2010, Census Briefs, C2010BR-09, U.S. Census Bureau. 2011; Issued
November. Available at: www.census.gov/prod/cen2010/briefs/c2010br-09.pdf
3. Cook AC, Joseph B, Inaba K, Nakonezny PA, Bruns BR, Kerby JD, et al. Multicenter external
validation of the Geriatric Trauma Outcome Score: a study by the prognostic
assessment of life and
limitations after trauma in the elderly(PALLIATE)
consortium. Trauma апd Care
Surg. 2016;
80(2): 204-209
4. NTDB Annual Report 2011.
American College of Surgeons. Nance ML, ed. Available
at: https://www.facs.org/~/media/files/quality%20programs/trauma/ntdb/ntdbannualreport2011.ashx
5. Gladkova
EN, Khodyrev VN, Lesnyak OM. Analysis of condition of realization of medical
care arrangement and outcomes in patients with proximal hip fractures. Osteoporosis and Osteopathy. 2011; (3): 7-10. Russian (Гладкова Е.Н.,
Ходырев В.Н., Лесняк О.М. Анализ состояния оказания медицинской помощи и
исходов у больных с переломами проксимального отдела бедра //Остеопороз и
остеопатии. 2011. № 3. С. 7-10)
6. Gorodnichenko AI, Uskov ON, Minaev AN, Korneev AN. Surgical
treatment of proximal femoral bone fractures in older patients. Kremlin Medicine. Clinical Herald. 2011;
(4): 65-69. Russian (Городниченко
А.И., Усков О.Н., Минаев А.Н., Корнеев А.Н. Хирургическое лечение переломов
проксимального отдела бедренной кости у пациентов старшей возрастной группы
//Кремлевская медицина. Клинический вестник. 2011. № 4. C.65-69)
7. Kaplan AV. Traumatology of older age. M.: Medicine, 1997; 426 p. Russian (Каплан
А.В. Травматология пожилого возраста. М.: Медицина, 1977. 426 с.)
8. Vorontsova
TN, Bogopolskaya AS, Cherny AZh, Shevchenko SB. Structure of group of patients
with proximal femoral bone fractures and calculation of annual requirement for
urgent surgical care. Traumatology and Orthopedics of Russia. 2016; 1(79): 7-20. Russian (Воронцова
Т.Н., Богопольская А.С., Черный А.Ж., Шевченко С.Б. Структура контингента
больных с переломами проксимального отдела бедренной кости и расчет
среднегодовой потребности в экстренном хирургическом лечении //Травматология и
ортопедии России. 2016. № 1(79). С. 7-20)
9. Goodmanson NW, Rosengart MR, Barnato AE, Sperry
JL, Peitzman AB, Marshall GT. Defining geriatric trauma: when does age make a
difference? Surgery. 2012; 152(4): 668-674
10. Hashmi A,
Ibrahim-Zada I, Rhee P, Aziz H, Fain MJ, Friese RS, et al. Predictors of mortality in geriatric trauma patients:
a systemic review and meta-analysis. J Trauma Acute Care Surg. 2014;
76(3): 894-901
11. Shevalaev GA, Dudina EV, Efremov IM. Comorbidity in patients at
the age of 50 and older with proximal femoral bone fractures. Issues of Traumatology and Orthopedics. 2011; (1): 31-33. Russian (Шевалаев Г.А., Дудина Е.В., Ефремов И.М. Коморбидность
у больных 50 лет и старше с переломами проксимального отдела бедренной кости
//Вопросы травматологии и ортопедии. 2011. № 1. С. 31-33)
12. Duvall DB,
Zhu X, Elliott AC, Wolf SE, Rhodes RL, Paulk ME, et al. Injury severity and
comorbidities alone do not predict futility of care after geriatric trauma. J Palliat Med. 2015; 18(3): 246-250
13. Zhao FZ, Wolf SE, Nakonezny PA, Minhajuddin
A, Rhodes RL, Paulk ME, et al. Estimating geriatric mortality after injury
using age, injury severity, and performance of a transfusion: the Geriatric
Trauma Outcome Score. J Palliat Med. 2015; 18(8): 677-681
14. Milyukov
AYu, Ustyantsev DD, Gilev YaKh, Mazeev DV. Predictive significance of
comorbidity status in development of complications in surgical care of patients
with injuries to proximal femoral bone. Polytrauma. 2017; (2): 17-26. Russian (Милюков А.Ю., Устьянцев Д.Д.,
Гилев Я.Х., Мазеев Д.В. Прогностическая значимость коморбидного статуса в
развитии осложнений при хирургическом лечении пациентов с травмами
проксимального отдела бедренной кости //Политравма. 2017. № 2. С. 17-26)
15. Agadzhanyan
VV, Milyukov AYu, Ustyantsev DD, Gilev YaKh. Prediction model of potential risk
of complications in patients with fractures of proximal femoral bone fractures.
Polytrauma. 2018; (3): 6-19. Russian (Агаджанян В.В., Милюков А.Ю., Устьянцев Д.Д., Гилев Я.Х.
Прогностическая модель потенциального риска развития осложнений у пациентов с
переломами проксимального отдела бедренной кости //Политравма. 2018. № 3. С. 6-19)
16. Agadzhanyan VV, Milyukov AYu, Ustyantsev DD. Selection of
surgical management for proximal femoral bone fractures: patent No. RU 2672691 S1 /No.2017144715; application from 19 December
2017; published on 19 November 2018; bulletin No.32. Russian (Агаджанян
В.В., Милюков А.Ю., Устьянцев Д.Д., Способ
выбора тактики хирургического лечения при переломах проксимального отдела
бедренной кости: патент № RU 2672691 С1 / №
2017144715; заявл. 19.12.2017; опубл. 19.11.2018, Бюл. № 32)
17. Osier
T, Baker SP, Long W. A modification of the Injury Severity Score that both
improves accuracy and simplifies scoring. J Trauma. 1997; 43(6): 922-925
18. Physical status of patients
according to ASA (American Society of Anesthesiolgists). ANEST-REAN.ru. Available at:
http://anest-rean.ru/asa/ (Физический статус пациентов
по классификации ASA (Американского
общества анестезиологов). ANEST-REAN.ru. Available at: http://anest-rean.ru/asa/)
19. Kaplan AV. Bone and joint injuries. 3rd edition. M.:
Medicine, 1979; 568 p. Russian (Каплан А.В. Повреждения костей и суставов. 3-е изд. М.: Медицина, 1979. 568 с.)
20. Tikhilov RM, Shapovalov VM. The manual for hip joint replacement.
Spb: Vreden RosNIITO, 2008; 324 p. Russian (Тихилов Р.М., Шаповалов В.М. Руководство по
эндопротезированию тазобедренного сустава. СПб.: РосНИИТО им. P.P. Вредена, 2008. 324 с.)
21. Goodwin RA. The Austine Moore
prothesis in fresh femoral neck fractures. A review of 611 post-operative
cases. Am. J. Orthop.Surg. 1968;
10(2): 40-43
22. Harris W.H. Traumatic
arthritis of the hip after dislocation and acetabular fractures: treatment of
mold arthroplasty. An end-result study using a new method of result evaluation.
J Bone Joint
Surg Am. 1969; 51(4): 737-755
23. Barnett E,
Nordin BE. The radiological diagnosis of osteoporosis: а new approach. Clin.
Radiol. 1960; (11): 166-174
24. Collen FM, Wade DT, Robb GF,
Bradshaw CM. The Rivermead Mobility Index: a further development of Rivermead
Motor Assessment. Internat. Disability
Studies. 1991; 13(2): 50-54
25. Singh M, Nagrath AR, Maini PS. Changes in trabecular pattern of the upper end of the femur as an
index of osteoporosis. J. Bone Joint Surg
Am. 1970; 52(3): 457-467
26. Boyd
CR, Tolson MA, Copes WS. Evaluating trauma care: the TRISS method. Trauma Score
and the Injury Severity Score. J Trauma. I987; 27(4): 370-378
27. Rogers
FB, Osier T, Krasne M, Rogers A, Bradburn EH, Lee JC, et al. Has TRISS become
an anachronism? A comparison of mortality between the National Trauma Data Bank
and Major Trauma Outcome Study Databases. J Trauma Acute Care Surg. 2012; 73(2): 326-331
28. Champion
HR, Copes WS, Sacco WJ, Frey CF, Holcroft JW, Hoyt DB, et al. Improved
predictions from a severity characterization of trauma (ASCOT) over Trauma and
Injury Severity Score (TRISS): results of an independent evaluation. J Trauma. 1996;
40(1): 42-48
29. Nirula
R, Gentilello LM. Futility of resuscitation criteria for the «young» old and
the «old» old trauma patient: a National Trauma Data Bank analysis. J Trauma. 2004;
57(1): 37-41
Статистика просмотров
Ссылки
- На текущий момент ссылки отсутствуют.
