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DOI: 10.1055/s-0043-1768624
Factors Associated with Readmission within 30 Days after Discharge and In-Hospital Mortality after Proximal Femoral Fracture Surgery in the Elderly: Retrospective Cohort[*]
Artikel in mehreren Sprachen: português | EnglishAbstract
Objective To evaluate the factors associated with readmission within 30 days after discharge (R30) and in-hospital mortality (IHM) in elderly patients undergoing proximal femur fracture surgery (PFF).
Methods Retrospective cohort with data from 896 medical records of elderly (≥ 60 years) patients submitted to PFF surgery in a Brazilian hospital between November 2014 and December, 2019. The patients included were followed-up from the date of hospitalization for surgery up to 30 days after discharge. As independent variables, we evaluated gender, age, marital status, pre- and postoperative hemoglobin (Hb), international normalized ratio, time of hospitalization related to the surgery, door-surgery time, comorbidities, previous surgeries, use of medications, and the American Society of Anesthesiologists (ASA) score.
Results The incidence of R30 was 10.2% (95% confidence interval [CI]: 8.3–12.3%), and the incidence of IHM was 5.7% (95%CI: 4.3–7.4%). Regarding R30, hypertension (odds ratio [OR]: 1.71; 95%CI: 1.03–2.96), and regular use of psychotropic drugs (OR: 1.74; 95%CI: 1.12–2.72) were associated in the adjusted model. In the case of IHM, higher chances were associated with chronic kidney disease (CKD) (OR: 5.80; 95%CI: 2.64–12.31), longer hospitalization time (OR: 1.06; 95%CI: 1.01–1.10), and R30 (OR: 3.60; 95%CI: 1.54–7.96). Higher preoperative Hb values were associated with a lower chance of mortality (OR: 0.73; 95%CI: 0.61–0.87).
Conclusion Findings suggest that the occurrence of these outcomes is associated with comorbidities, medications, and Hb.
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Introduction
Proximal femur fractures (PFFs) tend to be increasingly common in the elderly due to the phenomenon of epidemiological transition caused by increased chronic-degenerative conditions. Proximal femur fractures are among the most prevalent health conditions and represent a major impact on public health due to the functional declines they cause in the lives of the elderly.[1] [2] [3] This is a condition related to high mortality and disability rates,[4] and it represents the second leading cause of hospitalization.[5]
It is estimated that, in 2025, there will be ∼ 2.6 million PFF cases worldwide, and this number could be between 4.5 and 6.26 million by 2050.[5] [6] The incidence of PFF around the world reaches almost 600 fractures per 100,000 inhabitants[7] and, in Brazil, incidences from 194.6 to 215.3 per 100,000 inhabitants are reported.[8] [9] Considering the relevance of the subject, metrics such as readmission within 30 days after discharge (R30) and in-hospital mortality (IHM) after PFF surgery are of great interest.
An Italian study reported a rate of R30 of 45.6% after PFF surgery.[10] Factors mentioned in the literature associated with readmission are female gender, American Society of Anesthesiologists (ASA) score, functional status, comorbidities, Charlson score, alcoholism, delay to perform surgery, and total hip arthroplasty.[10] [11] [12]
In Brazil, postsurgery mortality ranges from 4.3 to 7.5%.[8] [13] Although PFF is more frequent in women, mortality is higher among men.[8] The predictors of mortality described in the literature are gender, ethnicity, delay in surgery, sarcopenia, higher ASA scores, comorbidities, hospitalization time, Charlson score, institutionalization, and weight loss.[1] [2] [13] [14] [15]
Considering the high incidence of PFF in the elderly, the great impact on public health, and the challenge of particularizing the care according to patient profile due to the few studies conducted in Brazil, the present study aims to evaluate the factors associated with R30 and IHM after PFF surgery in the elderly in a Brazilian private hospital.
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Material and Methods
Retrospective cohort study with data analysis of medical records in a private hospital in the city of Belo Horizonte, state of Minas Gerais, Brazil. We included patients ≥ 60 years old admitted with PFF, submitted to surgical treatment performed between November 2014 and December 2019. Patients were followed up from the date of hospitalization up to 30 days after discharge. Cases with incomplete records, patients with oncological proximal femur fractures, and patients with other fractures associated with the proximal third of the femur were excluded.
The dependent variables evaluated were R30 and IHM, defined as death during hospitalization or in the readmission period within 30 days. Sociodemographic characteristics such as gender, age, and marital status were analyzed as independent variables. Clinical aspects were also raised: door-surgery time in hours, time of hospitalization in days, hemoglobin (Hb) before and after surgery in g/dL, international normalized ratio (INR), comorbidities: hypertension, diabetes mellitus, chronic kidney disease (CKD), respiratory diseases, cardiovascular diseases, psychiatric disorders, neurological diseases, and endocrine diseases; use of medications: antihypertensives, oral antidiabetics, and insulins, antiemetics/antisecretory, psychotropic drugs, neuroleptics, and anticoagulants; previous surgeries: cardiovascular, femoral fracture, cancer, abdominal, or other surgeries. The type of fracture and the surgical procedure performed and the ASA score were also described.
The present study was approved by the Ethics Committee on September 21, 2020, under opinion number 4,290,194. The waiver of the free and informed consent form was requested because it was a retrospective study guarding the commitment to the confidentiality of the information.
Sample Size
The sample size was calculated to test the proportion of PFF IHM in the elderly. Considering a significance level of 5% and a minimum power of 80%, to test a proportion with a minimum difference of 4% for that found in a reference study,[16] of 10.03%, would be necessary at least 591 elderlies in the sample. Historically, the hospital operated an average of 240 elderly patients with PFF per year.
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Statistical analysis
The qualitative variables were presented as absolute and relative frequencies, and quantitative variables as ± standard deviation (SD) (median). The quantitative variables were submitted to the Shapiro-Wilk normality test.
Logistic regression models were used to evaluate the factors associated with the outcomes. The variables with p < 0.20 in the univariate analysis were included in a saturated model, and adopting the backward strategy, the final model was reached, in which the age was maintained regardless of significance for control. The quality of the fit was evaluated by the Hosmer-Lemeshow test. The results were presented as odds ratios (ORs) and their respective confidence intervals (CIs) of 95%. The analyses were performed in R software version 4.0.5 (R Foundation, Vienna, Austria), and statistical significance was considered when p < 0.05.
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Results
Of the 947 medical records of patients eligible for the study, 51 were excluded because they were from patients with other fractures. The sample analyzed was one with 896 elderly patients submitted to PFF surgery. There was a predominance of females (77.9%), the mean age was 83.4 ± 8.3 years old, and 45.9% were between 80 and 89 years old. Regarding marital status, 41.8% were widowed and 36.6% were married ([Table 1]).
Features |
Valid n |
Statistics |
---|---|---|
Sociodemographic |
||
Gender |
896 |
|
F |
698 (77.9) |
|
M |
198 (22.1) |
|
Age (years old) |
896 |
83.4 ± 8.3 (85.0) |
60 to 69 |
68 (7.6) |
|
70 to 79 |
202 (22.5) |
|
80 to 89 |
411 (45.9) |
|
≥ 90 |
215 (24.0) |
|
Marital status |
892 |
|
Married |
326 (36.6) |
|
Separated |
35 (3.9) |
|
Single |
158 (17.7) |
|
Widower |
373 (41.8) |
|
Clinics |
||
Door-surgery time (hours) |
895 |
11.9 ± 7.9 (10.6) |
Hospital stay (days) |
896 |
4.8 ± 4.8 (3.5) |
Readmission within 30 days after discharge |
890 |
91 (10.2) |
In-hospital mortality |
879 |
50 (5.7) |
Preoperative hemoglobin |
823 |
12.3 ± 1.7 (12.5) |
Postoperative hemoglobin |
840 |
9.7 ± 1.8 (9.6) |
INR |
806 |
1.2 ± 0.5 (1.1) |
Type of fracture |
896 |
|
Peritrochanteric fracture |
797 (88.9) |
|
Femoral neck fracture |
99 (11.1) |
|
Performed procedure |
896 |
|
Arthroplasty |
18 (2.0) |
|
Osteosynthesis |
878 (98.0) |
|
Comorbidities |
||
Hypertension |
885 |
603 (68.1) |
Diabetes mellitus |
885 |
178 (20.1) |
Chronic kidney disease |
885 |
75 (8.5) |
Respiratory diseases |
885 |
57 (6.4) |
Cardiovascular diseases |
885 |
320 (36.2) |
Psychiatric disorders |
885 |
83 (9.4) |
Neurological diseases |
885 |
165 (18.6) |
Endocrine diseases |
885 |
164 (18.5) |
Medicines |
||
Antihypertensive |
840 |
563 (67.0) |
Psychotropic |
840 |
365 (43.5) |
Antiemetic, anti-secretors |
840 |
175 (20.8) |
Oral antidiabetics and insulins |
840 |
152 (18.1) |
Anticoagulants |
840 |
97 (11.0) |
Neuroleptics |
840 |
64 (7.2) |
Previous surgeries |
896 |
|
Cardiovascular |
84 (9.4) |
|
Femur fracture |
37 (4.1) |
|
Cancer |
21 (2.3) |
|
Abdominal |
90 (10.1) |
|
Other surgeries |
117 (13.1) |
|
ASA |
892 |
|
1 |
46 (5.2) |
|
2 |
546 (61.2) |
|
3 |
261 (29.3) |
|
4 |
39 (4.4) |
The mean door-surgery time was 11.9 ± 7.9 hours and the mean length of hospital stay was 4.8 ± 4.8 days. The incidence of R30 was 10.2%, and of IHM, 5.7%. The mean pre- and postoperative Hb values were 12.3 ± 1.7 g/dL and 9.7 ± 1.8 g/dL, respectively, and INR 1.2 ± 0.5 ([Table 1]).
Peritrochanteric fractures represented 88.9% of cases and femoral neck fractures, 11.1%. Osteosynthesis was performed in 98.0% of the cases; when applied to trochanteric fracture cases, they were fixed with intramedullary implants, and in neck fractures cases, with canulate screws. All arthroplasties performed were total hip arthroplasties. The most common comorbidities were hypertension (68.1%), cardiovascular diseases (36.2%), and diabetes mellitus (20.1%), and glycemic control was performed in all diabetic patients. The most used drug groups were antihypertensive (67.0%) and psychotropic (43.5%). The use of anticoagulants did not interfere in the performance of surgery. On previous surgeries, 10.1% underwent abdominal surgeries and 9.4% cardiovascular surgeries. ASA 2 score was reported for 61.2% of the patients ([Table 1]).
Readmission within 30 days after discharge
Hypertension (OR: 1.77 95%CI: 1.07, 1.0;7) and psychotropic drugs (OR: 1.68; 95%CI: 1.08, 2.61) ([Table 2]) were associated in the univariate analysis at the highest chance of R30 (OR: 1.77–2.75) and psychotropic drugs (OR: 1.68; 95%CI: 1.08–2.61) ([Table 2]). In the multivariate model adjusted for age, the highest chance of R30 was associated with arterial hypertension (OR: 1.71; 95%CI: 1.03–2.96) and use of psychotropic drugs (OR: 1.74; 95%CI: 1.12–2.72) ([Table 3]).
Features |
Readmission within 30 days after discharge |
p-value |
||
---|---|---|---|---|
No (n = 799) |
Yes (n = 91) |
OR (95%CI) |
||
Gender |
||||
F |
624 (78.1) |
69 (75.8) |
0.88 (0.54–1.49) |
0.621 |
M |
175 (21.9) |
22 (24.2) |
− |
− |
Age (years old) |
83.2 ± 8.4 (85.0) |
84.5 ± 7.4 (85.5) |
1.02 (0.99–1.05) |
0.184 |
60 to 69 |
64 (8.0) |
4 (4.4) |
− |
- |
70 to 79 |
177 (22.2) |
23 (25.3) |
2.08 (0.76–7.29) |
0.192 |
80 to 89 |
369 (46.2) |
40 (44.0) |
1.73 (0.67–5.92) |
0.309 |
≥ 90 |
189 (23.7) |
24 (26.4) |
2.03 (0.75–7.11) |
0.205 |
Marital status |
||||
Married |
291 (36.6) |
34 (36.3) |
− |
− |
Separated |
33 (4.2) |
2 (2.2) |
0.53 (0.08–1.87) |
0.404 |
Single |
145 (18.2) |
12 (13.2) |
0.73 (0.35–1.42) |
0.371 |
Widower |
326 (41.0) |
44 (48.4) |
1.19 (0.74–1.93) |
0.475 |
Hospital stay (days) |
4.8 ± 5.0 (3.5) |
4.5 ± 3.2 (3.7) |
0.99 (0.93–1.03) |
0.671 |
Surgery waiting time (hours) |
12.0 ± 7.9 (11.1) |
10.9 ± 8.3 (8.9) |
0.98 (0.96–1.01) |
0.223 |
Preoperative hemoglobin |
12.3 ± 1.7 (12.5) |
12.2 ± 1.7 (12.1) |
0.94 (0.82–1.07) |
0.326 |
Postoperative hemoglobin |
9.8 ± 1.8 (9.7) |
9.6 ± 1.7 (9.6) |
0.96 (0.85–1.09) |
0.540 |
INR |
1.2 ± 0.5 (1.1) |
1.2 ± 0.4 (1.1) |
0.80 (0.39–1.35) |
0.479 |
Type of fracture |
||||
Peritrochanteric fracture |
705 (88.2) |
86 (94.5) |
2.29 (0.99–6.64) |
0.079 |
Femoral neck fracture |
94 (11.8) |
5 (5.5) |
− |
− |
Performed procedure |
||||
Arthroplasty |
17 (2.1) |
1 (1.1) |
− |
− |
Osteosynthesis |
782 (97.9) |
90 (98.9) |
1.96 (0.39–35.46) |
0.517 |
Comorbidities |
||||
Hypertension |
526 (66.8) |
71 (78.0) |
1.77 (1.07–3.04) |
0.031 |
Diabetes mellitus |
161 (20.4) |
14 (15.4) |
0.71 (0.38–1.25) |
0.256 |
Chronic kidney disease |
65 (8.2) |
10 (11.0) |
1.37 (0.64–2.67) |
0.377 |
Respiratory diseases |
55 (7.0) |
2 (2.2) |
0.30 (0.05–1.00) |
0.098 |
Cardiovascular diseases |
285 (36.2) |
34 (37.4) |
1.05 (0.67–1.64) |
0.822 |
Psychiatric disorders |
74 (9.4) |
9 (9.9) |
1.06 (0.48–2.09) |
0.877 |
Neurological diseases |
143 (18.1) |
20 (22.0) |
1.27 (0.73–2.12) |
0.374 |
Endocrine diseases |
147 (18.7) |
14 (15.4) |
0.79 (0.42–1.40) |
0.446 |
Medicines |
||||
Antihypertensive |
493 (66.4) |
64 (70.3) |
1.20 (0.76–1.96) |
0.448 |
Oral antidiabetics and insulins |
139 (18.7) |
11 (12.1) |
0.60 (0.29–1.11) |
0.124 |
Antiemetics, anti-secretors |
147 (19.8) |
27 (29.7) |
1.71 (1.04–2.75) |
0.030 |
Psychotropic |
313 (42.1) |
50 (54.9) |
1.68 (1.08–2.61) |
0.021 |
Neuroleptics |
59 (7.5) |
5 (5.5) |
0.72 (0.25–1.68) |
0.490 |
Anticoagulants |
84 (10.7) |
12 (13.2) |
1.27 (0.64–2.35) |
0.465 |
Previous surgeries |
||||
Cardiovascular |
76 (9.5) |
7 (7.7) |
0.79 (0.32–1.66) |
0.572 |
Femur fracture |
35 (4.4) |
2 (2.2) |
0.49 (0.08–1.65) |
0.333 |
Cancer |
18 (2.3) |
3 (3.3) |
1.48 (0.34–4.48) |
0.537 |
Abdominal |
85 (10.7) |
5 (5.5) |
0.49 (0.17–1.12) |
0.130 |
Other surgeries |
109 (13.6) |
8 (8.8) |
0.61 (0.27–1.22) |
0.199 |
ASA |
||||
1 |
43 (5.4) |
2 (2.2) |
− |
− |
2 |
487 (61.3) |
55 (60.4) |
2.43 (0.72–15.14) |
0.229 |
3 |
235 (29.6) |
26 (28.6) |
2.38 (0.68–15.10) |
0.249 |
4 |
30 (3.8) |
8 (8.8) |
4.73 (0.92–39.80) |
0.074 |
Variables |
OR |
OR (95%CI) |
p-value |
---|---|---|---|
Readmission within 30 days after discharge |
|||
Intercept |
0.04 |
(0.01–0.10) |
< 0.001 |
Age (years old) |
|||
60 to 69 |
− |
− |
- |
70 to 79 |
1.87 |
(0.68–6.62) |
0.267 |
80 to 89 |
1.54 |
(0.59–5.30) |
0.428 |
≥ 90 |
1.86 |
(0.68–6.57) |
0.271 |
Systemic arterial hypertension |
1.71 |
(1.03–2.96) |
0.045 |
Use of psychotropic drugs |
1.74 |
(1.12–2.72) |
0.015 |
p-value H-L |
0.870 |
||
In-hospital mortality |
|||
Intercept |
1.17 |
(0.10–12.23) |
0.870 |
Age (years old) |
|||
60 to 69 |
− |
− |
− |
70 to 79 |
0.64 |
(0.15–3.31) |
0.515 |
80 to 89 |
0.57 |
(0.16–2.68) |
0.400 |
≥ 90 |
1.10 |
(0.31–5.19) |
0.909 |
Chronic kidney disease |
5.80 |
(2.64–12.31) |
< 0.001 |
Hospital stay (days) |
1.06 |
(1.01–1.10) |
0.005 |
Readmission within 30 days after discharge |
3.60 |
(1.54–7.96) |
0.002 |
Preoperative hemoglobin |
0.73 |
(0.61–0.87) |
< 0.001 |
p-value H-L |
0.738 |
#
In-hospital mortality
Increase in age (OR: 1.05; 95%CI 1.01–1.09), increase in hospitalization time (OR: 1.07; 95%CI: 1.03–1.12), readmission within 30 days after discharge (OR: 2.64; 95%CI: 1.24–5.19) and chronic kidney disease (OR: 7.05; 95%CI: 3.41–14.10) presented with higher chances of IHM in the univariate analysis. The increase in pre- and postoperative Hb values were associated with a lower chance of IHM (OR: 0.73; 95%CI: 0.62–0.85 for preoperative hemoglobin and OR: 0.70; 95%CI: 0.58–0.84 for postoperative Hb) ([Table 4]). In the final age-adjusted model, the following represented a higher chance of IHM: having CKD (OR: 5.80; 95%CI: 2.64–12.31), increase in hospitalization time (OR: 1.06; 95%CI: 1.01–1.10), readmission within 30 days after discharge (OR: 3.60; 95%CI: 1.54–7.96), and, with lower chances, increased preoperative hemoglobin (OR: 0.73, 95%CI: 0.61–0.87) ([Table 3]).
Features |
In-hospital mortality |
p-value |
||
---|---|---|---|---|
No (n = 829) |
Yes (n = 50) |
OR (95%CI) |
||
Gender |
||||
F |
651 (78.5) |
34 (68.0) |
0.58 (0.32–1.10) |
0.085 |
M |
178 (21.5) |
16 (32.0) |
− |
− |
Age (years old) |
83.2 ± 8.2 (84.0) |
86.2 ± 8.7 (87.0) |
1.05 (1.01–1.09) |
0.012 |
60 to 69 |
63 (7.6) |
3 (6.0) |
− |
- |
70 to 79 |
194 (23.4) |
6 (12.0) |
0.65 (0.17–3.14) |
0.550 |
80 to 89 |
383 (46.2) |
21 (42.0) |
1.15 (0.38–4.98) |
0.823 |
≥ 90 |
189 (22.8) |
20 (40.0) |
2.22 (0.73–9.65) |
0.209 |
Marital status |
||||
Married |
303 (36.7) |
16 (32.0) |
− |
− |
Separated |
34 (4.1) |
1 (2.0) |
0.56 (0.03–2.86) |
0.576 |
Single |
152 (18.4) |
4 (8.0) |
0.50 (0.14–1.39) |
0.220 |
Widower |
337 (40.8) |
29 (58.0) |
1.63 (0.88–3.13) |
0.129 |
Hospital stay (days) |
4.6 ± 4.0 (3.5) |
7.7 ± 11.9 (4.4) |
1.07 (1.03–1.12) |
0.001 |
Door-surgery time (hours) |
11.8 ± 7.9 (10.5) |
12.2 ± 7.9 (12.7) |
1.01 (0.97–1.04) |
0.762 |
Readmission within 30 days after discharge |
80 (9.7) |
11 (22.0) |
2.64 (1.24–5.19) |
0.007 |
Preoperative hemoglobin |
12.4 ± 1.7 (12.6) |
11.3 ± 1.6 (11.6) |
0.73 (0.62–0.85) |
< 0.001 |
Postoperative hemoglobin |
9.8 ± 1.8 (9.7) |
8.8 ± 1.5 (8.6) |
0.70 (0.58–0.84) |
< 0.001 |
INR |
1.2 ± 0.4 (1.1) |
1.3 ± 0.6 (1.1) |
1.35 (0.74–2.11) |
0.248 |
Type of fracture |
||||
Peritrochanteric |
733 (88.4) |
49 (98.0) |
6.42 (1.38–114.25) |
0.067 |
Femur neck |
96 (11.6) |
1 (2.0) |
− |
− |
Performed procedure |
||||
Arthroplasty |
17 (2.1) |
1 (2.0) |
− |
− |
Osteosynthesis |
812 (97.9) |
49(98.0) |
1.03 (0.20–18.67) |
0.980 |
Comorbidities |
||||
Hypertension |
563 (67.9) |
27 (69.2) |
1.07 (0.54–2.21) |
0.863 |
Diabetes mellitus |
167 (20.1) |
7 (17.9) |
0.87 (0.35–1.89) |
0.738 |
Chronic kidney disease |
61 (7.4) |
14 (35.9) |
7.05 (3.41–14.10) |
< 0.001 |
Respiratory diseases |
52 (6.3) |
5 (12.8) |
2.20 (0.73–5.39) |
0.115 |
Cardiovascular diseases |
298 (35.9) |
18 (46.2) |
1.53 (0.79–2.91) |
0.198 |
Psychiatric disorders |
78 (9.4) |
3 (7.7) |
0.80 (0.19–2.29) |
0.719 |
Neurological diseases |
155 (18.7) |
6 (15.4) |
0.79 (0.29–1.79) |
0.604 |
Endocrine diseases |
151 (18.2) |
7 (17.9) |
0.98 (0.39–2.14) |
0.966 |
Medicines |
||||
Antihypertensive |
525 (66.6) |
26 (72.2) |
1.30 (0.64–2.87) |
0.486 |
Oral antidiabetics and insulins |
143 (18.1) |
7 (19.4) |
1.09 (0.43–2.40) |
0.844 |
Antiemetics. anti-secretors |
160 (20.3) |
11 (30.6) |
1.73 (0.80–3.50) |
0.142 |
Psychotropic |
339 (43.0) |
20 (55.6) |
1.66 (0.85–3.29) |
0.143 |
Neuroleptics |
59 (7.1) |
3 (7.7) |
1.09 (0.26–3.13) |
0.892 |
Anticoagulants |
93 (11.2) |
3 (7.7) |
0.66 (0.16–1.87) |
0.496 |
Previous surgeries |
||||
Cardiovascular |
73 (8.8) |
8 (16.0) |
1.97 (0.83–4.15) |
0.093 |
Femur fracture |
33 (4.0) |
3 (6.0) |
1.54 (0.36–4.50) |
0.487 |
Cancer |
19 (2.3) |
2 (4.0) |
1.78 (0.28–6.36) |
0.449 |
Abdominal |
83 (10.0) |
5 (10.0) |
1.00 (0.34–2.36) |
0.996 |
Other surgeries |
111 (13.4) |
3 (6.0) |
0.41 (0.10–1.15) |
0.143 |
ASA |
||||
1 |
39 (4.7) |
5 (10.0) |
− |
− |
2 |
514 (62.3) |
18 (36.0) |
0.27 (0.10–1.06) |
0.065 |
3 |
238 (28.8) |
23 (46.0) |
0.75 (0.29–2.35) |
0.589 |
4 |
34 (4.1) |
4 (8.0) |
0.92 (0.21–3.74) |
0.904 |
#
#
Discussion
Proximal femur fracture in the elderly represents a public health problem worldwide due to its high incidence, morbidity, and mortality. Despite the large number of studies addressing the theme, knowledge about regional realities in contrast to what is already established in the literature can help in more accurate strategies in the care of these patients. In the present study, incidences of 10.2% of R30 and 5.7% of IHM were observed in patients with PFF undergoing surgical treatment. Hypertension added to the use of psychotropic drugs increased the chance of R30. They were associated with a higher chance of IHM having CKD, longer hospitalization time and R30, and the increase in preoperative Hb was associated with a lower chance of IHM. These findings suggest that the presence of comorbidities such as hypertension and CKD are related to outcomes, and possibly others that motivate the regular use of psychotropic drugs, in addition to higher values of preoperative Hb.
Sample Profile
In the present study, it was observed that 77.9% of the patients were female. The predominance of females among the elderly with PFF is well described in the literature.[2] [8] [9] [10] [11] [17] The mean age of the individuals evaluated in the present study was 83.4 ± 8.3 years old, 83.9 ± 8.2 years old for women and 81.4 ± 8.5 years old for men (p < 0.001). European studies reported a mean age of patients with PFF > 80 years old;[10] [17] however, Brazilian studies reported a mean age < 80 years old.[9] [13] Higher mean age in females has been reported by several studies.[2] [9] [13]
Brazilian studies describe average hospitalization times of 8.9 and 12.2 days.[8] [13] In Minas Gerais, a mean hospitalization of 7.3 days was mentioned.[8] In Spain, Prieto et al.[17] found 11.5 days of average hospitalization time. In the present study, the mean length of hospital stay was 4.8 days, shorter than that found in the literature, which can be explained by the fact that they are data from a single private hospital.
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Readmission within 30 days after discharge
Readmission within 30 days after discharge is an important metric because it represents the quality of care provided by the hospital unit and because it is an important predictor of mortality. A systematic review showed that the median readmission rate within 30 days was 10.1%, ranging from 4.5 to 23.1% in 22 analyzed studies.[12] The present study obtained an R30 of 10.2%, a value very close to that reported in the systematic review.
The association between arterial hypertension and R30 found in the present study corroborates the results obtained in an American study with > 8,000 patients.[18] An Indian study compared the bone mineral density (BMD) of patients with hypertensive and non-hypertensive PFF and observed that hypertensive patients had significantly lower BMD.[19] A recent American study pointed to hypertension as a factor associated with a higher chance of transfusion after PFF surgery, and transfusion is associated with a higher risk of mortality and readmission.[20] With the data from these two studies, it is verified that hypertension in patients with PFF seems to be associated with greater bone fragility of the elderly and the occurrence of severe outcomes associated with mortality.
The use of psychotropic drugs can be a proxy for depression, which was associated with rehospitalization within 3 months in a Finnish study.[11]
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In-hospital mortality
The in-hospital mortality rate found in the present study was 5.7%, 8.1% among men and 4.9% among women (p = 0.117), values that corroborate the literature of both Brazilian and international studies. Studies conducted in southern Brazil had an IHM of 4.3 to 7.5%,[9] [13] while European studies reported 2.1 and 3.8%.[10] [17] Higher mortality among men was pointed out by previous studies.[8] [21]
The association of CKD with mortality was described by a Spanish study[2] and in an American study,[15] and CKD was also the cause of readmission of 2.4% of the cases described in an Italian study.[10] Renal failure was identified as a complication of PFF surgery in 14.1% of the cases.[17] The relationship of CKD with a higher chance of IHM found in the present study can then be explained by being a possible evolution of a complication of surgery and because it is the cause of readmission, another independent factor associated with IHM. In the present study, CKD was not directly associated with R30.
Longer hospital stay was associated with a higher chance of IHM in this sample. The association of IHM with hospitalization is still little described in the literature, but it is expected that the elderly with longer hospitalization time present more severe conditions, which would explain a higher chance of death. Some studies address the time until surgery as a risk factor for mortality,[1] [13] [14] [15] which was not observed in the present study. One hypothesis would be the fact that the waiting time until surgery is low in the present study (mean ∼ 12 hours), because it is a private hospital.
Kates et al.[22] reported that 18.6% of patients die during readmission. As demonstrated with the data of the present study, the factors associated with readmission suggest a profile of more frail elderly people, with chronic disease and using various medications. This scenario could be a hypothesis for the association between R30 and IHM demonstrated in this sample. Low Hb values are associated with anemia, which is an important risk factor for hospitalization, morbidity, and mortality in the elderly,[23] so the ratio of higher preoperative hemoglobin values with lower chance of mortality is consistent with the literature.
The present study had as limitation the fact that it is a retrospective search for data from medical records, so that only the available variables could be used and thus it was not possible to evaluate important information, such as functional independence status, body mass index, smoking, and alcohol consumption. Another limiting point is the fact that it is a single-center study, which does not allow the generalization of results.
#
#
Conclusion
In the present article, factors associated with R30 and IHM outcomes were evaluated in a cohort of 896 patients ≥ 60 years old, diagnosed with PFF and undergoing surgical treatment. The results of this study raise the hypothesis that the occurrence of these outcomes is associated with the presence of comorbidities, medication use, and the value of preoperative Hb.
#
#
* Work developed at the Department of Health Sciences, Federal University of Santa Catarina, Araranguá, SC, Brazil.
-
Referências
- 1 Xu BY, Yan S, Low LL, Vasanwala FF, Low SG. Predictors of poor functional outcomes and mortality in patients with hip fracture: a systematic review. BMC Musculoskelet Disord 2019; 20 (01) 568
- 2 Guzon-Illescas O, Perez Fernandez E, Crespí Villarias N. et al. Mortality after osteoporotic hip fracture: incidence, trends, and associated factors. J Orthop Surg Res 2019; 14 (01) 203
- 3 Cummings SR, Melton LJ. Epidemiology and outcomes of osteoporotic fractures. Lancet 2002; 359 (9319): 1761-1767
- 4 Wei J, Zeng L, Li S, Luo F, Xiang Z, Ding Q. Relationship between comorbidities and treatment decision-making in elderly hip fracture patients. Aging Clin Exp Res 2019; 31 (12) 1735-1741
- 5 Cooper C, Campion G, Melton III LJ. Hip fractures in the elderly: a world-wide projection. Osteoporos Int 1992; 2 (06) 285-289
- 6 Gullberg B, Johnell O, Kanis JA. World-wide projections for hip fracture. Osteoporos Int 1997; 7 (05) 407-413
- 7 Kanis JÁ, Odén A, McCloskey EV, Johansson H, Wahl DA, Cooper C. IOF Working Group on Epidemiology and Quality of Life. A systematic review of hip fracture incidence and probability of fracture worldwide. Osteoporos Int 2012; 23 (09) 2239-2256
- 8 Peterle VCU, Geber JC, Darwin W, Lima AV, Bezerra PE, Novaes MRCG. Indicators of morbidity and mortality by femur fractures in older people: a decade-long study in brazilian hospitals. Acta Ortop Bras 2020; 28 (03) 142-148
- 9 Silva DMW, Lazaretti-Castro M, Freitas Zerbini CA, Szejnfeld VL, Eis SR, Borba VZC. Incidence and excess mortality of hip fractures in a predominantly Caucasian population in the South of Brazil. Arch Osteoporos 2019; 14 (01) 47
- 10 Di Giovanni P, Di Martino G, Zecca IA, Porfilio I, Romano F, Staniscia T. Incidence of hip fracture and 30-day hospital readmissions in a region of central Italy from 2006 to 2015. Geriatr Gerontol Int 2019; 19 (06) 483-486
- 11 Yli-Kyyny TT, Sund R, Heinänen M, Malmivaara A, Kröger H. Risk factors for early readmission due to surgical complications after treatment of proximal femoral fractures - A Finnish National Database study of 68,800 patients. Injury 2019; 50 (02) 403-408
- 12 Ali AM, Gibbons CER. Predictors of 30-day hospital readmission after hip fracture: a systematic review. Injury 2017; 48 (02) 243-252
- 13 Ribeiro TA, Premaor MO, Larangeira JA. et al. Predictors of hip fracture mortality at a general hospital in South Brazil: an unacceptable surgical delay. Clinics (Sao Paulo) 2014; 69 (04) 253-258
- 14 Hu F, Jiang C, Shen J, Tang P, Wang Y. Preoperative predictors for mortality following hip fracture surgery: a systematic review and meta-analysis. Injury 2012; 43 (06) 676-685
- 15 Endo A, Baer HJ, Nagao M, Weaver MJ. Prediction model of in.hospital mortality after hip fracture surgery. J Orthop Trauma 2018; 32 (01) 34-38
- 16 Ram GG, Govardhan P. In-Hospital Mortality following Proximal Femur Fractures in Elderly Population. Surg J (NY) 2019; 5 (02) e53-e56
- 17 Prieto-Alhambra D, Reyes C, Sainz MS. et al. In-hospital care, complications, and 4-month mortality following a hip or proximal femur fracture: the Spanish registry of osteoporotic femur fractures prospective cohort study. Arch Osteoporos 2018; 13 (01) 96
- 18 Basques BA, Bohl DD, Golinvaux NS, Leslie MP, Baumgaertner MR, Grauer JN. Postoperative length of stay and 30-day readmission after geriatric hip fracture: an analysis of 8434 patients. J Orthop Trauma 2015; 29 (03) e115-e120
- 19 Dhibar DP, Gogate Y, Aggarwal S, Garg S, Bhansali A, Bhadada SK. Predictors and outcome of fragility hip fracture: a prospective study from North India. Indian J Endocrinol Metab 2019; 23 (03) 282-288
- 20 Arshi A, Lai WC, Iglesias BC. et al. Blood transfusion rates and predictors following geriatric hip fracture surgery. Hip Int 2021; 31 (02) 272-279
- 21 Guerra TEM, Viana RD, Feil L, Feron ET, Maboni J, Vargas ASG. One-year mortality of elderly patients with hip fracture surgically treated at a hospital in Southern Brazil. Rev Bras Ortop 2017; 52 (01) 17-237
- 22 Kates SL, Behrend C, Mendelson DA, Cram P, Friedman SM. Hospital readmission after hip fracture. Arch Orthop Trauma Surg 2015; 135 (03) 329-337
- 23 Goodnough LT, Schrier SL. Evaluation and management of anemia in the elderly. Am J Hematol 2014; 89 (01) 88-96
Endereço para correspondência
Publikationsverlauf
Eingereicht: 18. Februar 2022
Angenommen: 18. Oktober 2022
Artikel online veröffentlicht:
25. Mai 2023
© 2023. Sociedade Brasileira de Ortopedia e Traumatologia. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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-
Referências
- 1 Xu BY, Yan S, Low LL, Vasanwala FF, Low SG. Predictors of poor functional outcomes and mortality in patients with hip fracture: a systematic review. BMC Musculoskelet Disord 2019; 20 (01) 568
- 2 Guzon-Illescas O, Perez Fernandez E, Crespí Villarias N. et al. Mortality after osteoporotic hip fracture: incidence, trends, and associated factors. J Orthop Surg Res 2019; 14 (01) 203
- 3 Cummings SR, Melton LJ. Epidemiology and outcomes of osteoporotic fractures. Lancet 2002; 359 (9319): 1761-1767
- 4 Wei J, Zeng L, Li S, Luo F, Xiang Z, Ding Q. Relationship between comorbidities and treatment decision-making in elderly hip fracture patients. Aging Clin Exp Res 2019; 31 (12) 1735-1741
- 5 Cooper C, Campion G, Melton III LJ. Hip fractures in the elderly: a world-wide projection. Osteoporos Int 1992; 2 (06) 285-289
- 6 Gullberg B, Johnell O, Kanis JA. World-wide projections for hip fracture. Osteoporos Int 1997; 7 (05) 407-413
- 7 Kanis JÁ, Odén A, McCloskey EV, Johansson H, Wahl DA, Cooper C. IOF Working Group on Epidemiology and Quality of Life. A systematic review of hip fracture incidence and probability of fracture worldwide. Osteoporos Int 2012; 23 (09) 2239-2256
- 8 Peterle VCU, Geber JC, Darwin W, Lima AV, Bezerra PE, Novaes MRCG. Indicators of morbidity and mortality by femur fractures in older people: a decade-long study in brazilian hospitals. Acta Ortop Bras 2020; 28 (03) 142-148
- 9 Silva DMW, Lazaretti-Castro M, Freitas Zerbini CA, Szejnfeld VL, Eis SR, Borba VZC. Incidence and excess mortality of hip fractures in a predominantly Caucasian population in the South of Brazil. Arch Osteoporos 2019; 14 (01) 47
- 10 Di Giovanni P, Di Martino G, Zecca IA, Porfilio I, Romano F, Staniscia T. Incidence of hip fracture and 30-day hospital readmissions in a region of central Italy from 2006 to 2015. Geriatr Gerontol Int 2019; 19 (06) 483-486
- 11 Yli-Kyyny TT, Sund R, Heinänen M, Malmivaara A, Kröger H. Risk factors for early readmission due to surgical complications after treatment of proximal femoral fractures - A Finnish National Database study of 68,800 patients. Injury 2019; 50 (02) 403-408
- 12 Ali AM, Gibbons CER. Predictors of 30-day hospital readmission after hip fracture: a systematic review. Injury 2017; 48 (02) 243-252
- 13 Ribeiro TA, Premaor MO, Larangeira JA. et al. Predictors of hip fracture mortality at a general hospital in South Brazil: an unacceptable surgical delay. Clinics (Sao Paulo) 2014; 69 (04) 253-258
- 14 Hu F, Jiang C, Shen J, Tang P, Wang Y. Preoperative predictors for mortality following hip fracture surgery: a systematic review and meta-analysis. Injury 2012; 43 (06) 676-685
- 15 Endo A, Baer HJ, Nagao M, Weaver MJ. Prediction model of in.hospital mortality after hip fracture surgery. J Orthop Trauma 2018; 32 (01) 34-38
- 16 Ram GG, Govardhan P. In-Hospital Mortality following Proximal Femur Fractures in Elderly Population. Surg J (NY) 2019; 5 (02) e53-e56
- 17 Prieto-Alhambra D, Reyes C, Sainz MS. et al. In-hospital care, complications, and 4-month mortality following a hip or proximal femur fracture: the Spanish registry of osteoporotic femur fractures prospective cohort study. Arch Osteoporos 2018; 13 (01) 96
- 18 Basques BA, Bohl DD, Golinvaux NS, Leslie MP, Baumgaertner MR, Grauer JN. Postoperative length of stay and 30-day readmission after geriatric hip fracture: an analysis of 8434 patients. J Orthop Trauma 2015; 29 (03) e115-e120
- 19 Dhibar DP, Gogate Y, Aggarwal S, Garg S, Bhansali A, Bhadada SK. Predictors and outcome of fragility hip fracture: a prospective study from North India. Indian J Endocrinol Metab 2019; 23 (03) 282-288
- 20 Arshi A, Lai WC, Iglesias BC. et al. Blood transfusion rates and predictors following geriatric hip fracture surgery. Hip Int 2021; 31 (02) 272-279
- 21 Guerra TEM, Viana RD, Feil L, Feron ET, Maboni J, Vargas ASG. One-year mortality of elderly patients with hip fracture surgically treated at a hospital in Southern Brazil. Rev Bras Ortop 2017; 52 (01) 17-237
- 22 Kates SL, Behrend C, Mendelson DA, Cram P, Friedman SM. Hospital readmission after hip fracture. Arch Orthop Trauma Surg 2015; 135 (03) 329-337
- 23 Goodnough LT, Schrier SL. Evaluation and management of anemia in the elderly. Am J Hematol 2014; 89 (01) 88-96