CC BY-NC-ND 4.0 · Rev Bras Ortop (Sao Paulo) 2023; 58(02): 222-230
DOI: 10.1055/s-0043-1768624
Artigo Original
Trauma

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 | English
1   Faculdade Ciências Médicas de Minas Gerais, Belo Horizonte, MG, Brasil
,
1   Faculdade Ciências Médicas de Minas Gerais, Belo Horizonte, MG, Brasil
,
2   Departamento de Ciências da Saúde, Universidade Federal de Santa Catarina. Araranguá, SC, Brasil
,
2   Departamento de Ciências da Saúde, Universidade Federal de Santa Catarina. Araranguá, SC, Brasil
,
3   Programa de Pós-Graduação em Ciências da Saúde, Faculdade Ciências Médicas de Minas Gerais, Belo Horizonte, MG, Brasil
› Institutsangaben
Financial Support This study did not receive any financial support from either public, commercial, or not-for-profit sources.
 

Abstract

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]).

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]).

Table 2

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

Table 3

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


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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]).

Table 4

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


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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]


#

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.


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* 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

Isabel Cristina Gomes Moura, PhD
Alameda Ezequiel Dias
275–Santa Efigênia, 30130-110, Belo Horizonte, MG
Brasil   

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