Associations between Early Surgery and Postoperative Outcomes in Elderly Patients with Distal Femur Fracture: A Retrospective Cohort Study
by
, , , , and
Norio Yamamoto
1,2,3
,
Hiroyuki Ohbe
4,*,
Yosuke Tomita
5,
Takashi Yorifuji
2,
Mikio Nakajima
4,6,
Yusuke Sasabuchi
7,
Yuki Miyamoto
4,8,
Hiroki Matsui
4,
Tomoyuki Noda
9 and
Hideo Yasunaga
4 1
Department of Orthopedic Surgery, Miyamoto Orthopedic Hospital, Okayama 773-8236, Japan
2
Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8558, Japan
3
Systematic Review Workshop Peer Support Group (SRWS-PSG), Osaka 541-0043, Japan
4
Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo 113-0033, Japan
5
Department of Physical Therapy, Faculty of Health Care, Takasaki University of Health and Welfare, Takasaki 370-0033, Japan
6
Emergency Life-Saving Technique Academy of Tokyo, Foundation for Ambulance Service Development, Tokyo 192-0364, Japan
7
Data Science Center, Jichi Medical University, Tochigi 329-0498, Japan
8
Department of Emergency Medicine, Kyoto Prefectural University of Medicine, Kyoto 602-8566, Japan
9
Department of Orthopaedic Surgery and Traumatology, Kawasaki Medical School General Medical Center, Okayama 700-8505, Japan
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2021, 10(24), 5800; https://doi.org/10.3390/jcm10245800
Submission received: 25 September 2021
/
Revised: 29 November 2021
/
Accepted: 8 December 2021
/
Published: 11 December 2021
(This article belongs to the Special Issue Orthopedic Treatment of Diseases and Fractures in Elderly)
Abstract
:Previous literature has provided conflicting results regarding the associations between early surgery and postoperative outcomes in elderly patients with distal femur fractures. Using data from the Japanese Diagnosis Procedure Combination inpatient database from April 2014 to March 2019, we identified elderly patients who underwent surgery for distal femur fracture within two days of hospital admission (early surgery group) or at three or more days after hospital admission (delayed surgery group). Of 9678 eligible patients, 1384 (14.3%) were assigned to the early surgery group. One-to-one propensity score matched analyses showed no significant difference in 30-day mortality between the early and delayed groups (0.5% versus 0.5%; risk difference, 0.0%; 95% confidence interval, −0.7% to 0.7%). Patients in the early surgery group had significantly lower proportions of the composite outcome (death or postoperative complications), shorter hospital stays, and lower total hospitalization costs than patients in the delayed surgery group. Our results showed that early surgery within two days of hospital admission for geriatric distal femur fracture was not associated with a reduction in 30-day mortality but was associated with reductions in postoperative complications and total hospitalization costs.
1. Introduction
The incidence of distal femur fracture increases markedly with age [1]. Elderly patients with distal femur fracture were reported to have similar demographic characteristics and outcomes to elderly patients with hip fracture [2]. Elderly patients with distal femur fracture have poor postoperative outcomes because of their many perioperative complications caused by preoperative immobilization [2,3], which is similar to the case for elderly patients with hip fracture [4]. In elderly patients with hip fracture, systematic reviews have demonstrated the beneficial effects of early surgery on postoperative outcomes, including mortality and postoperative complications [5,6].
However, prior studies have provided mixed results regarding the association between the timing of surgery and postoperative mortality in elderly patients with distal femur fracture. Several observational studies found that early surgery was associated with reduced mortality [7,8,9], while other studies showed no such association [10,11,12,13]. One of the reasons for these conflicting results may be small patient numbers used in previous studies (n = 88 to 392) [2,3,7,8,9,10,11,12]. In addition, confounding factors may not have been sufficiently adjusted for because of the small numbers of patients.
The purpose of the present study was to examine the associations between early surgery and postoperative outcomes in elderly patients with distal femur fractures using data from a nationwide inpatient database. We hypothesized that early surgery is associated with a lower in-hospital mortality, a lower proportion of postoperative complications, and lower medical costs. By clarifying these associations, we suggest a better treatment strategy for geriatric distal femur fracture that will improve patient outcomes and the social economy of healthcare.
2. Materials and Methods
This study was a retrospective cohort study using a national administrative inpatient database under the REporting of studies Conducted using Observational Routinely-collected Data (RECORD) statement reporting guidelines [14]. This study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of The University of Tokyo (approval number: 3501-(3); 25 December 2017). The requirement for informed consent was waived because of the anonymous nature of the data.
2.1. Data Source
We used the Japanese Diagnosis Procedure Combination inpatient database under the management of the Ministry of Health, Labour, and Welfare, which includes administrative claims data and discharge abstracts from more than 1600 acute-care hospitals and covers approximately 90% of all tertiary emergency hospitals in Japan [15]. The database includes information on age, sex, body weight, body height, smoking history, level of consciousness at admission, home medical care use, location before hospital admission, ambulance use, diagnoses recorded with International Classification of Diseases Tenth Revision (ICD-10) codes, treatments recorded with Japanese medical procedure codes, medications administered, discharge status, and hospitalization costs [15]. The diagnoses at admission, comorbidities at admission, and complications during hospitalization are recorded in the database. The attending physicians are required to report objective evidence for their diagnoses for the purpose of cost reimbursement because the diagnostic records are linked to a payment system [15]. In a validation study of the database, the recorded procedures had a high sensitivity and specificity, while the recorded diagnoses had a high specificity and moderate sensitivity [16]. We also used facility information and statistics data from the Survey of Medical Institutions 2015 [17]. We combined these data with the data from the Japanese Diagnosis Procedure Combination inpatient database using specific hospital identifiers. The Survey of Medical Institutions data included the hospital type (academic hospital, teaching hospital, or tertiary emergency hospital) and the number of hospital beds.
2.2. Patient Selection
We searched the database and included patients who: (i) were admitted for distal femur fracture (ICD-10 code, S724), (ii) underwent surgery for distal femur fracture during hospitalization, and (iii) were discharged between April 2014 and March 2019. We excluded patients who: (i) were less than 60 years of age, (ii) were transferred from another hospital, (iii) had subsequent admission for distal femur fracture during the study period, (iv) were admitted to hospitals that could not be linked with data from the Survey of Medical Institutions 2015, (v) were admitted for open distal femur fracture (ICD-10 code, S7241), (vi) were treated with external fixation, (vii) had non-union, (viii) had bone tumor, and (ix) underwent surgery beyond 12 days after hospital admission.
2.3. Main Exposure
The main exposure was timing to surgery after hospital admission. We divided the eligible patients into an early surgery group (surgery within two days of hospital admission) and a delayed surgery group (surgery at three or more days after hospital admission). We defined the timing for early surgery as within two days of hospital admission, because this was considered representative timing for surgery in previous studies on distal femur fracture and hip fracture [7,8,10,18].
2.4. Outcomes
The primary outcome was the all-cause 30-day in-hospital mortality. Patients discharged alive within 30 days of hospital admission were considered alive at 30 days. The 30-day observation period was the common follow-up period used in previous studies [2,19]. The secondary outcomes were all-cause in-hospital mortality, composite outcome of death or postoperative complications during hospitalization, length of hospital stay, length of time from surgery to discharge, and total hospitalization costs [19]. The composite outcome was defined as death during hospitalization or at least one postoperative complication in the post-admission complication diagnoses detected by relevant ICD-10 codes (listed in Supplementary Materials Table S1) [20]. Length of hospital stay was defined as the duration of hospital admission to hospital discharge. The exchange rate for total hospitalization costs was set at 1 US dollar to 110 Japanese yen.
2.5. Covariates
The covariates were age; sex; body mass index at admission; smoking history; level of consciousness at admission using the Japan Coma Scale, which is well correlated with the Glasgow Coma Scale [21]; home medical care use; admission from nursing home; ambulance use, admission on a weekend (Friday to Sunday); calendar year; comorbidities according to the ICD-10 codes (listed in Supplementary Materials Table S2), Charlson comorbidity index [22]; ICD-10-based trauma mortality prediction score [23]; intensive care unit or high care unit use at admission; fracture type of periprosthetic fracture; operative method used for distal femur fracture; and hospital characteristics. We comprehensively selected these covariates as confounders based on existing literature with clinical judgment [18,19].
Body mass index (kg/m2) was categorized as <18.5, 18.5–24.9, 25.0–29.9, ≥30.0, and missing data. An ICD-10-based trauma mortality prediction score was developed and validated by Wada et al. [23]; it has achieved a high accuracy for mortality prediction in the Japanese Diagnosis Procedure Combination inpatient database. Patients were considered to have severe medical conditions at admission if they were admitted to an intensive care unit or a high care unit on the day of admission [18]. We defined hospital volume as the number of operations for distal femur fracture during the study period.
2.6. Statistical Analysis
A propensity score matching method was applied to compare the outcomes between the early and delayed surgery groups. First, we performed a multivariable logistic regression analysis to estimate the propensity scores for patients receiving early surgery using all covariates listed in Table 1. Briefly, we performed one-to-one nearest-neighbor matching without replacement using a caliper width set at 20% of the standard deviation for the estimated propensity scores [24]. Absolute standardized differences were calculated for all covariates in the unmatched and matched cohorts to confirm the balance of the covariate distributions between the early and delayed surgery groups. The imbalance in the covariate distributions was considered negligible when the absolute standardized differences between the two groups were less than 10% [24]. The propensity score matching was performed using the PSMATCH2 module of STATA (Edwin Leuven and Barbara Sianesi) [25]. We calculated risk differences and their 95% confidence intervals for the outcomes using a generalized linear model with the identity link function and with cluster-robust standard errors for individual hospitals as clusters.
Subsequently, we performed the following four subgroup analyses to estimate the heterogeneity of the treatment effect on the primary outcome in the propensity score-matched cohort: patients with admission on the weekend, patients with a Charlson comorbidity index ≥1, patients with a hospital size < 400 beds, and patients with a hospital volume <4.
Categorical variables were presented as numbers and percentages, while continuous variables were presented as means and standard deviations (SDs). All p-values were two-sided and values of p < 0.05 were considered statistically significant. All analyses were performed using the STATA/MP 16.0 software (StataCorp, College Station, TX, USA).
3. Results
After the application of the exclusion criteria, a total of 9678 patients were eligible for the study (Figure 1). The mean (SD) age was 81.1 (9.3) years, and 90.3% were women. Among the eligible patients, 1384 (14.3%) were assigned to the early surgery group and 8294 (85.7%) were assigned to the delayed surgery group. Surgery on day 4 after hospital admission (15.4%) was the most common timing (Figure 2). The mean (SD) timing for surgery after hospital admission was 1.8 (0.4) days in the early surgery group and 5.9 (2.3) days in the delayed surgery group.
Table 1 shows the patient characteristics in the two groups before and after propensity score matching. Before propensity score matching, patients in the early surgery group tended to have intensive care unit or high care unit use at admission and be admitted to a hospital with a high hospital volume, while patients in the delayed surgery group tended to have admission on the weekend, comorbidities of rheumatic diseases and renal dysfunction, and a higher Charlson comorbidity index. The proportions of periprosthetic fracture were 6.6% in the early surgery group and 8.1% in the delayed surgery group. After propensity score matching, the patient characteristics were found to be well-balanced between the two groups (Supplementary Materials Figure S1). The propensity score distributions before and after propensity score matching are shown in Supplementary Materials Figures S2 and S3.
Table 2 shows the outcomes before and after propensity score matching. Before propensity score matching, 30-day mortality in the early and delayed surgery groups was 0.9% and 0.5%, respectively. After propensity score matching, there was no significant difference in 30-day mortality between the two groups (risk difference, 0.0%; 95% CI, −0.7% to 0.7%). There was no significant difference in in-hospital mortality between the two groups. The composite outcome was significantly less common in the early surgery group compared with the delayed surgery group (13.5% versus 17.1%; risk difference, −3.7%; 95% CI, −6.5% to −0.9%). Regarding postoperative complications, acute coronary syndrome was significantly less frequent in the early surgery group compared with the delayed surgery group (Supplementary Materials Table S3). Patients in the early surgery group had a significantly shorter length of hospital stay (risk difference, −8.4 days; 95% CI, −11.8 to −5.0 days), a shorter length of time from surgery to discharge (risk difference, −4.5 days; 95% CI, −7.9 to −1.0 days), and lower total hospitalization costs (risk difference, −2101 US dollars; 95% CI, −2991 to −1212 US dollars) than patients in the delayed surgery group.
The four subgroup analyses showed no significant differences in 30-day mortality between the two groups and the results were consistent with those in the main analysis (Table 3).
4. Discussion
The present study was a large-scale investigation of the effectiveness of early surgery for distal femur fracture in elderly patients using data from a nationwide inpatient database in Japan. The results showed that early surgery within two days of hospital admission was not associated with a reduction in 30-day mortality but was significantly associated with reductions in postoperative complications, length of hospital stay, and total hospitalization costs.
Early surgery did not have clinical effectiveness in reducing 30-day mortality. This finding was consistent with that of previous studies on geriatric distal femur fracture that assessed outcomes with covariate adjustment using a multivariable logistic regression model [10,12]. However, the finding that early surgery in elderly patients with distal femur fracture did not reduce 30-day mortality differed from results gained in elderly patients with hip fracture [19].
Regardless of the timing of surgery, the 30-day mortality in the present study was less than 1% and much lower than the rates of 3% to 8% seen in previous studies on geriatric distal femur fracture [2,7,10,11]. However, the low 30-day mortality was consistent with the 30-day mortality rates in geriatric hip fracture studies that used data from large databases (0.6% to 1.0% in Japan; 5.8% to 6.5% in Canada; 6.3% in Sweden) [3,18,19,20]. In our cohort with a very low 30-day mortality, early surgery did not have clinical effectiveness for 30-day mortality.
Early surgery was associated with better clinical outcomes and lower costs, as demonstrated by the lower frequency of the composite outcome, shorter length of hospital stay, and lower total hospitalization costs. Early surgery was associated with fewer postoperative complications, consistent with a previous study [8]. Elderly patients are vulnerable and the prevention of postoperative complications may be associated with favorable functional outcomes and improved quality of life [26]. Similar to the case for geriatric hip fracture patients, this may have arisen because early surgery in geriatric distal femur fracture patients enabled the early initiation of rehabilitation, increasing the chance for better functional recovery, resulting in fewer postoperative complications, and having positive impacts on hospital stay and total hospitalization costs [18,27]. The mechanism for the benefits of early surgery on functional outcomes should be addressed in future studies.
The present study had several strengths. To the best of our knowledge, this was the first large-scale study to demonstrate the effectiveness of early surgery for distal femur fracture in elderly patients on in-hospital mortality, postoperative complications, length of hospital stay, and total hospitalization costs. The study was able to compensate for limitations of previous studies that arose from their small sample sizes and low external validity due to the use of single-center data. Targeting the performance of surgery within two days of admission represents a significant change in practice, because 85.7% of the patients in the study did not receive surgery within two days. The early timing of surgery in hip fracture is already recognized worldwide as a quality indicator for the assessment of hospital performance; therefore, the results of the present study may inform existing distal femur fracture care guidelines and policies.
This study also has some limitations. First, this study may have immortal time biases for the two time points—namely, the time from hospital admission to surgery and time after early discharge [28]. In this study, time from hospital admission to surgery was considered immortal because the performance of surgery implied that the patients survived until surgery. Therefore, the delayed surgery group had a guaranteed survival advantage over the early surgery group because of the immortal time from hospital admission to surgery. Meanwhile, time after early discharge was considered immortal because patients who were discharged alive were considered to remain alive at 30 days in this study. Therefore, the early surgery group had a guaranteed survival advantage over the delayed surgery group because of the immortal time after early discharge. Second, this observational study using a real-world database unmeasured confounding variables. Thus, individual surgeons decided the timing of surgery according to the criteria in their own settings, which would lead to confounding by indication. We attempted to control for possible confounding factors described in previous reports, including covariates of patient and surgeon-hospital characteristics. However, we were unable to obtain detailed data on the distal femur fracture type and the time from injury to admission. We assumed that the day of injury was the same as the day of hospital admission. The appropriate timing for surgery needs to be further investigated with better time resolution, such as hours, instead of number of days from admission to surgery in future studies. Third, the Japanese Diagnosis Procedure Combination inpatient database does not contain links to data after discharge. Therefore, we could not evaluate the outcomes after longer follow-up (90 or 365 days). Previous studies showed that delayed surgery by more than two days in geriatric distal femur fracture patients was significantly associated with increased 1-year mortality [7,8]. In addition, the assumption that patients who were discharged alive within 30 days of hospital admission remained alive at 30 days could lead to misclassification for 30-day in-hospital mortality. Therefore, further studies are needed to examine the effectiveness of early surgery on mortality with longer follow-up periods. Fourth, there is a lack of external validity because all the data were obtained from a Japanese database. It remains unclear whether the results of the study can be generalized to other countries with different patient characteristics and healthcare systems.
5. Conclusions
This nationwide observational study suggested that early surgery within two days of hospital admission was not associated with a reduction in 30-day mortality in patients with geriatric distal femur fracture. However, early surgery was associated with decreased postoperative complications and lower total hospitalization costs.
Supplementary Materials
The following are available online at https://www.mdpi.com/article/10.3390/jcm10245800/s1, Figure S1: Distribution of propensity scores before matching, Figure S2: Distribution of propensity scores after matching; Figure S3: Kissing plot in propensity score matching, Table S1: International Classification of Diseases Tenth Revision (ICD-10) codes for complications, Table S2: International Classification of Diseases Tenth Revision (ICD-10) codes for comorbidities, Table S3: Postoperative complications in the original unmatched cohort and matched cohort.
Author Contributions
Conceptualization, N.Y., H.O., Y.T., M.N., Y.S. and T.N.; methodology, N.Y., H.O., Y.T. and T.Y.; software, H.O.; formal analysis, H.O., N.Y. and Y.T.; resources, H.O.; data curation, Y.M. and H.M.; writing—original draft, N.Y., H.O. and Y.T.; writing—review and editing, N.Y., H.O. and H.Y.; visualization, N.Y., H.O. and Y.T.; supervision, H.Y.; project administration, H.O.; funding acquisition, H.Y. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by grants from the Ministry of Health, Labour and Welfare, Japan (21AA2007 and 20AA2005) and the Ministry of Education, Culture, Sports, Science and Technology, Japan (20H03907).
Institutional Review Board Statement
This study was performed in accordance with the amended Declaration of Helsinki and was approved by the Institutional Review Board of The University of Tokyo (approval number: 3501-(3); 25 December 2017).
Informed Consent Statement
The review board waived the requirement for informed consent because of the anonymous nature of the data. No information describing individual patients, hospitals, or treating physicians was obtained.
Data Availability Statement
The datasets analyzed during the current study are not publicly available owing to contracts with the hospitals providing data to the database.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Lundin, N.; Huttunen, T.T.; Enocson, A.; Marcano, A.I.; Felländer-Tsai, L.; Berg, H.E. Epidemiology and mortality of pelvic and femur fractures-a nationwide register study of 417,840 fractures in Sweden across 16 years: Diverging trends for potentially lethal fractures. Acta Orthop. 2021, 92, 323–328. [Google Scholar] [CrossRef]
- Jennison, T.; Divekar, M. Geriatric distal femoral fractures: A retrospective study of 30 day mortality. Injury 2019, 50, 444–447. [Google Scholar] [CrossRef] [PubMed]
- Wolf, O.; Mukka, S.; Ekelund, J.; Möller, M.; Hailer, N.P. How deadly is a fracture distal to the hip in the elderly? An observational cohort study of 11,799 femoral fractures in the Swedish Fracture Register. Acta Orthop. 2021, 92, 40–46. [Google Scholar] [CrossRef]
- Carpintero, P.; Caeiro, J.R.; Carpintero, R.; Morales, A.; Silva, S.; Mesa, M. Complications of hip fractures: A review. World J. Orthop. 2014, 5, 402–411. [Google Scholar] [CrossRef]
- Welford, P.; Jones, C.S.; Davies, G.; Kunutsor, S.K.; Costa, M.L.; Sayers, A.; Whitehouse, M.R. The association between surgical fixation of hip fractures within 24 hours and mortality: A systematic review and meta-analysis. Bone Jt. J. 2021, 103, 1176–1186. [Google Scholar] [CrossRef] [PubMed]
- Klestil, T.; Röder, C.; Stotter, C.; Winkler, B.; Nehrer, S.; Lutz, M.; Klerings, I.; Wagner, G.; Gartlehner, G.; Nussbaumer-Streit, B. Impact of timing of surgery in elderly hip fracture patients: A systematic review and meta-analysis. Sci. Rep. 2018, 8, 13933. [Google Scholar] [CrossRef] [Green Version]
- Myers, P.; Laboe, P.; Johnson, K.J.; Fredericks, P.D.; Crichlow, R.J.; Maar, D.C.; Weber, T.G. Patient Mortality in Geriatric Distal Femur Fractures. J. Orthop. Trauma. 2018, 32, 111–115. [Google Scholar] [CrossRef]
- Moloney, G.B.; Pan, T.; Van Eck, C.F.; Patel, D.; Tarkin, I. Geriatric distal femur fracture: Are we underestimating the rate of local and systemic complications? Injury 2016, 47, 1732–1736. [Google Scholar] [CrossRef]
- Streubel, P.N.; Ricci, W.M.; Wong, A.; Gardner, M.J. Mortality after distal femur fractures in elderly patients. Clin. Orthop. Relat. Res. 2011, 469, 1188–1196. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Nyholm, A.M.; Palm, H.; Kallemose, T.; Troelsen, A.; Gromov, K.; DFDB Collaborators. No association between surgical delay and mortality following distal femoral fractures. A study from the danish fracture database collaborators. Injury 2017, 48, 2833–2837. [Google Scholar] [CrossRef]
- Larsen, P.; Ceccotti, A.A.; Elsoe, R. High mortality following distal femur fractures: A cohort study including three hundred and two distal femur fractures. Int. Orthop. 2020, 44, 173–177. [Google Scholar] [CrossRef]
- Brogan, K.; Akehurst, H.; Bond, E.; Gee, C.; Poole, W.; Shah, N.N.; McChesney, S.; Nicol, S. Delay to surgery does not affect survival following osteoporotic femoral fractures. Injury 2016, 47, 2294–2299. [Google Scholar] [CrossRef] [PubMed]
- Smolle, M.A.; Hörlesberger, N.; Maurer-Ertl, W.; Puchwein, P.; Seibert, F.J.; Leithner, A. Periprosthetic fractures of hip and knee-A morbidity and mortality analysis. Injury 2021, 52, 3483–3488. [Google Scholar] [CrossRef] [PubMed]
- Benchimol, E.I.; Smeeth, L.; Guttmann, A.; Harron, K.; Moher, D.; Petersen, I.; Sørensen, H.T.; von Elm, E.; Langan, S.M. The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. PLoS Med. 2015, 12, e1001885. [Google Scholar] [CrossRef] [PubMed]
- Yasunaga, H. Real World Data in Japan: Chapter II the Diagnosis Procedure Combination Database. Ann. Clin. Epidemiol. 2019, 1, 76–79. [Google Scholar] [CrossRef]
- Yamana, H.; Moriwaki, M.; Horiguchi, H.; Kodan, M.; Fushimi, K.; Yasunaga, H. Validity of diagnoses, procedures, and laboratory data in Japanese administrative data. J. Epidemiol. 2017, 27, 476–482. [Google Scholar] [CrossRef]
- The Ministry of Health, Labour and Welfare, Japan: Statistical Surveys 2015. Available online: https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/open_data.html (accessed on 24 September 2021).
- Sasabuchi, Y.; Matsui, H.; Lefor, A.K.; Fushimi, K.; Yasunaga, H. Timing of surgery for hip fractures in the elderly: A retrospective cohort study. Injury 2018, 49, 1848–1854. [Google Scholar] [CrossRef]
- Pincus, D.; Ravi, B.; Wasserstein, D.; Huang, A.; Paterson, J.M.; Nathens, A.B.; Kreder, H.J.; Jenkinson, R.J.; Wodchis, W.P. Association Between Wait Time and 30-Day Mortality in Adults Undergoing Hip Fracture Surgery. JAMA 2017, 318, 1994–2003. [Google Scholar] [CrossRef] [Green Version]
- Ogawa, T.; Yoshii, T.; Moriwaki, M.; Morishita, S.; Oh, Y.; Miyatake, K.; Nazarian, A.; Shiba, K.; Okawa, A.; Fushimi, K.; et al. Association between Hemiarthroplasty vs Total Hip Arthroplasty and Major Surgical Complications among Patients with Femoral Neck Fracture. J. Clin. Med. 2020, 9, 3203. [Google Scholar] [CrossRef]
- Shigematsu, K.; Nakano, H.; Watanabe, Y. The eye response test alone is sufficient to predict stroke outcome—Reintroduction of Japan Coma Scale: A cohort study. BMJ Open. 2013, 3, e002736. [Google Scholar] [CrossRef] [Green Version]
- Charlson, M.E.; Pompei, P.; Ales, K.L.; MacKenzie, C.R. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J. Chronic. Dis. 1987, 40, 373–383. [Google Scholar] [CrossRef]
- Wada, T.; Yasunaga, H.; Yamana, H.; Matsui, H.; Matsubara, T.; Fushimi, K.; Nakajima, S. Development and validation of a new ICD-10-based trauma mortality prediction scoring system using a Japanese national inpatient database. Inj. Prev. 2017, 23, 263–267. [Google Scholar] [CrossRef] [PubMed]
- Austin, P.C. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat. Med. 2009, 28, 3083–3107. [Google Scholar] [CrossRef] [Green Version]
- Edwin, L.; Barbara, S. PSMATCH2: Stata Module to Perform Full Mahalanobis and Propensity Score Matching, Common Support Graphing, and Covariate Imbalance Testing; Statistical Software Components: Boston, MA, USA, 2003. [Google Scholar]
- Kammerlander, C.; Riedmüller, P.; Gosch, M.; Zegg, M.; Kammerlander-Knauer, U.; Schmid, R.; Roth, T. Functional outcome and mortality in geriatric distal femoral fractures. Injury 2012, 43, 1096–1101. [Google Scholar] [CrossRef] [PubMed]
- Brox, W.T.; Roberts, K.C.; Taksali, S.; Wright, D.G.; Wixted, J.J.; Tubb, C.C.; Patt, J.C.; Templeton, K.J.; Dickman, E.; Adler, R.A.; et al. The American Academy of Orthopaedic Surgeons Evidence-Based Guideline on Management of Hip Fractures in the Elderly. J. Bone Jt. Surg. Am. 2015, 97, 1196–1199. [Google Scholar] [CrossRef]
- Lévesque, L.E.; Hanley, J.A.; Kezouh, A.; Suissa, S. Problem of immortal time bias in cohort studies: Example using statins for preventing progression of diabetes. BMJ 2010, 340, 907–911. [Google Scholar] [CrossRef] [Green Version]
Figure 1.
Flow chart for patient inclusion and exclusion.
Figure 2.
Days from hospital admission to surgery. The dotted line shows the border between the early and delayed surgery groups.
Figure 2.
Days from hospital admission to surgery. The dotted line shows the border between the early and delayed surgery groups.
Table 1.
Patient characteristics before and after propensity score matching.
| Unmatched Cohort | Matched Cohort | |||||
|---|---|---|---|---|---|---|
| Early Surgery (≤2 Days) n = 1384 | Delayed Surgery (≥3 Days) n = 8294 | ASD | Early Surgery (≤2 Days) n = 1382 | Delayed Surgery (≥3 Days) n = 1382 | ASD | |
| Age (years), mean (SD) | 81.3 (9.4) | 81.1 (9.3) | 2.3 | 81.3 (9.4) | 81.4 (9.5) | 0.7 |
| Female sex, n (%) | 1227 (88.7) | 7515 (90.6) | 6.4 | 1225 (88.6) | 1214 (87.8) | 2.6 |
| Body mass index (kg/m2), n (%) | ||||||
| <18.5 | 264 (19.1) | 1495 (18.0) | 2.7 | 264 (19.1) | 262 (19.0) | 0.4 |
| 18.5–24.9 | 718 (51.9) | 4384 (52.9) | 2 | 716 (51.8) | 701 (50.7) | 2.2 |
| 25.0–29.9 | 235 (17.0) | 1478 (17.8) | 2.2 | 235 (17.0) | 252 (18.2) | 3.2 |
| ≥30 | 64 (4.6) | 399 (4.8) | 0.9 | 64 (4.6) | 69 (5.0) | 1.7 |
| Missing | 103 (7.4) | 538 (6.5) | 3.8 | 103 (7.5) | 98 (7.1) | 1.4 |
| Smoking history, n (%) | ||||||
| Non-smoker | 1189 (85.9) | 7080 (85.4) | 1.6 | 1187 (85.9) | 1182 (85.5) | 1.0 |
| Current/past smoker | 96 (6.9) | 602 (7.3) | 1.3 | 96 (6.9) | 99 (7.2) | 0.8 |
| Missing | 99 (7.2) | 612 (7.4) | 0.9 | 99 (7.2) | 101 (7.3) | 0.6 |
| Unconscious at admission, n (%) | 186 (13.4) | 979 (11.8) | 4.9 | 184 (13.3) | 180 (13.0) | 0.9 |
| Home medical care use, n (%) | 107 (7.7) | 693 (8.4) | 2.3 | 107 (7.7) | 106 (7.7) | 0.3 |
| Admission from nursing home, n (%) | 246 (17.8) | 1281 (15.4) | 6.3 | 245 (17.7) | 232 (16.8) | 2.5 |
| Ambulance use, n (%) | 796 (57.5) | 5129 (61.8) | 8.8 | 795 (57.5) | 794 (57.5) | 0.1 |
| Admission on weekend, n (%) | 182 (13.2) | 3444 (41.5) | 67.1 | 182 (13.2) | 183 (13.2) | 0.2 |
| Calendar year, n (%) | ||||||
| 2014 | 282 (20.4) | 1862 (22.4) | 5.1 | 282 (20.4) | 274 (19.8) | 1.4 |
| 2015 | 284 (20.5) | 1750 (21.1) | 1.4 | 284 (20.5) | 311 (22.5) | 4.8 |
| 2016 | 280 (20.2) | 1633 (19.7) | 1.4 | 280 (20.3) | 250 (18.1) | 5.5 |
| 2017 | 278 (20.1) | 1595 (19.2) | 2.2 | 276 (20.0) | 291 (21.1) | 2.7 |
| 2018 | 260 (18.8) | 1454 (17.5) | 3.3 | 260 (18.8) | 256 (18.5) | 0.7 |
| Comorbidities, n (%) | ||||||
| Dementia | ||||||
| Absent | 861 (62.2) | 5239 (63.2) | 2 | 860 (62.2) | 855 (61.9) | 0.7 |
| Mild | 261 (18.9) | 1702 (20.5) | 4.2 | 260 (18.8) | 273 (19.8) | 2.4 |
| Moderate/severe | 262 (18.9) | 1353 (16.3) | 6.9 | 262 (19.0) | 254 (18.4) | 1.5 |
| Myocardial infarction | 4 (0.3) | 80 (1.0) | 8.6 | 4 (0.3) | 5 (0.4) | 0.9 |
| Chronic heart failure | 69 (5.0) | 609 (7.3) | 9.8 | 69 (5.0) | 68 (4.9) | 0.3 |
| Peripheral vascular disease | 11 (0.8) | 98 (1.2) | 3.9 | 11 (0.8) | 14 (1.0) | 2.2 |
| Cerebrovascular disease | 120 (8.7) | 783 (9.4) | 2.7 | 120 (8.7) | 115 (8.3) | 1.3 |
| Chronic pulmonary disease | 39 (2.8) | 286 (3.4) | 3.6 | 39 (2.8) | 38 (2.7) | 0.4 |
| Rheumatic disease | 44 (3.2) | 436 (5.3) | 10.3 | 44 (3.2) | 37 (2.7) | 2.5 |
| Peptic ulcer | 40 (2.9) | 264 (3.2) | 1.7 | 40 (2.9) | 41 (3.0) | 0.4 |
| Mild liver dysfunction | 46 (3.3) | 389 (4.7) | 7 | 46 (3.3) | 40 (2.9) | 2.2 |
| Diabetes mellitus without complications | 225 (16.3) | 1571 (18.9) | 7.1 | 224 (16.2) | 197 (14.3) | 5.1 |
| Diabetes mellitus with complications | 21 (1.5) | 239 (2.9) | 9.3 | 21 (1.5) | 23 (1.7) | 1 |
| Hemiplegia | 14 (1.0) | 57 (0.7) | 3.5 | 14 (1.0) | 15 (1.1) | 0.8 |
| Renal dysfunction | 28 (2.0) | 307 (3.7) | 10.1 | 28 (2.0) | 41 (3.0) | 5.6 |
| Malignancy | 37 (2.7) | 277 (3.3) | 3.9 | 37 (2.7) | 35 (2.5) | 0.8 |
| Severe liver dysfunction | 3 (0.2) | 9 (0.1) | 2.7 | 3 (0.2) | 4 (0.3) | 1.8 |
| Charlson comorbidity index | 0.7 (1.0) | 0.9 (1.1) | 17.9 | 0.7 (1.0) | 0.7 (0.9) | 1.1 |
| Trauma mortality prediction score, mean (SD) | 3.6 (1.5) | 3.5 (1.5) | 4.5 | 3.6 (1.5) | 3.6 (1.7) | 1.1 |
| ICU/HCU at admission, n (%) | 59 (4.3) | 195 (2.4) | 10.7 | 57 (4.1) | 56 (4.1) | 0.4 |
| Periprosthetic fracture, n (%) | 92 (6.6) | 672 (8.1) | 5.6 | 92 (6.7) | 94 (6.8) | 0.6 |
| Operation, n (%) | ||||||
| Treatment with plating | 772 (55.8) | 4813 (58.0) | 4.5 | 772 (55.9) | 799 (57.8) | 3.9 |
| Treatment with nailing | 462 (33.4) | 2684 (32.4) | 2.2 | 460 (33.3) | 429 (31.0) | 4.8 |
| Treatment with arthroplasty | 9 (0.7) | 36 (0.4) | 2.9 | 9 (0.7) | 6 (0.4) | 3 |
| Treatment unknown | 141 (10.2) | 761 (9.2) | 3.4 | 141 (10.2) | 148 (10.7) | 1.7 |
| Academic hospital, n (%) | 219 (15.8) | 1206 (14.5) | 3.6 | 219 (15.8) | 216 (15.6) | 0.6 |
| Teaching hospital, n (%) | 1064 (76.9) | 6298 (75.9) | 2.2 | 1062 (76.8) | 1047 (75.8) | 2.6 |
| Tertiary hospital, n (%) | 447 (32.3) | 2226 (26.8) | 12 | 445 (32.2) | 457 (33.1) | 1.9 |
| Hospital beds, n (%) | ||||||
| <200 | 196 (14.2) | 1307 (15.8) | 4.5 | 196 (14.2) | 202 (14.6) | 1.2 |
| 200–399 | 528 (38.2) | 3335 (40.2) | 4.2 | 527 (38.1) | 532 (38.5) | 0.7 |
| 400–599 | 463 (33.5) | 2398 (28.9) | 9.8 | 462 (33.4) | 458 (33.1) | 0.6 |
| 600–799 | 160 (11.6) | 900 (10.9) | 2.2 | 160 (11.6) | 152 (11.0) | 1.8 |
| >800 | 37 (2.7) | 354 (4.3) | 8.7 | 37 (2.7) | 38 (2.7) | 0.4 |
| Hospital volume, n (%) | 5.0 (2.4) | 4.5 (2.4) | 19.1 | 5.0 (2.4) | 5.0 (2.6) | 1.0 |
ASD, absolute standardized difference; ICU, intensive care unit; HCU, high care unit. Body mass index was calculated as weight in kilograms divided by height in meters squared.
Table 2.
Outcomes in the original unmatched cohort and matched cohort.
| Unmatched Cohort | Matched Cohort | |||||
|---|---|---|---|---|---|---|
| Early Surgery (≤2 Days) n = 1384 | Delayed Surgery (≥3 Days) n = 8294 | Early Surgery (≤2 Days) n = 1382 | Delayed Surgery (≥3 Days) n = 1382 | Risk Difference (95% CI) | p-Value | |
| Primary outcome | ||||||
| 30-day mortality, n (%) | 12 (0.9) | 41 (0.5) | 12 (0.9) | 12 (0.9) | 0.0 (−0.7 to 0.7) | >0.999 |
| Secondary outcomes | ||||||
| In-hospital mortality, n (%) | 21 (1.5) | 106 (1.3) | 21 (1.5) | 21 (1.5) | 0.0 (−0.9 to 0.9) | >0.999 |
| Composite outcome, n (%) | 187 (13.5) | 1383 (16.7) | 186 (13.5) | 237 (17.1) | −3.7 (−6.5 to −0.9) | 0.007 |
| Length of hospital stay (days), mean (SD) | 42 (42) | 53 (36) | 42 (42) | 50 (36) | −8.4 (−11.8 to −5.0) | <0.001 |
| Length of time from surgery to discharge (days), mean (SD) | 41 (42) | 48 (36) | 41 (42) | 45 (36) | −4.5 (−7.9 to −1.0) | 0.011 |
| In-hospital costs (US dollars), mean (SD) | 16,099 (10,721) | 18,844 (10,803) | 16,101 (10,729) | 18,202 (9859) | −2101 (−2991 to −1212) | <0.001 |
Hospital costs were calculated using the exchange rate of 1 US dollar = 110 Japanese yen.
Table 3.
Subgroup analyses for 30-day mortality in the propensity score-matched cohort.
| Early Surgery | Delayed Surgery | Risk Difference (95% CI) | p-Value | |
|---|---|---|---|---|
| Admission on weekend | ||||
| 30-day mortality, n (%) | 1/182 (0.5) | 2/183 (1.1) | −0.5 (−2.4 to 1.3) | 0.571 |
| Charlson comorbidity index ≥ 1 | ||||
| 30-day mortality, n (%) | 4/652 (0.6) | 6/670 (0.9) | −0.3 (−1.2 to 0.7) | 0.552 |
| Hospital size < 400 beds | ||||
| 30-day mortality, n (%) | 5/723 (0.7) | 8/734 (1.1) | −0.4 (−1.4 to 0.6) | 0.415 |
| Hospital volume < 4 | ||||
| 30-day mortality, n (%) | 5/548 (0.9) | 5/578 (0.9) | −0.0 (−1.1 to 1.2) | 0.933 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Yamamoto, N.; Ohbe, H.; Tomita, Y.; Yorifuji, T.; Nakajima, M.; Sasabuchi, Y.; Miyamoto, Y.; Matsui, H.; Noda, T.; Yasunaga, H. Associations between Early Surgery and Postoperative Outcomes in Elderly Patients with Distal Femur Fracture: A Retrospective Cohort Study. J. Clin. Med. 2021, 10, 5800. https://doi.org/10.3390/jcm10245800
AMA Style
Yamamoto N, Ohbe H, Tomita Y, Yorifuji T, Nakajima M, Sasabuchi Y, Miyamoto Y, Matsui H, Noda T, Yasunaga H. Associations between Early Surgery and Postoperative Outcomes in Elderly Patients with Distal Femur Fracture: A Retrospective Cohort Study. Journal of Clinical Medicine. 2021; 10(24):5800. https://doi.org/10.3390/jcm10245800
Chicago/Turabian StyleYamamoto, Norio, Hiroyuki Ohbe, Yosuke Tomita, Takashi Yorifuji, Mikio Nakajima, Yusuke Sasabuchi, Yuki Miyamoto, Hiroki Matsui, Tomoyuki Noda, and Hideo Yasunaga. 2021. "Associations between Early Surgery and Postoperative Outcomes in Elderly Patients with Distal Femur Fracture: A Retrospective Cohort Study" Journal of Clinical Medicine 10, no. 24: 5800. https://doi.org/10.3390/jcm10245800
APA StyleYamamoto, N., Ohbe, H., Tomita, Y., Yorifuji, T., Nakajima, M., Sasabuchi, Y., Miyamoto, Y., Matsui, H., Noda, T., & Yasunaga, H. (2021). Associations between Early Surgery and Postoperative Outcomes in Elderly Patients with Distal Femur Fracture: A Retrospective Cohort Study. Journal of Clinical Medicine, 10(24), 5800. https://doi.org/10.3390/jcm10245800
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
