Is the Timing of Surgery a Sufficient Predictive Factor for Outcomes in Patients with Proximal Femur Fractures? A Systematic Review
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Screening and Selection Criteria
2.2. Quality Assessment
2.3. Data Abstraction
3. Results
3.1. Study Characteristics
3.2. Type of Fracture
3.3. Time to Surgery
3.4. Reason for Delaying Surgery and the Preoperative Medical Condition of the Patient
3.5. Mortality
3.6. Complications
3.7. Length of Stay
4. Discussion
5. Limitations and Suggestions for Further Research
6. Conclusions
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Author, Year of Publication, Country | Follow-Up | Sample Size | Extracapsular Fracture | Early Surgery Definition | Outcomes | Prolonged LOS for Delayed | Risk of Bias |
---|---|---|---|---|---|---|---|
Shah, 2015 Pakistan [9] | In-hospital | 190 | 100% | 48 h | In-hospital mortality/in-hospital complications | N/A | 6 |
Matassi, 2015 Italy [10] | 1 year | 132 | 48.50% | 48 h | 1-year mortality/in-hospital complications/LOS/post-op functional ability | − | 8 |
Dong, 2016 China [11] | 30 days | 28 | 15.62% | 48 h | 30-day mortality/30-day complications/LOS/post-op functional ability | + | 4 |
Utrilla, 2016 Spain [12] | 1 year | 628 | 62.89% | 48 h | In-hospital mortality/30-day mortality/3-month mortality/1-year mortality/complications | + | 7 |
Bennett, 2018 USA [13] | In-hospital | 841 | N/A | 48 h | In-hospital mortality/in-hospital complications | + | 6 |
Sasabuchi, 2018 Japan [14] | 30 days | 208,936 | 48.80% | 48 h | 30-day mortality/30-day complications | + | 7 |
Declarador, 2018 Singapore [15] | 1 year | 446 | 43.04% | 48 h | In-hospital mortality/1-year mortality/In-hospital complications | + | 7 |
Butler, 2019 Australia [16] | 1 year | 265 | N/A | 48 h | 30-day mortality/1-year mortality/in-hospital complications | N/A | 7 |
King, 2020 Australia [17] | 90 days | 84 | 55.95% | 48 h | In-hospital mortality/30-day mortality/3-month mortality/in-hospital complications | + | 7 |
Kilinc, 2020 Turkey [18] | 1 year | 443 | 51% | 48 h | 1-year mortality | N/A | 6 |
Gupta, 2021 India [19] | 1 year | 87 | 79.31% | 48 h | 1-year mortality | N/A | 8 |
Bhatti, 2021 USA [20] | In-hospital | 28,031 | N/A | 48 h | In-hospital mortality/in-hospital complications | N/A | 5 |
Kristan, 2021 Slovenia [21] | 1 year | 641 | 49.92% | 48 h | 30-day mortality/1-year mortality | N/A | 8 |
Fu, 2017 USA [22] | 30 days | 26,051 | N/A | 24 h | 30-day mortality/in-hospital complications | + | 7 |
Maheshwari, 2017 USA [23] | 1 year | 720 | N/A | 24 h | 1-year mortality | N/A | 6 |
Couto, 2018 Portugal [24] | In-hospital | 372 | 66.12% | 24 h | In-hospital mortality | N/A | 5 |
Nia, 2021 Austria [25] | 180 days | 1101 | 50.5% | 24 h | 30-day mortality/180-day mortality | N/A | 8 |
Lieten, 2021 Belgium [26] | >2 years | 840 | N/A | 24 h | In-hospital mortality/30-day mortality/in-hospital complications | + | 6 |
van Rijckevorsel, 2022 The Netherlands [27] | 30 days | 1803 | 44% | 24 h | In-hospital mortality/30-day mortality/in-hospital complications | + | 8 |
Liu, 2023 China [28] | >2 years | 763 | 43.9% | 24 h | 30-day mortality/3-month mortality/6 months mortality/in-hospital complications | − | 5 |
Study | Patient | In Hospital Mortality | Early Surgery (Hours) | Relative Risk | Confidence Interval | ||
---|---|---|---|---|---|---|---|
Early | Delayed | Early n (%) | Delayed n (%) | ||||
Shah, 2015 [9] | 138 | 52 | 2 (1.44) | 5 (9.61) | 48 | 6.6346 | 1.3281–33.1433; p = 0.0211 |
Lizaur-Utrilla, 2016 [12] | 180 | 448 | 1 (0.55) | 5 (1.11) | 48 | 1.9868 | 0.2337–16.8883; p = 0.5295 |
Bennett, 2018 [13] | 575 | 266 | 8 (1.39) | 15 (5.63) | 48 | 4.0531 | 1.7398–9.4420; p = 0.0012 |
Declarador, 2018 [15] | 144 | 302 | 0 (0) | 4 (1.32) | 48 | 4.3069 | 0.2334–79.4645; p = 0.3262 |
King, 2020 [17] | 17 | 11 | 0 (0) | 1 (9.09) | 48 | 4.5 | 0.1995–101.5223; p = 0.3441 |
Bhatti, 2021 [20] | 23,043 | 4419 | 375 (1.67) | 194 (4.39) | 48 | 2.6976 | 2.2616–3.2178; p < 0.0001 |
Couto, 2018 [24] | 92 | 280 | 5 (5.43) | 14 (5) | 24 | 0.92 | 0.3406–2.4849; p = 0.8694 |
Lieten, 2021 [26] | 517 | 288 | 19 (3.67) | 16 (5.56) | 24 | 1.5117 | 0.7655–2.9853; p = 0.2340 |
van Rijckevorsel, 2022 [27] | 1386 | 362 | 42 (3.03) | 13 (3.59) | 24 | 1.1851 | 0.6294–2.2312; p = 0.5989 |
Total | 26,092 | 6428 | 452 (1.73) | 267 (4.15) |
Study | Patient | 30-Day Mortality | Early Surgery (Hours) | Relative Risk | Confidence Interval | ||
---|---|---|---|---|---|---|---|
Early | Delayed | Early n (%) | Delayed n (%) | ||||
Dong, 2016 [11] | 18 | 10 | 2 (11.11) | 1 (10) | 48 | 0.9 | 0.0927–8.7343; p = 0.9276 |
Sasabuchi, 2018 [14] | 47,073 | 161,863 | 456 (0.96) | 1410 (0.87) | 48 | 0.8992 | 0.8095–0.9989; p = 0.0476 |
Butler, 2019 [16] | 170 | 95 | 1 (0.58) | 8 (8.42) | 48 | 14.3158 | 1.8179–112.7351; p = 0.0115 |
King, 2020 [17] | 17 | 11 | 0 (0) | 1 (9.09) | 48 | 4.5 | 0.1995–101.5223; p = 0.3441 |
Kristan, 2021 [21] | 345 | 263 | 16 (4.63) | 17 (6.46) | 48 | 1.3938 | 0.6912–2.8104; p = 0.3534 |
Fu, 2017 [22] | 5921 | 20,130 | 297 (5.01) | 1129 (5.61) | 24 | 1.1181 | 0.9872–1.2664; p = 0.0788 |
Nia, 2021 [25] | 611 | 189 | 26 (4.25) | 41 (21.69) | 24 | 5.0979 | 3.0376–8.5555; p < 0.0001 |
van Rijckevorsel, 2022 [27] | 1304 | 342 | 124 (9.5) | 33 (9.64) | 24 | 1.0147 | 0.6789–1.5167; p = 0.9432 |
Liu, 2023 [28] | 136 | 657 | 1 (0.73) | 9 (1.36) | 24 | 1.863 | 0.2341–14.8270; p = 0.5566 |
Total | 55,595 | 183,560 | 923 (1.66) | 2608 (1.42) |
Study | Patient | 1-Year Mortality | Early Surgery (Hours) | Relative Risk | Confidence Interval | ||
---|---|---|---|---|---|---|---|
Early (n) | Delayed (n) | Early n (%) | Delayed n (%) | ||||
Matassi, 2015 [10] | 33 | 99 | 6 (18.18) | 23 (23.23) | 48 | 1.2778 | 0.5698–2.8652; p = 0.5519 |
Lizaur-Utrilla, 2016 [12] | 180 | 448 | 26 (14.44) | 61 (13.61) | 48 | 0.9427 | 0.6161–1.4422; p = 0.7854 |
Declarador, 2018 [15] | 144 | 302 | 5 (3.47) | 28 (9.27) | 48 | 2.6702 | 1.0528–6.7721; p = 0.0386 |
Butler, 2019 [16] | 170 | 95 | 16 (9.41) | 15 (15.78) | 48 | 1.6776 | 0.8687–3.2399; p = 0.1234 |
Kılınç, 2020 [18] | 212 | 231 | 69 (32.54) | 93 (40.25) | 48 | 1.237 | 0.9639–1.5874; p = 0.0948 |
Gupta, 2021 [19] | 17 | 45 | 1 (5.88) | 24 (53.3) | 48 | 9.0667 | 1.1364–72.3405; p = 0.0375 |
Kristan, 2021 [21] | 299 | 224 | 62 (20.73) | 56 (25) | 48 | 1.2056 | 0.8076–1.7999; p = 0.3603 |
Maheshwari, 2017 [23] | 284 | 436 | 41 (14.43) | 118 (27.06) | 24 | 1.8747 | 1.3581–2.5878; p = 0.0001 |
Liu, 2023 [28] | 124 | 561 | 13 (10.48) | 105 (18.71) | 24 | 1.7853 | 0.9718–3.2798; p = 0.0618 |
Total | 1463 | 2441 | 239 (16.33) | 523 (21.42) |
Study (Early Definition, h) | Patient Group | Follow-Up | Patient Group | Odds Ratio | Confidence Interval | ||
---|---|---|---|---|---|---|---|
Early (n) | Delayed (n) | Early (n) | Delayed (n) | ||||
URINARY TRACT INFECTIONS | |||||||
Shah et al. [9] | 138 | 52 | In-hospital | 4 | 4 | 2.7917 | 0.6717–11.6028; p = 0.1578 |
Declarador et al. [15] | 144 | 302 | In-hospital | 3 | 18 | 2.9789 | 0.8630–10.2819; p = 0.0842 |
Fu et al. [22] | 5921 | 20,130 | 30 days | 338 | 1127 | 0.9796 | 0.8644–1.1102; p = 0.7470 |
Lieten et al. [26] | 536 | 304 | In-hospital | 166 | 113 | 1.13187 | 0.9808–1.7730; p = 0.0670 |
Van Rijckevorsel [27] | 1428 | 375 | In-hospital | 124 | 29 | 0.8814 | 0.5784–1.3432; p = 0.5570 |
Liu et al. [28] | 137 | 666 | In-hospital | 5 | 74 | 3.3 | 1.3084–8.3231; p = 0.0114 |
DEEP VENOUS THROMBOSIS/PULMONARY EMBOLISM | |||||||
Shah et al. [9] | 138 | 52 | In-hospital | 0 | 1 | 8.068 | 0.3234–201.2431; p = 0.2033 |
Sasabuchi et al. [14] | 47,073 | 161,863 | 30 days | 170 | 718 | 1.2293 | 1.0397–1.4535; p = 0.0157 |
Declarador et al. [15] | 144 | 302 | In-hospital | 0 | 2 | 2.4043 | 0.1147–50.4087; p = 0.5720 |
Fu et al. [22] | 5921 | 20,130 | 30 days | 93 | 370 | 1.1734 | 0.9330–1.475; p = 0.1715 |
Liu et al. [28] | 137 | 666 | In-hospital | 1 | 9 | 1.863 | 0.2341–14.8270; p = 0.5566 |
WOUND INFECTION | |||||||
Shah et al. [9] | 138 | 52 | In-hospital | 3 | 3 | 2.7551 | 0.5380–14.1093; p = 0.2239 |
Fu et al. [22] | 5921 | 20,130 | 30 days | 58 | 250 | 1.2712 | 0.9539–1.6940; p = 0.1014 |
Lieten [26] | 536 | 304 | In-hospital | 11 | 9 | 1.4561 | 0.5965–3.5544; p = 0.4092 |
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Rădulescu, M.; Necula, B.-R.; Mironescu, S.A.; Roman, M.D.; Schuh, A.; Necula, R.-D. Is the Timing of Surgery a Sufficient Predictive Factor for Outcomes in Patients with Proximal Femur Fractures? A Systematic Review. J. Pers. Med. 2024, 14, 773. https://doi.org/10.3390/jpm14070773
Rădulescu M, Necula B-R, Mironescu SA, Roman MD, Schuh A, Necula R-D. Is the Timing of Surgery a Sufficient Predictive Factor for Outcomes in Patients with Proximal Femur Fractures? A Systematic Review. Journal of Personalized Medicine. 2024; 14(7):773. https://doi.org/10.3390/jpm14070773
Chicago/Turabian StyleRădulescu, Mihai, Bogdan-Radu Necula, Sandu Aurel Mironescu, Mihai Dan Roman, Alexander Schuh, and Radu-Dan Necula. 2024. "Is the Timing of Surgery a Sufficient Predictive Factor for Outcomes in Patients with Proximal Femur Fractures? A Systematic Review" Journal of Personalized Medicine 14, no. 7: 773. https://doi.org/10.3390/jpm14070773