TY - JOUR
T1 - Proximal Femur Fractures in the Elderly—A Novel Modality to Predict Mortality
T2 - The Neutrophil-to-Lymphocyte Ratio
AU - Marom, Omer
AU - Paz, Inbar
AU - Segal, David
AU - Topaz, Guy
AU - Abelson, Nitzan
AU - Tavdi, Alex
AU - Behrbalk, Refael
AU - Palmanovich, Ezequiel
AU - Ohana, Nissim
AU - Yaacobi, Eyal
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Background: The assessment and identification of elderly patients with proximal femur fractures (PFF) who are at high risk of postoperative mortality may influence the treatment decision-making process. The purpose of this study was to determine whether the neutrophil-to-lymphocyte ratio (NLR) could be used to predict postoperative mortality in the elderly population. Methods: A four-year retrospective cohort study of electronic medical records was conducted at a single tertiary care hospital between 2015 and 2018. Data from 1551 patients aged 65 years and older who underwent surgical treatment for PFF were collected and analyzed. The data included complete blood counts at admission, demographic information, underlying illnesses, type of surgery, and postoperative mortality and complications during the first year of follow-up. A survival analysis model was utilized. Results: The mean age was 90.76 ± 1.88 years, 1066 (68.7%) women. Forty-four (2.8%) patients experienced postoperative infection. A higher NLR0 was independently associated with higher all-cause mortality rates in patients who underwent surgical treatment for PFF (p = 0.041). Moreover, the mean NLR0 value was higher when the death occurred earlier after surgery (p < 0.001). Conclusions: When combined with other clinical and laboratory findings, NLR0 levels may serve as a potentially valuable, inexpensive, and reliable prognostic biomarker to improve risk stratification for elderly patients who are candidates for PFF surgery. Furthermore, with additional research, we could potentially develop a treatment algorithm to identify patients at high risk of postoperative mortality.
AB - Background: The assessment and identification of elderly patients with proximal femur fractures (PFF) who are at high risk of postoperative mortality may influence the treatment decision-making process. The purpose of this study was to determine whether the neutrophil-to-lymphocyte ratio (NLR) could be used to predict postoperative mortality in the elderly population. Methods: A four-year retrospective cohort study of electronic medical records was conducted at a single tertiary care hospital between 2015 and 2018. Data from 1551 patients aged 65 years and older who underwent surgical treatment for PFF were collected and analyzed. The data included complete blood counts at admission, demographic information, underlying illnesses, type of surgery, and postoperative mortality and complications during the first year of follow-up. A survival analysis model was utilized. Results: The mean age was 90.76 ± 1.88 years, 1066 (68.7%) women. Forty-four (2.8%) patients experienced postoperative infection. A higher NLR0 was independently associated with higher all-cause mortality rates in patients who underwent surgical treatment for PFF (p = 0.041). Moreover, the mean NLR0 value was higher when the death occurred earlier after surgery (p < 0.001). Conclusions: When combined with other clinical and laboratory findings, NLR0 levels may serve as a potentially valuable, inexpensive, and reliable prognostic biomarker to improve risk stratification for elderly patients who are candidates for PFF surgery. Furthermore, with additional research, we could potentially develop a treatment algorithm to identify patients at high risk of postoperative mortality.
KW - comorbidity
KW - femur
KW - fracture
KW - mortality
KW - neutrophil-to-lymphocyte ratio
UR - http://www.scopus.com/inward/record.url?scp=85146522240&partnerID=8YFLogxK
U2 - 10.3390/jcm12020456
DO - 10.3390/jcm12020456
M3 - Article
C2 - 36675385
AN - SCOPUS:85146522240
SN - 2077-0383
VL - 12
JO - Journal of Clinical Medicine
JF - Journal of Clinical Medicine
IS - 2
M1 - 456
ER -