DOI: https://doi.org/10.21203/rs.3.rs-1961246/v1
Objectives: The aim of this study was to define the risk factors affecting the prognosis of patients with acute traumatic spinal cord injury (tSCI), and to discuss the value of prognostic nutritional index (PNI) and controlling nutritional status (COUNT) score in predicting the prognosis of patients with acute tSCI.
Methods: We retrospectively analyzed the clinical data of 75 patients with acute tSCI. The optimal cutoff value was obtained through the receiver operating characteristic curve (ROC), and the value of PNI and COUNT score were 45.05 and 3.5 respectively. Patients were divided into high PNI groups and low PNI groups, high COUNT groups and low COUNT groups respectively based on cutoff values. The differences of outcome indexes such as American spinal injury association impairment scale (AIS), exercise score, Bathel index score and light touch score were analyzed, and the prognostic factors of tSCI patients were analyzed. A improved outcome was defined as improvement of AIS grade ≥ 1.
Results: Compared with the improvement group, the non-improvement group had lower serum albumin and PNI, higher COUNT score, longer hospital stay and higher postoperative infection rate (P < 0.05). PNI and COUNT score were closely related to the AIS grade (r = 0.629, P < 0.001; r = -0.855, P < 0.001). After adjusting for confounding factors, the odds ratios of PNI and COUNT score for predicting improved outcomes in patients with acute tSCI were 1.396 (95%CI: 1.141-1.709） and 0.284 (95%CI: 0.136-0.0.594）, respectively. The area under the curve (AUC) of PNI and count scores for predicting improved outcomes were 0.752 (95% CI: 0.641 ~ 0.862, P < 0.001) and 0.766 (95% CI: 0.654 ~ 0.879, P < 0.001), respectively.
Conclusion: PNI and count scores may be independent predictors of improved outcomes in patients with acute tSCI.
Traumatic spinal cord injury (tSCI) is a devastating disaster for patients and their families, often resulting in loss of independence and continued increase in mortality1. About 250,000-500,000 patients each year have spine cord injury(SCI) due to various causes, of which up to 90% of SCI patients are caused by traumatic causes, with lifetime medical costs ranging from $1.1 million to $4.7 million2,3. We found that the prognosis of tSCI patients with similar clinical manifestations and imaging manifestations is often quite different, and a simple and feasible prognostic indicator is needed to predict the prognosis of patients and guide treatment. In recent years, prognostic nutritional index (PNI) and controlling nutritional status (CONUT) scores have been reported as objective and easy-to-apply indicators for predicting the prognosis of patients with severe traumatic brain injury or cancer4,5. PNI was calculated from serum albumin and peripheral blood lymphocyte counts and was originally used to assess preoperative nutritional status, surgical risk, and postoperative complications in surgical patients. The COUNT score is calculated from serum albumin concentration, peripheral blood lymphocyte count, and total cholesterol and is an early screening tool for malnutrition. However, it is unclear that whether PNI and COUNT score could be used as prediction indexes for predicting outcomes in patients with acute tSCI. The purpose of this study was to identify the risk factors affecting the prognosis of patients with acute tSCI, and to study the value of PNI and COUNT scores in predicting the prognosis of patients with acute tSCI.
We retrospectively collected clinical data of newly diagnosed tSCI patients in the Second Affiliated Hospital of Chongqing Medical University from June 2015 to June 2020.
The inclusion criteria were as follows:
The exclusion criteria were follows:
The Ethics Committee of the Second Affiliated Hospital of Chongqing Medical University approved the project (no. 59/Ethics 2022) and all methods were performed in accordance with relevant guidelines and regulations. Informed consent was obtained from all patients prior to participation.
Data were collected on demographic characteristics (age, gender, etc.), tobacco use history, alcohol use history, medical history, surgical history and postoperative complications. Serum albumin, total cholesterol, total lymphocyte counts were obtained by automated test system systems Hitachi 7600 and BM2000. Body mass index (BMI) was calculated from the preoperative heights and weights of the patients, which were measured by our medical staff at admission. Follow-up was conducted by telephone, review of patient outpatient and inpatient medical records, and the deadline for follow-up was March 2022. The median follow-up time of patients was 26 (20.0, 35.0) months. Neurological outcomes were assessed by the American Spinal Injury Association impairment scale (AIS). The primary outcome was change in AISA Impairment Scale grade from admission to last follow-up (at least 1 year). Secondary outcomes were changes in motor scores, Bathel index scores and light touch scores at last follow-up.
PNI was calculated using the following formula: serum albumin (g/L) + 5 ´ total lymphocyte count (×109/L)7. CONUT scores were calculated from the serum albumin concentration, total blood cholesterol level, and total peripheral lymphocyte count (Table 1)4. The improvement of AIS grade at the last follow-up ≥1 grade was defined as improvement, or was defined as non-improvement. According to the receiver operating characteristic curve (ROC) at the last follow-up calculated the area under the curve (AUC) of the PNI and COUNT scores. Optimal cutoff values were calculated using Youden index maxima (sensitivity + specificity − 1).
Statistical analysis was performed using SPSS 25.0 software, continuous data were expressed as mean ± standard deviation (SD) or median (P25, P75), categorical data were expressed as frequency and percentage (%) express. Categorical variables were compared using chi-square test, adjusted chi-square test or Fisher’s exact test, and continuous variables were compared using Mann–Whitney U test or unpaired t-test. The ROC curve was drawn as a predictor, and the area under the curve (AUC) was used to evaluate the predicted value. The correlation between PNI, COUNT score and AIS grade was analyzed by Spearman correlation. Independent predictors of acute tSCI were determined by univariate and multivariate logistic regression, and odds ratios (OR) and 95% confidence intervals (CI) were calculated. All P values were on the 2 sides and significance was set at P < 0.05.
The patient characteristics table is shown in Table 2. A total of 75 patients were included in this study, after 5 who were lost to follow-up were excluded. The mean age was 52.69 (18-84), and 58(77.3%) patients were male. The median hospital stay was 17 days, and the mean BMI was 25.67, 64 (85.3%) patients underwent surgery after admission. Among the 75 patients, 31 (41.3%) smoked, and 23 (30.7%) drank alcohol. The comorbidities at admission were hypertension in 10 patients (13.3%), diabetes in 2 patients (2.7%), and coronary heart disease in 1 patient (1.3 %), 2 cases of COPD (2.7%), 2 cases of cerebral infarction (2.7%). A total of 3 cases (4.0%) had infection after operation, and they were cured after symptomatic treatment with antibiotics. At the last follow-up, a total of 3 patients (4.0%) died, including 1 patient who did not receive surgical treatment (AIS B, died 6 months after injury), and 2 patients who received surgical treatment (AIS A died 12 months after surgery; AIS D died 2 months after surgery). On admission, the AIS grades of the patients were grade A in 12 cases (16.0%), grade B in 10 cases (13.3%), grade C in 15 cases (20.0%), and grade D in 38 cases (50.7%), and 53 patients’ (70.7%) injured segment was cervical, 10 cases (13.3%) were thoracic, and 12 cases (16.0%) were lumbar.
According to the receiver operating characteristic (ROC) curve of the 75 tSCI patients at the last follow-up, the area under the ROC curve (AUC) of PNI and COUNT scores were 0.752 (P＜0.001) and 0.766 (P＜0.001), respectively. According to the Youden index, the optimal cutoff values of PNI and COUNT scores were 45.05 (95%CI 0.641-0.862) and 3.5 (95%CI 0.654-0.879), respectively (Figure 1). According to cutoff value, the patients were divided into high PNI group (≥45.05, 28 cases, 37.3%) and low PNI group (＜45.05, 47 cases, 62.7%), high COUNT group (≥3.5，44例，58.7%) and low COUNT group (＜3.5，31例，41.3%).
There was no significant difference in clinical characteristics between the high PNI group and the low PNI group (Table 3). While patients in the low CONUT group had a shorter hospital stay (P=0.042), a higher BMI index (P=0.034), and a higher motor score on admission (P=0.007) than those in the high COUNT group (Table 4). Statistical analysis showed the motor score, Barthel index score, light touch score, and improvement rate of AIS grade in the high PNI group at the last follow-up was better than that in the low PNI group, and the difference was statistically significant (P<0.05). The Barthel index score, light touch score and improvement rate of AIS grade in the low COUNT group was better than that in the high COUNT group, and the difference was statistically significant (P<0.05), and there was no significant difference in the changes in motor score (P=0.075), for details see Tables 5-6.
A total of 51 (68%) patients improved at last follow-up (AIS grade ≥1), of which 28 (90.3%) were in the low COUNT group and 26 (92.9%) in the high PNI group. After controlling for hospitalization days and postoperative infection factors, Spearman correlation analysis showed that PNI and COUNT scores were strongly correlated with AIS grades (r=0.629, P＜0.001; r=-0.620, P＜0.001). At the same time, there was also a strong correlation between PNI and COUNT scores (r=-0.855, P＜0.001), and the patients in the low PNI group and the high COUNT group had a large overlap (Table 7).
As shown in Table 8, compared with the improvement group, more patients with COUNT ≥ 3.5 and PNI＜45.05 were observed in the non-improvement group (P＜0.001). To explore the relationship between the last follow-up outcome and clinical characteristics, univariate analysis showed that compared with the improvement group, the patients in the non-improvement group had longer hospitalization days and higher postoperative infection rates (P＜0.05). The clinical characteristic factors with P＜0.2 were included in the multivariate Logistics regression equation. Because PNI and COUNT score had a strong correlation and were found to be complete intermediary variables after being included in the model, the models were established separately. The hospitalization days, drinking, COPD, postoperative infection, PNI or COUNT scores were included to construct multivariate Logistic regression analysis. The results showed that both PNI and COUNT scores were independent predictors of acute tSCI improvement (Tables 9-10), with adjusted odds ratios of 1.396 (95%CI: 1.141-1.709, P=0.001) and 0.284 (95%CI: 0.136-0.0.594, P=0.001).
The receiver operating characteristic (ROC) curve of improvement at last follow-up showed that PNI and COUNT scores had predictive value. The AUC of PNI and COUNT scores were 0.752 (95%CI 0.641-0.862, P＜0.001) and 0.766 (95%CI 0.654-0.879, P＜0.001), respectively, and the PNI cutoff value was 51.0% sensitive and 91.7% specific, the COUNT score was 54.9% sensitive and 87.5% specific (Figure 1). There was no statistical difference in the AUC comparing PNI and COUNT scores by Delong test (P=0.690).
This study analyzed the relationship between PNI and COUNT scores and prognosis in patients with acute tSCI. Our findings suggest that patients with higher COUNT scores and lower PNI at admission had a worse prognosis than patients with lower COUNT scores and higher PNI at last follow-up. Combining the ROC curve results of PNI and COUNT scores, we believe that PNI and COUNT scores at admission may be important independent predictors of patients with acute tSCI.
For tSCI patients, it is difficult to predict the recovery of the spinal cord because of the differences in the severity of functional loss and neurological damage caused by the complex trauma process at the time of injury, and the final outcome is determined by a series of complex biomechanical and physiological factors. The inconsistency caused by this injury makes predicting long-term prognostic outcomes from initial conditions a difficult task for clinicians. Therefore, the significance of predictive indicators is to enable clinicians to provide more accurate information to patients and their families, and to formulate specific rehabilitation plans based on expected results.
ASIA Impairment Scale and MRI have been widely used clinically as classic diagnostic methods for SCI patients, and they can be predicting prognosis simultaneously8,9. Aggressive cardiopulmonary management and early surgical intervention have also shown favorable outcomes10,11. And the use of biomarker concentrations in cerebrospinal fluid to assess the extent of spinal cord injury is an innovative and effective approach in recent years12. These methods are undoubtedly useful; however, their applicability and/or resolution are often limited. PNI and COUNT score as predicting prognosis are easy to obtain and operate, can make up for the shortcoming of the above methods to a certain extent. According to ROC curve, we get the clear cutoff value of PNI and COUNT. Researchers, clinicians and patients can easily predict the prognosis for each individual tSCI patient using this value. As mentioned above, the optimal cutoff value show high specificity and low sensitivity(PNI was 51.0% sensitive and 91.7% specific, COUNT score was 54.9% sensitive and 87.5% specific), which means that the accuracy is better when predicting a patient with a good prognosis by the cutoff value, and caution is required when the prognosis is bad. Similarly, when the prediction results of the two indicators are contradictory, the better outcome should be believed. subgroup analysis by cutoff value showed that higher PNI may be related to better motor score, light touch score, Barthel index score, AIS classification improvement rate; higher COUNT score may be related to worse light touch score, Barthel index score, AIS classification improvement rate. A retrospective cohort study of 154 patients with cervical spinal cord injury showed that individual nutritional status and BMI at admission may be independently associated with functional independence measure (FIM) efficacy13. Low albumin levels have been reported to be closely associated with poor prognosis in patients with cervical spinal cord injury14. In this study, BMI and albumin were included in the analysis, and the results showed that PNI and COUNT scores had better predictive effects than they.
Research in recent decades has yielded substantial evidence immune-nutritional status plays an important role in the prognosis of SCI patients 13-16. Immune-nutritional status are difficult to show from physical examination and imaging examinations, but biochemical indicators in blood tests may change in the acute phase of tSCI. PNI and COUNT scores are Immune-nutritional screening tools composed of different immune and nutritional biochemical indicators which have been widely used to predict the prognosis of patients with severe traumatic brain injury, cancer or spinal surgery4,5,17.PNI is calculated from albumin, lymphocytes, while COUNT score is calculated from albumin, lymphocytes, total cholesterol. Albumin is often considered a nutritional marker, but it may also exert neuroprotective effects by reducing cerebral edema and improving the metabolic activity of neurons18. Albumin is also a free radical scavenger, which can prevent lipid peroxidation, regulate the content of nitric oxide in microcirculation, inhibit endothelial cell apoptosis, and maintain normal microvascular permeability19,20. The results of this study showed that patients in the non-improvement group had lower serum albumin levels(P=0.002). Studies have shown that plasma cholesterol is also related to cell membrane cholesterol, which affects the fluidity of cell surface receptors and their ability to transmit transmembrane signals21. Coronary atherosclerotic heart disease (CHD) caused by dyslipidemia is known as the leading cause of death in patients with SCI22. As a immune biochemical indicator, B lymphocytes are transformed into plasma cells under antigen stimulation and produce antibodies that can specifically bind to the corresponding antigen, called immunoglobulins. Immunoglobulin G (IgG) can attenuate neuroinflammation and improves neurobehavioral recovery after cervical spinal cord injury23. Our study showed that there was no significant difference in lymphocyte and cholesterol between the non-improved group and the improved group (P=0.051, P=0.15), it may be due to insufficient number of cases and further research is needed to verify.
Based on the results of this study, it is reasonable to believe that the PNI and COUNT scores can be used to guide the risk stratification of patients with acute tSCI and provide early individualized treatment for patients with acute tSCI, while the current research on patients with acute tSCI is still blank. Combining these prognostic indicators with clinical guidelines for malnutrition risk to assess patient admissions and develop standardized individual protocols will be the focus of future therapeutic care. In the early care of patients with acute tSCI, appropriate measures should be taken to minimize the decline of immune-nutritional status in patients with acute tSCI. However, due to the irreversibility of negative nitrogen balance in patients with SCI, attempting to correct it by overfeeding may result in hypercapnia, hyperglycemia, uremia and hypertriglyceridemia24. In 2016, the Society of Critical Care Medicine (SCCM) and American Society for Parenteral and Enteral Nutrition (ASPEN) published guidelines for nutritional support in the adult critically ill population. They recommended the use of indirect calorimetry to determine energy requirements25. Studies have shown that for acute SCI patients, Weir is the best predictive equation, followed by Penn State formula, which can more accurately predict the energy requirements of acute SCI patients26. In the care of patients with acute tSCI, the decline of immune-nutritional status should be minimized in the early stage, the energy required by patients should be accurately calculated, early enteral nutrition should be promoted. During the rehabilitation process, attention should be paid to a sufficient and comprehensive diet to assist the clinical test results, and through daily testing and nutrition, promote the recovery of nutrition and immune function, and improve the rehabilitation effect.
We aware that our research may have some limitations. The first is we only measured and evaluated the nutritional status at admission, and did not evaluate the nutritional status of patients after surgery and discharge. The Second is the energy intake during hospitalization was not recorded. Moreover, this study is a single-center retrospective cohort study with relatively few cases. Additional validation through randomized controlled multicenter trials is warranted.
Higher PNI and lower COUNT scores were associated with improved prognosis in patients with acute tSCI and were independent prognostic factors in patients with acute tSCI. The PNI and COUNT scores may help predict the prognosis of patients with acute tSCI and develop more precise treatment regimens as readily available indicators.
Conflict of interest: The authors declare no conflicts of interest.
Funding: None.
Contributions: Z.Y.K. and S.C. provided ideas and design of the study. L.L. contributed to the acquisition of data. D.Z. performed the statistical analysis. Z.Q.W. wrote this manuscript. All authors read and approved the final manuscript.
Acknowledgments: None.
Ethics approval and consent to participate: The Ethics Committee of the Second Affiliated Hospital of Chongqing Medical University approved the project. The project complies with the National Institutes of Health guidelines.
Availability of data and materials: Datasets are available from the corresponding author on reasonable request.
Table 1 to 10 are available in the Supplementary Files section.