Factors Associated with Delayed Inflammatory Recovery after Spinal Surgery without Surgical Site Infection: A Retrospective Study

Article Information

Hideaki Imabayashi1*, Atsushi Miyake2, Kazuhiro Chiba2

1Department of Orthopedic Surgery, Tokyo Saiseikai Central Hospital, Tokyo, Japan

2Department of Orthopedic Surgery, National Defense Medical College, Saitama, Japan

*Corresponding Author: Hideaki Imabayashi, Department of Orthopedic Surgery, Tokyo Saiseikai Central Hospital, Mita 1-4-17, Minato Ward, Tokyo 108-0073, Japan

Received: 30 January 2022; Accepted: 07 February 2022; Published: 18 February 2022


Hideaki Imabayashi, Atsushi Miyake, Kazuhiro Chiba

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Background: We have previously reported ten effective serological indicators of surgical site infection (SSI) in the perioperative period after spinal surgery. However, the false-positive fractions of these markers were 0.15-0.39 which frequencies were not negligible. These mean the delays of surgical inflammatory recoveries without SSI. This study aimed to identify and classify the factors associated with these delays.

Methods: This retrospective study enrolled 320 patients who underwent spinal surgery for causes other than infectious spondylitis without surgical site infection. Demographic data, preoperative serological data, operative times, and operative methods were examined by multivariate regression for each SSI indicator and classified into related groups.

Results: Nine significantly associated factors, age, malignancy, preoperative total protein, albumin, white blood cell count, albumin/globulin ratio, C-reactive protein, operation time, and use of spinal instrumentation were found. We classified the patients into three groups according to their preoperative nutritional status, immune-inflammation status, and surgical procedure. Malnutrition, high CRP and WBC, older age, and malignancy might be related to delays in surgical recovery without SSI; therefore, a single indicator may have limited capability in detecting SSI.

Conclusions: We have to recognize the several causes to retard surgical inflammatory recovery. Improved preoperative conditions and less invasive surgery may decrease delays and improve the accuracy of SSI indicators.


Delayed Inflammatory Recovery, Malnutrition, Preoperative Condition, Spine Surgery, Surgical Site Infection

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Article Details

1. Introduction

Surgical site infection (SSI) is a major complication of spinal surgery, and its prevention and early detec- tion are of utmost importance [1-3]. After spinal surgery in patients without SSI, lymphocyte counts rapidly decreased to less than 1000/µL on posto- perative days 1 and 2, then gradually increased to over 1000/µL by postoperative day 4 and returned to preoperative levels in 3 weeks. Neutrophil counts rapidly increase, peaking on postoperative days 1 and 2, then gradually decreasing on day 4 and norma- lizing in 2–3 weeks [3-5]. We previously reported ten effective serological indicators, four indicators were white blood cell (WBC) count, neutrophil count,

neutrophil-to-lymphocyte ratio (NLR), and C-reac- tive protein (CRP) levels on postoperative day 7 [6]. For the ratio of serological cell counts between perio- perative periods, significant differences were obser- ved among six items, namely lymphocyte ratio from preoperative day to postoperative day 7 (LRp7), NLR ratio from preoperative day to postoperative day 7 (NLRRp7), neutrophil ratio from postoperative days 2 to 7 (NR27), lymphocyte ratio from postoperative days 2 to 7 (LR27), NLR ratio from postoperative days 2 to 7 (NLRR27), and CRP ratio from posto- perative days 2 to 7 (CR27) [6]. In terms of accuracy, the area under the curve (AUC) for these indicators was 0.711 to 0.825, specificities were 0.61 to 0.89, which indicates relatively high accuracy. The false- positive fractions, calculated as “1-specificity”, were 0.11 to 0.39, indicating delayed surgical inflamm- atory recovery without SSI. In actual clinical settings, false-positive cases are commonly encounered after surgery, presenting a diagnostic conundrum [6, 7]. The present study aimed to identify factors associated with delayed surgical inflammatory recovery and to utilize these results in accurately diagnosing SSI.

2. Methods

2.1 Study design and subjects

This retrospective study included 419 consecutive patients who underwent spinal surgery at a university hospital between 2012 and 2016. We excluded all patients that were administered unplanned antimicr- obial agents, except for prophylactic use, on the day of surgery and subsequently on day 1 after surgery, based on the recommendations of the Centers for Disease Control and Prevention [8]. Further, we excluded all cases with missing serological data. SSI was defined according to the criteria of the Centers for Disease Control and Prevention. The diagnosis was made by the attending surgeon based on the need for debridement, blood cultures that tested positive for infectious agents, or drainage of the surgical wou- nd within 4 weeks [8]. Initially, 419 cases were regis- tered, of which nine cases were excluded for the use of unplanned antimicrobial agents without SSI and 81 cases were excluded for missing values. Finally, 329 patients were included in the study. The research was performed in accordance with the ethical standards of our institute (Approval No. 3042).

2.2 Leucocyte data

White blood cell and differential counts were measured preoperatively and on postoperative days 1, 2, and 7. A lymphocyte count < 1000/µL was defined as lymphopenia. An automated cell counter (XN- 3100; Sysmex Corporation, Kobe, Japan) was used to determine the absolute white blood cell count and the percentage of neutrophils and lymphocytes. The neutrophil/lymphocyte ratio was also calculated.

2.3 Calculating the number for positive SSI indicators

If positive SSI indicators were met, 1 point was assigned. We calculated the total number of positive indicators in the SSI and non-SSI groups.

2.4 Data collection

We collected data regarding the age and sex, preoperative serologic parameters such as albumin (ALB pre), total protein (TP pre), globulin (GLB pre), albumin/globulin ratio (AGR pre), C-reactive protein (CRP pre), operation time (Op time), and

operative bleeding (Op bleeding). We also collected data on malignancies, malignant tumor surgery, emergency procedures, and spinal instrumentation. Surgical intervention was classified into three ordinal scales as follows: scale 1 included operations without spinal instrumentation, such as laminoplasty and laminectomy; scale 2, included one level of spinal fusion with instrumentation; and scale 3, comprised further invasive spinal fusions with instrumentation at more than one level.

2.5 Statistical analysis

Data are presented as numbers for categorical variables, and median and range for continuous varia- bles. Correlation was assessed using the correlation ratio (η2) for interval and ratio variables and Cramér’s measure of association (V) for nominal variables. Factors with a high η2 (>0.15) and high Cramér’s V (> 0.15) were selected for multivariate logistic regression analysis to identify the association with each serological indicator. The areas under the (AUC) receiver operating characteristic (ROC) curve analyses were calculated for each factor, and the cut- off value for each associated factor was also calculated. To summarize the significant factors associated with SSI indicators, we classified the associated factors. Statistical analyses were performed using SPSS for Windows (version 22.0; IBM Corp., Armonk, NY, USA), with statistical significance set at a two-tailed p-value of < 0.05.

3. Results

3.1 Patient characteristics

Among the 329 patients, 320 had no SSI (non-SSI group) and 9 developed SSI (SSI group). The non-

SSI group comprised 167 men and 153 women, with a median age of 68 years (range, 11-90 years). The median operative time was 166 min (range, 38-515 min), and the median intraoperative blood loss was 103 mL (range, 3-2475 mL). The surgical scale was as follows: Scale 1 was 147; Scale 2, 57; Scale 3, 116 cases; and spinal instrumentation, 174 cases. Figure 1 shows a histogram of the total number of positive indicators in the SSI and non-SSI groups. There were 50 cases in the non-SSI group. The median values were 2 points (range: 0-10) in the non-SSI group and 8 points (range: 4-10) in the SSI group. The cut-off value for SSI was 6 points (p < 0.001, specificity: 0.87, sensitivity: 0.89).

3.2 Factors associated with SSI indicators

The factors showing a strong correlation (η2 > 0.15 or Cramér’s V > 0.15) with SSI indicators are shown in Table 1 and further assessed using multivariate logistic regression (Table 2). Totally, nine associated factors were identified. The preoperative CRP (CRP pre: p = 0.004. Odds: 1.41) and operation time (Op time: p < 0.001, Odds: 1.005) for SSI indicator of in the relation to WBC cell counts at postoperative day 7, using spinal instrumentation (Spinal instru- mentation: p = 0.004, Odds: 3.63), preoperative AGR (AGR pre: p = 0.001, Odds: 0.167) and operation time (Op time: p = 0.002, Odds: 1.005) for SSI indicator in relation to Neutrophil cell counts at day 7 postoperatively, preoperative total protein (TP pre: p

= 0.007,Odds: 0.552), preoperative AGR (AGR pre: p = 0.002, Odds: 0.259) and operation time (Op time: p < 0.001, Odds: 1.007) for NLR at day 7 postoperatively, using spinal instrumentation (Spinal instrumentation: p = 0.001, Odds: 3.179), preopera-tive WBC (WBC pre: p = 0.010, Odds: 1.0001) and preoperative albumin (ALB pre: p = 0.045, Odds: 0.581) for CRP at postoperative day 7. Operation time (Op time: p<0.001, odds: 1.006) for SSI indi- cator in the relation to NLR ratio from preoperative day to postoperative day 7 (NLRRp7), preoperative WBC count (WBC pre: p = 0.015, odds: 1.0001), and preoperative CRP (CRP pre: p = 0.040, odds: 1.223) for neutrophil cell ratio from postoperative days 2 to 7 (NR27). Preoperative albumin (ALB pre: p = 0.011, odds: 0.542) for lymphocyte cell ratio from postop- erative days 2 to 7 (LR27), preoperative total protein (TP pre: p < 0.001, odds: 0.442), and preoperative CRP (CRP pre: p = 0.009, odds: 1.299) for NLR ratio from postoperative days 2 to 7 (NLRR27), age (p < 0.001, odds: 1.035), and malignancy (p = 0.010,

odds: 2.581) on postoperative days 2 to 7 (CR27).

The cut-off values for the associated factors are shown in Table 3. The maximum cut-off values were as follows, CRP pre was 0.5 µg/dL, Op time was 240 mins, WBC pre was 7500 /µL. The minimum cut-off values were: AGR pre, 1.4; ALB pre, 3.7 g/dL; and TP pre, 6.4 g/dL. The cut-off age was 73 years. We categorized the nine associated factors into three groups: the first group included preoperative factors such as nutritional status, including TP pre and ALB pre. The second group included preoperative immu- ne-inflammation status including age, malignancy, WBC pre, CRP pre, and AGR pre. The first and second groups were preoperative patient-associated factors. The third group was operative procedure, which included operative time and spinal instrum- entation.


Figure 1: Histogram of non-SSI and SSI groups for the number of positive SSI indicators.

The values over 0.15 are described. The grey labels are exceptions due to the direct relationship between associated factors and SSI indicators. WBC pre: preoperative white blood cell count; NLR pre: preoperative neutrophil to lymphocyte ratio; Neutrophil pre: preoperative neutrophil count; Lymphocyte pre: preoperative lymphocyte count; PLT pre: preoperative platelet counts; CRP pre: preoperative C-reactive protein; ALB pre: preoperative albumin value; TP pre: preoperative total protein value; GLB pre: preoperative globulin value; AGR pre: preoperative albumin/globulin ratio; Op time: operation time; Op bleeding: operation bleeding.

Table 1: Correlation using the correlation ratio (η2) and Cramér’s measure of association (V).

Table icon

WBC, white blood cells; NLR, neutrophil/lymphocyte ratio; CRP, C-reactive protein; LRp7, lymphocyte ratio from preoperative day to postoperative day 7; NLRRp7: NLR ratio from preoperative day to postoperative day 7; NR27: neutrophil ratio from postoperative days 2 to 7; LR27: lymphocyte ratio from postoperative days 2 to 7; NLRR27: NLR ratio from postoperative days 2 to 7, CR27: CRP ratio from postoperative days 2 to 7; AUC: area under the curve. WBC pre: preoperative white blood cell count, CRP pre: preoperative C-reactive protein, ALB pre: preoperative albumin value, TP pre: preoperative total protein value, AGR pre: preoperative albumin/globulin ratio, Op time: operation time.

Table 2: Multivariate logistic regression analysis for each SSI indicator.

Table icon

WBC, white blood cells; NLR, neutrophil/lymphocyte ratio; CRP, C-reactive protein; LRp7, lymphocyte ratio from preoperative day to postoperative day 7; NLRRp7: NLR ratio from preoperative day to postoperative day 7; NR27: neutrophil ratio from postoperative days 2 to 7; LR27: lymphocyte ratio from postoperative days 2 to 7; NLRR27: NLR ratio from postoperative days 2 to 7, CR27: CRP ratio from postoperative days 2 to 7; AUC: area under the curve. WBC pre: preoperative white blood cell count, CRP pre: preoperative C-reactive protein, ALB pre: preoperative albumin value, TP pre: preoperative total protein value, AGR pre: preoperative albumin/globulin ratio, Op time: operation time.

Table icon

Table 3: Cut-off values for associated factors were determined using receiver operating characteristic (ROC) curve analyses.

4. Discussion

Some articles showed the original SSI indicator, but this was mainly a single criterion. Postoperative lym- phopenia (lymphocyte counts below 1000/µL) is an effective indicator of SSI [3-5]. Iwata et al. reported that the cut-off value for lymphocyte counts indi- cating SSI was 1180/µL on postoperative day 4 (sensitivity, 90.9%; specificity, 65.4%) and 1090/µL

at day 7 (sensitivity, 63.6%; specificity, 78.5%) [9, 10]. The re-descending lymphocytes (sensitivity 55%, specificity 81%) and re-ascending neutrophils (sensitivity 46%, specificity 93%) compared to the values on days 1 and 4 postoperatively were indi- cators of SSI [11]. For each criterion, there was a false position fraction (FPF) the same as “1-speci- ficity,” which meant the delay of surgical inflame- matory’ recovery without SSI: this current study is the only article to investigate these delays.

We found ten indicators and the best combination with the highest accuracy of area under the curve (AUC) for receiver operating characteristic (ROC) curve analyses [6]. In the current study (Figure 1), we found that only 50 patients had negative SSI indi- cators, 270 patients had one or more positive indi- cators without SSI, with a median value of 2 points. Most of the patients with SSI had six or more positive indicators. Although each indicator’s accur- acy was different and giving 1 point equally for each positive SSI indicator included problems, patients with less than six points might have a high possibility of delayed surgical recovery without SSI. These results indicate that a single indicator has limited capacity in detecting SSI, and preoperative status influences surgical inflammatory recovery.

4.1 Factors associated with SSI indicators

These factors were categorized using principal comp- onent (PC) analysis, but PC analysis was inadequate for classification (Kaiser-Meyer-Olkin measure of sampling adequacy: 0.489 < 0.5). It may be difficult to classify patients without surgical intervention, and we categorized the patients into two groups based on their preoperative nutritional status and immune- inflammation status. Nutritional status plays a key role in SSI and wound healing [12-14]. Malnutrition prolongs wound healing by promoting fibroblast proliferation and collagen synthesis [12]. For pre- operative albumin (ALB pre), some articles reported that the cut-off value of ALB pre for SSI was 3.5 g/dL [15, 16]. In our results, 3.7 g/dL was the cut-off value for SSI indicators, which means ALB pre < 3.7 g/dL can easily induce delays in CRP and lymphocyte recovery after surgery (Table 3). We consider that ALB pre < 3.7 g/dL might be in yellow light with caution for SSI.

The current study shows that malnutrition affects blood cell reactions during spinal surgery. T cells, which are lymphocytes, are highly influenced by nutrient uptake from the environment. In states of severe malnutrition, T-cell survival, proliferation, and inflammatory cytokine production are all decreased, as are T-cell glucose uptake and metabolism [17, 18]. Thus, immune cells themselves are affected by malnutrition and are related to delayed operative inflammatory recovery. Immune-inflammation status included factors such as age, malignancy, WBC pre-, CRP pre-, and AGR pre. Aging is associated with a state of immunosuppression related to inflammation [19]. “Inflammaging” is a state of chronic, low-level systemic inflammation in the absence of clinically defined infection and is one of the consequences of aging in humans [19]. The current study, which was conducted on participants over 73 years of age, may induce a delay in CRP recovery. Neoplastic immu- nity, which is strongly influenced by innate and adaptive immunity, acts actively with malignant tumors. The microenvironment of cancer and inflam- mation are closely related. Inflammation related to cancer can also be immunosuppressive [20-22].

High WBC pre-and CRP pre- counts directly indicate preoperative inflammation. WBC > 7500/µL, CRP pre > 0.5 µg/dL are not high values, but indicate a significant possibility of delayed surgical recovery. AGR assesses levels of albumin and globulin, which constitute the principal protein comp- onents of human serum. Albumin reflects nutritional status, while globulin plays a key role in immunity and inflammation [23]. AGR is widely used as a prognostic indicator in several human cancers [24- 27]. Inflammatory conditions suppress albumin synthesis, which causes hypoalbuminemia and may increase the levels of globulin [28]. Thus, AGR is a useful biomarker of inflammation. AGR < 1.4, also induces a delay in neutrophil and NLR recovery. Surgical invasion may also affect the immune system and wound healing [29-31]. It can be assumed that a high degree of surgical invasion may cause immune- osuppression, and surgery using spinal instru- mentation is more invasive than surgery without instrumentation [31]. In summary, for preoperative patient condition, nutritional status with TP pre < 6.4 g/dL, ALB pre < 3.7 g/dL; immune-inflammation status with age >73 y/o, CRP pre > 0.5 µg/dL, WBC pre > 7500/µL, AGR pre < 1.4; mali-gnancy, and surgical invasion with operative time >240 min and using spinal instrumentation, are the nine associated factors which may cause delays in recovery from surgical inflammation. They indicate caution must be exercised for SSI. The present study was limited by its retrospective design and single-center setting. Additionally, we could not find effective factors associated with SSI indicators among the SSI and non-SSI groups, which was a direct analysis detect- ing the difference between SSI and non-SSI.

In conclusion, preoperative patient conditions such as malnutrition and high immune-inflammation status influence operative inflammatory recovery, which mimics infection even in the absence of SSI. Therefore, these factors may not always indicate SSI and, as such, must be interpreted with caution. Improving preoperative conditions such as nutritional status and immune-inflammation status may decrease the incidence of delayed recovery without SSI and may improve the accuracy of SSI indicators.

Conflict of Interest



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