Introduction
Approximately 112.5 million blood donations are annually collected worldwide, and the number of transfused red cells is 19.5 and 13.5 million units in China and the US, respectively.[1] Red cells are used to treat anemia; however, they are associated with side effects.[2] A decision regarding red-cell transfusion should be made when the benefits outweigh the risks and conserving red cell supplies and cost-effectiveness are also vital. Weighing the benefits and risks of transfusion triggered many clinical trials,[3-10] reviews,[11,12] and meta-analyses [13-17] to compare the liberal strategy with the restrictive strategy; however, debate still exists. The trigger and target hemoglobin levels for red-cell transfusion remain controversial, mainly owing to the diversity among patients. In a given clinical setting, a hemoglobin-based restrictive strategy may lead to oxygen supply/consumption imbalance, while a liberal strategy may result in exposure to unnecessary transfusion risk and exacerbation of blood shortage. Moreover, guidelines[18-20] and consensus[21] state the importance of an individualized approach and emphasize that a patient's medical status should be evaluated before making a transfusion decision. However, no guidelines suggest a practical way of objectively evaluating a patient's oxygen supply/consumption balance, and an individualized strategy has not been studied. Therefore, the optimal trigger and target hemoglobin levels for red-cell transfusion should be adjusted according to the factors, including but not limited to hemoglobin, as well as the other three equal-weighted factors in each patient. We proposed a score for individualized red-cell transfusion and conducted a pilot study in spine surgery. The results suggested that an objective evaluation of the oxygen supply/consumption balance and an individualized strategy with red-cell transfusion trigger and target could be achieved by application of the score and that the individualized strategy reduced the red cell requirement by 70% compared to that associated with a liberal strategy, without an increase in adverse events or prolonged length of hospital stay.[22] Then, we modified the previous score as the West-China-Liu's Score consisting of four factors (pulmonary function, cardiac function, and total body oxygen consumption, as well as the history of angina) for evaluating oxygen supply/consumption balance in total body and heart for individualized transfusion, and designed this trial to test the hypothesis that an individualized strategy can reduce the red cell requirement without compromising patient safety as compared with those associated with restrictive and liberal strategies in elective non-cardiac surgeries in adults.
Methods
Ethical approval
The study protocol was approved by the Biological-Medical Ethical Committee of the West China Hospital of Sichuan University on January 10, 2012 (No. 2012(1)) and was registered at http://www.clinicaltrials.gov (NCT01597232). This open-label, multicenter, randomized clinical trial was conducted in 35 centers (Supplementary files, https://links.lww.com/CM9/B419) in China. An independent data and safety monitoring board approved the study protocol and monitored the study. Written informed consent was obtained from all participants.
Patients
Clinicians approached consecutive patients undergoing elective non-cardiac surgery with an estimated blood loss >1000 mL or 20% blood volume. Eligible patients were aged ≥14 years, and their habitation was <2500 m above sea level. Patients were ineligible if they declined to receive transfusions, the American Society of Anesthesiologists (ASA) classification was V or VI, or if they had severe hematological disorders or hemoglobinopathies, tumor metastasis, or multiple tumors.
Randomization and masking
The participants were randomized in a 1:1:1 ratio into three groups, stratified by the participating centers using the Statistical Analysis System (SAS) (Cary, NC, USA) Windows 9.1 programming. The group allocation was concealed in a non-transparent envelope with only a five-digit number of study IDs on the surface. Envelopes were distributed to each center where eligible patients were randomly assigned a study ID in the sequence according to the order of the patients recruited.
The investigator and care providers, but not the participants, research nurses for follow-up, or statisticians, were aware of the treatment allocation. All authors vouched for the data and analysis and the study's fidelity to the protocol.
Intervention
Both hemoglobin concentrations and the West-China-Liu's Score (Table 1) were simultaneously measured for all patients before and immediately after surgery, 24 h after randomization, on the discharge day, whenever red-cell transfusion was considered, and after each transfusion during the study.
Table 1 -
West-China-Liu's Score.
| Points added |
Minimum FiO2 to keep SpO2 ≥95% (%) |
Adrenaline infusion rate (μg·kg−1·min−1) |
Core body temperature∗ (°C) |
History of angina |
| 0 |
≤35 |
Not required |
<38 |
No |
| +1 |
36–50 |
≤0.05 |
38–40 |
On exertion |
| +2 |
≥51 |
>0.05 |
>40 |
During normal daily living or at rest |
∗Core body temperature is measured at either nasopharynx, oropharynx, tympanic membrane, rectum, or esophagus. Axillary temperature with 0.5°C added is accepted as core temperature. The West-China-Liu's Score consists of four items: (1) Minimum inhaled oxygen concentration to keep pulse oxygen saturation ≥95%, a clinical indicator for pulmonary function because it is not safe to measure the lowest pulse oxygen saturation while inhaling air in patients with poor pulmonary function. (2) Infusing rate of adrenalin required to maintain an adequate cardiac output. Here, adrenalin could be replaced by other inotropics with equivalent potent infusing rates because different institutions or medical groups may use different drugs as the first line inotropic. (3) Core body temperature, a clinical indicator of total body oxygen consumption. (4) History of angina and its severity. This is integrated into the score because the heart, an organ extracting and consuming most oxygen from blood, is the most sensitive to the oxygen supply/consumption misbalance in the body. The West-China-Liu's Score consists of 6 basal points and four items with maximum added 2 points for each item. The final score is the sum of 6 basal points plus all added points. If the sum point is ≥10, the final score will be counted as 10. The final West-China Liu's-Score ranges from minimum 6 up to maximum 10. These five levels of the score match with the five levels of hemoglobin concentration from lowest 6 g/dL up to highest 10 g/dL, which grade individual patients for their red-cell transfusion trigger and target at that time. If the final score is equal to or smaller than the instant hemoglobin concentration, red cells will not be transfused; if the score is bigger than the instant hemoglobin concentration, red cells will be transfused and the units of red cells required is twice the difference of the score minus hemoglobin concentration, because one unit of red cells is collected from 200 mL whole blood in China and the hemoglobin level could be increased by approximately 0.5 g/dL in most adults.
If a patient's hemoglobin concentration dropped to <10.0 g/dL during or after surgery, the patient was randomly assigned to one of the following three groups. In the restrictive group, red cells were transfused according to Chinese transfusion guidelines,[19] which state that red cells are generally required with a hemoglobin concentrations <7 g/dL and not required with a hemoglobin concentration ≥10 g/dL. When the hemoglobin concentration is between 7 and 10 g/dL, red-cell transfusion decisions should be based on physicians’ judgment regarding patients’ cardiopulmonary reserve, oxygen consumption, and age. In the liberal group, the red-cell transfusion trigger was hemoglobin concentration <9.5 g/dL and target was to maintain hemoglobin concentration >10 g/dL. In the individualized group, red-cell transfusion was guided by the West-China-Liu's score [Table 1], which comprises six basal points and four items with a maximum of two points added for each. The final score is the sum of six basal points plus all added points (if the sum is greater than 10, the final score is counted as 10). Therefore, the final score ranges from 6 to 10. These five levels of the score match the five levels of hemoglobin concentration from the lowest 6 g/dL up to the highest 10 g/dL as both the red-cell transfusion trigger and target. If the final score is equal to or smaller than the current hemoglobin concentration, red cells will not be transfused; if the score is higher than the current hemoglobin concentration, red cell will be transfused and the units of red cells required are twice the difference of the score minus hemoglobin concentration because one unit of red cells is collected from 200 mL whole blood in China and elevates hemoglobin concentration by approximately 0.5 g/dL in most adults. Red blood cells were transfused within 30 min of the transfusion decision being made.
Research nurses telephoned the patients or legal guardians for follow-up. All data were collected via a web-based system, through which we monitored the participating centers for protocol adherence. Non-adherence to the protocol included red-cell transfusion without evaluation by the West-China-Liu's Score or red cells were transfused when hemoglobin level was >10 g/dL in all three groups or red cells were not transfused after the hemoglobin level was <7 g/dL in the restrictive group or <9.5 g/dL in the liberal group. Non-adherence data were included in the final analysis.
The principal investigator, study coordinator, and Office of Scientific Research at the West China Hospital were jointly responsible for all aspects of the study protocol and amendments. Ren Liao implemented the site monitoring. Three research nurses performed the data collection and follow-up.
Outcome measures
Two primary outcomes were evaluated in this study. First, the proportion of patients who received red blood cells (superiority test); and second, a composite of in-hospital complications (Supplementary Table 1, https://links.lww.com/CM9/B419) and all-cause mortality by day 30 (non-inferiority test).
The secondary outcomes included allogeneic blood cost and total in-hospital cost; all-cause mortality by day 60, day 180, and 1 year; in-hospital complications and infection rate; intensive care unit admission rate; incision healing status; and length of hospital stay after surgery.
Statistical analysis
The primary comparisons were between individualized and liberal and restrictive groups. In our pilot study,[22] 36.5% of the patients in the individualized group received red-cell transfusion, and we conservatively assumed a 20.0% difference between the two groups (36.5% vs. 56.5%) and then planned to recruit 1200 participants (400 in each group) (superiority test) for red-cell transfusion rate as the first primary outcome, and 4200 patients to allow for 3% of the non-inferiority margin of the composite rate between the individualized and restrictive groups as the second primary outcome with a difference of 2% (4% vs. 6%) within groups to be clinically important to achieve >99% power with an alpha level of 0.025 and an estimated 20% dropout rate. In December 2015, according to the original protocol plan, we reevaluated the sample size after 1200 patients were enrolled and found that 7659 patients would be needed for a non-inferiority margin of 3% points between the individualized and restrictive groups. The data and safety monitoring board approved a reduction in the recruitment of 1200 patients. This change resulted in an absolute change of approximately 4.5% in the non-inferiority margin of the composite rate.
All analyses followed the intention-to-treat principle and were performed using SAS 9.4. Continuous variables were presented as means ± standard deviations or medians (interquartile ranges), as appropriate. Categorical variables were presented as n (percentage). We calculated the risk difference and odds ratio and used the chi-square test to compare the primary outcomes among the three groups. The significance level was set at 2.5% to control for the type I error rate for the two primary comparisons. We also compared the proportions between the individual and each of the other two groups using Z tests. For continuous secondary outcomes, analysis of variance (ANOVA) or Kruskal–Wallis tests (if the normal distribution assumption was violated) were used for comparisons among the three groups. Group comparisons were performed using independent two-sample t tests or Wilcoxon rank-sum tests as appropriate. For discrete outcomes, chi-square tests and odds ratios were used. Survival probabilities were calculated using Kaplan–Meier estimators and the comparisons were performed using methods by Klein et al.[23] For the hemoglobin level and the West-China-Liu's score, we used a repeated-measurement ANOVA model with a random intercept for within-patient correlation. Two-sided P values <0.025 were considered statistically significant.
A sensitivity analysis was performed for the primary outcomes. We first fitted a random effect logistic model with transfusion requirement (or the composite of in-hospital complications and all-cause mortality by day 30) as the outcome and the group as the predictor, adjusting for age, sex, and ASA classification. The group effects were similar to those of the primary analysis in terms of showing the same direction and significance of the estimators. A random intercept was included to model correlations within each study center.
For the primary outcomes, we performed subgroup analysis by subgroups defined by age, ASA classification, and West-China-Liu's Score (scores of all peri-operative measurements were 6 or >6 at least once). Forest plots were drawn based on odds ratios and corresponding 95% confidence intervals (CIs).
Results
From May 17, 2012, to January 18, 2016, 1351 eligible patients signed the consent, of whom 80 had tumor metastasis, 1 withdrew consent, and 57 had hemoglobin concentrations not dropping <10.0 g/dL. A total of 1213 patients underwent randomization, and three patients were withdrawn at the physician's request. A total of 1210 patients received the assigned intervention, 26 of whom were withdrawn at the physician's request and two at the patient's request. A total of 1182 patients were included in the final analysis as follows: 379, 419, and 384 in the individualized, restrictive, and liberal strategies, respectively [Figure 1]. A telephonic follow-up was performed on January 20, 2017. The patient's baseline characteristics were similar among the three groups [Table 2].
;)
Figure 1: CONSORT flow diagram of individualized red-cell transfusion strategy for non-cardiac surgery in adults.
Table 2 -
Comparison of the baseline characteristics and surgical types among the three groups with different red-cell transfusion strategy.
| Characteristics |
Individualized group (n = 379) |
Restrictive group (n = 419) |
Liberal group (n = 384) |
| Age (years) |
48.9 ± 15.6 |
50.4 ± 15.1 |
51.6 ± 15.4 |
| Male |
119 (31.4) |
151 (36.0) |
152 (39.6) |
| Weight (kg) |
60.0 ± 10.8 |
59.8 ± 11.2 |
60.3 ± 11.7 |
| Body mass index (kg/m2) |
23.0 ± 3.5 |
22.7 ± 3.7 |
22.8 ± 3.8 |
| ASA physical status |
|
|
|
| I or II |
317 (83.6) |
357 (85.2) |
308 (80.2) |
| III or IV |
62 (16.4) |
62 (14.8) |
76 (19.8) |
| Cardiovascular disease |
29 (7.7) |
34 (8.1) |
33 (8.6) |
| Surgery type |
|
|
|
| General |
129 (34.0) |
148 (35.3) |
134 (34.9) |
| Orthopedic |
139 (36.7) |
158 (37.7) |
153 (39.8) |
| Thoracic |
7 (1.9) |
6 (1.4) |
7 (1.8) |
| Neurosurgical |
30 (7.9) |
36 (8.6) |
38 (9.9) |
| Urological |
11 (2.9) |
15 (3.6) |
9 (2.3) |
| Gynecological |
59 (15.6) |
54 (12.9) |
42 (10.9) |
| Others |
4 (1.1) |
2 (0.5) |
1 (0.3) |
| Tumor |
133 (35.1) |
157 (37.5) |
151 (39.3) |
Data are shown as n (%) or mean ± standard deviation. ASA: American Society of Anesthesiologists. Data from the full analysis set population are presented here. In the individualized group, red-cell transfusion trigger and target were determined according to the West-China-Liu's Score. In the restrictive group, decision of red-cell transfusion was made in accordance with the current Chinese transfusion guidelines, which state that red-cell transfusion is usually required with the Hb level <7 g/dL; and usually not required with the hemoglobin level ≥10 g/dL; when the hemoglobin concentration is between 7 g/dL and 10 g/dL, decision of red-cell transfusion should be based on the physician's judgment about patients’ condition. In the liberal group, the red-cell transfusion trigger was a Hb level <9.5 g/dL and red-cell transfusion target was to maintain Hb level ≥10 g/dL. No significant differences were found among the three groups for any of the listed variables.
Primary outcomes
Of the patients receiving the individualized strategy, 30.6% (116/379) received red-cell transfusion, which was significantly less than the numbers in the restrictive (62.5% [262/419]; absolute risk difference: 31.92% [97.5% CI: 24.42–39.42%]; P<0.001) and liberal strategies (89.8% [345/384]; absolute risk difference: 59.24% [97.5% CI: 52.91%–65.57%]; P<0.001; Table 3). The composite of in-hospital complications and all-cause mortality by day 30 did not significantly differ among the three groups (P = 0.224; Table 3). The composites were similar between the individualized and restrictive groups (11.6% [44/379] vs. 11.5% [48/419]; absolute risk difference: −0.15% [97.5% CI: −5.23% to 4.92%]; P = 0.946), and similar between the individualized and liberal groups (11.6% [44/379] vs. 15.1% [58/384]; absolute risk difference: 3.49% [97.5% CI: −2.02% to 9.01%]; P = 0.156). For the non-inferiority test, we set the non-inferiority margin to 4.50%. The individualized group was non-inferior to the liberal group, as the lower bound (−2.02%) was greater than −4.50%. The individualized group was not significantly non-inferior to the restrictive group, as the lower bound (−5.23%) of the CI was smaller than −4.50%. However, the risk difference was −0.15%, which was close to 0, and no significant difference between the risks of the two groups existed.
Table 3 -
Primary and secondary outcomes among the three groups with different red-cell transfusion strategy.
| Outcomes |
Individualized group (n = 379) |
Restrictive group (n = 419) |
Liberal group (n = 384) |
Odds ratio (97.5% CI) |
Risk difference (97.5% CI) |
Mean difference (95% CI) |
P value |
| Primary outcomes |
|
|
|
|
|
|
|
| Patients received red cell transfusion |
116 (30.6) |
262 (62.5) |
345 (89.8) |
|
|
|
<0.001 |
|
|
|
|
3.78 (2.70–5.30)†
|
|
|
<0.001†
|
|
|
|
|
20.06 (12.74–31.57)‡
|
|
|
<0.001‡
|
| Composite of in-hospital complications and mortality by day30 |
44 (11.6) |
48 (11.5) |
58 (15.1) |
|
|
|
0.224 |
|
|
|
|
0.99 (0.60–1.62)†
|
−0.15 (−5.23, 4.92) †
|
|
0.946†
|
|
|
|
|
1.35 (0.84–2.19)‡
|
3.49 (−2.02, 9.01)‡
|
|
0.156‡
|
| Secondary outcomes |
|
|
|
|
|
|
|
| Units of red cell transfused per person∗
|
0.0 (0–2.0) |
2.0 (0–4.0) |
3.5 (2.0–4.5) |
|
|
|
<0.001 |
|
|
|
|
1.57 (0.90–2.23)†
|
|
|
<0.001†
|
|
|
|
|
2.75 (2.07–3.42)‡
|
|
|
<0.001‡
|
| Patients received FFP transfusion |
84 (22.1) |
174 (41.7) |
175 (45.8) |
|
|
|
<0.001 |
| Patients received platelet transfusion |
13 (3.4) |
4 (1.0) |
9 (2.4) |
|
|
|
0.059 |
| Patients received cryoprecipitate transfusion |
11 (2.9) |
8 (1.9) |
11 (2.9) |
|
|
|
0.598 |
| Patients received albumin transfusion |
60 (15.8) |
86 (20.6) |
75 (19.6) |
|
|
|
0.195 |
| Hemoglobin concentration (g/dL) |
|
|
|
|
|
|
|
| Preoperation |
10.8 ± 1.7 |
10.8 ± 1.7 |
11.2 ± 1.8 |
|
|
|
0.092 |
| Completion of operation |
8.6 ± 1.3 |
9.0 ± 1.3 |
10.4 ± 1.3 |
|
|
|
<0.001 |
| 24 h after operation |
9.1 ± 1.6 |
9.6 ± 1.7 |
10.6 ± 1.5 |
|
|
|
<0.001 |
| Before discharge |
9.6 ± 1.4 |
9.8 ± 1.4 |
10.7 ± 1.3 |
|
|
|
<0.001 |
| Before all transfusions |
6.5 ± 1.6 |
7.7 ± 1.3 |
8.5 ± 1.0 |
|
|
|
<0.001 |
| West-China-Liu's Score |
|
|
|
|
|
|
|
| Preoperation |
6.1 ± 0.4 |
6.0 ± 0.3 |
6.1 ± 0.3 |
|
|
|
0.128 |
| Completion of operation |
6.2 ± 0.6 |
6.1 ± 0.4 |
6.1 ± 0.4 |
|
|
|
0.033 |
| 24 h after operation |
6.3 ± 0.5 |
6.2 ± 0.5 |
6.2 ± 0.5 |
|
|
|
0.258 |
| Before discharge |
6.1 ± 0.4 |
6.0 ± 0.2 |
6.1 ± 0.3 |
|
|
|
0.128 |
| Before all transfusions |
7.0 ± 1.0 |
6.3 ± 0.7 |
6.2 ± 0.6 |
|
|
|
<0.001 |
| Scores of all measurements were 6 |
240 (63.5) |
283 (69.4) |
268 (72.4) |
|
|
|
0.028 |
| Mortality by day30 |
4 (1.1) |
2 (0.5) |
8 (2.3) |
|
|
|
0.116 |
| Mortality by day60 |
4 (1.1) |
3 (0.8) |
14 (4.1) |
|
|
|
0.013 |
| Mortality by day180 |
12 (3.6) |
12 (3.2) |
21 (6.1) |
|
|
|
0.126 |
| Mortality by 1 year |
22 (7.6) |
25 (7.7) |
33 (10.9) |
|
|
|
0.062 |
| In-hospital complications§
|
44 (11.6) |
48 (11.5) |
57 (14.8) |
|
|
|
0.273 |
|
|
|
|
0.98 (0.64–1.52)†
|
|
|
0.946†
|
|
|
|
|
1.33 (0.87–2.02)‡
|
|
|
0.187‡
|
| Cardiac |
2 (0.5) |
1 (0.2) |
7 (1.8) |
|
|
|
0.035 |
| Central nervous |
4 (1.1) |
4 (1.0) |
5 (1.3) |
|
|
|
0.890 |
| Pulmonary |
13 (3.4) |
19 (4.5) |
19 (5.0) |
|
|
|
0.565 |
| Digestive |
9 (2.4) |
6 (1.4) |
8 (2.1) |
|
|
|
0.611 |
| Urinary/reproductive |
3 (0.8) |
4 (1.0) |
5 (1.3) |
|
|
|
0.771 |
| Post-operative bleeding |
1 (0.3) |
2 (0.5) |
1 (0.3) |
|
|
|
0.830 |
| Others |
22 (5.8) |
25 (6.0) |
31 (8.1) |
|
|
|
0.365 |
| In-hospital infection |
18 (4.8) |
26 (6.2) |
29 (7.6) |
|
|
|
0.274 |
| ICU admission rate |
68 (17.9) |
77 (18.5) |
83 (21.7) |
|
|
|
0.354 |
| Healing status of surgical incision |
|
|
|
|
|
|
0.636 |
| I |
372 (96.1) |
396 (94.5) |
360 (93.8) |
|
|
|
|
| II |
11 (2.8) |
18 (4.2) |
20 (5.2) |
|
|
|
|
| III |
4 (1.0) |
5 (1.3) |
4 (1.0) |
|
|
|
|
| Stitch removal time (days) |
15.5 ± 6.7 |
15.8 ± 8.9 |
14.2 ± 13.3 |
|
|
|
0.280 |
| Length of hospital stay (days) |
21.5 ± 13.9 |
21.6 ± 13.1 |
21.8 ± 14.2 |
|
|
|
0.796 |
| Length of hospital stay after surgery (days) |
12.4 ± 11.3 |
12.2 ± 9.9 |
12.3 ± 9.9 |
|
|
|
0.732 |
| Transfusion related cost |
|
|
|
|
|
|
|
| (Thousand ¥ per person) |
0.55 ± 1.4 |
1.06 ± 1.6 |
1.52 ± 2.2 |
|
|
|
<0.001 |
|
|
|
|
|
|
0.51 (0.29, 0.72)†
|
<0.001†
|
|
|
|
|
|
|
0.97 (0.71, 1.24)‡
|
<0.001‡
|
| Total in-hospital cost |
|
|
|
|
|
|
|
| (Thousand ¥ per person) |
61.9 ± 47.1 |
66.0 ± 48.0 |
68.2 ± 42.7 |
|
|
|
0.013 |
|
|
|
|
|
|
4.05 (−2.59, 1.07)†
|
0.232†
|
|
|
|
|
|
|
6.21 (−0.19, 12.62)‡
|
0.057‡
|
| Non-adherence |
22 (5.7) |
5 (1.2) |
20 (5.0) |
|
|
|
0.001 |
Data are shown as n (%) or median (interquartile). CI: Confidence interval; SD: Standard deviation; FFP: Fresh frozen plasma; ICU: Intensive care unit.
∗In China, one unit of red-cell is collected from 200 mL of whole blood.
†Restrictive group compared with the individualized group.
‡Liberal group compared with individualized group.
§Some patients had more than one in-hospital complications from different systems.
Secondary outcomes
In the individualized strategy, 0.0 (0–2.0) units of red cells were transfused, which is significantly less than those corresponding to the restrictive (2.0 [0–4.0] units; P < 0.001) and liberal strategies (3.5 [2.0–4.5] units; P < 0.001). Preoperative hemoglobin levels were similar in all three groups. In all other measurements, hemoglobin levels in the restrictive strategy group were significantly higher than those in the individualized strategy group and lower than those in the liberal strategy group. The three groups had similar West-China-Liu's Scores throughout the study [Table 3].
The individualized strategy spent significantly less Chinese Yuan (¥) for allogeneic blood cost (¥550 for individualized strategy vs. ¥1056 for restrictive strategy and ¥1524 for liberal strategy, P<0.001) and less total in-hospital cost (¥61,944 for individualized strategy vs. ¥65,990 for restrictive strategy and ¥68,156 for liberal strategy, P = 0.013) than restrictive and liberal strategies [Table 3]. Individualized (1.2%) and restrictive (0.8%) strategies had significantly lower all-cause mortality by day 60 than the liberal strategy (4.1%, P = 0.003). The three groups exhibited no differences in all-cause mortality by day 30, 180, 1 year, and other secondary outcomes [Table 3].
Subgroup analysis revealed that the individualized strategy had significantly less red-cell transfusion [Figure 2A and 2B]; however, a similar composite of in-hospital complications and all-cause mortality by day 30 [Figure 2C and 2D], as compared with the restrictive and liberal strategies defined by age, ASA classification, and the West-China-Liu's Score.
Figure 2: For the primary outcomes, subgroup analysis of group differences was performed by subgroup defined by age (<65 years, ≥65 years), ASA class (I–II, III–IV), and the West-China-Liu's Score at all assessments (all were six, and at least one assessment was >6). For the subgroup of score, data were missing for one patient in the individualized group, for 11 in the restrictive group, and for 14 in the liberal group. The solid vertical line represents odds ratio of the overall analysis for the primary outcomes, and the dashed lines indicate the 95% CI. The diamond and the horizontal line represent the odds ratio and corresponding 95% CI at each subgroup. A and B show the subgroup analyses of number of patients receiving red-cell transfusion. A: Individualized group vs. restrictive group. B: Individualized group vs. liberal group. C and D show the subgroup analyses of composite of in-hospital complications and all-cause mortality by day-30. C: Individualized group vs. restrictive group. D: Individualized group vs. liberal group. ASA: American Society of Anesthesiologists; CI: Confidence interval.
Discussion
In this study, the individualized strategy had 51.0% fewer exposures to allogeneic red cells (30.6% vs. 62.5%) and a 50.0% reduction in the mean number of units of red cells transfused (1.58 vs. 3.15) as compared with the restrictive strategy. Consistent with previous trials,[6-10] a restrictive strategy received less red-cell transfusion (62.5% vs. 89.8%) than a liberal strategy in this trial. The other outcomes related to patient safety did not significantly differ among the three groups. This study shows that an individualized strategy is safe and associated with less medical resource consumption than liberal or restrictive strategies in adult patients undergoing elective non-cardiac surgery.
The oxygen delivery/consumption balance is determined by multiple factors, and diversity and dynamic changes in these factors exist among surgical patients. No single numerical laboratory value, including hemoglobin concentration, can sufficiently indicate the balance and serve as an absolute trigger and target for red-cell transfusion. Therefore, an optimal approach to balancing the risks between anemia and allogeneic red cell exposure should be patient-individualized after objectively assessing each patient's real-time condition regarding oxygen delivery/consumption balance and thereafter determining individual red-cell transfusion triggers and targets. Transfection using red cells elevates blood oxygen delivery and restores oxygen supply/consumption balance. We developed the West-China-Liu's Score based on the physiology of oxygen supply/consumption balance, which is directly proportional to hemoglobin concentration, arterial oxygen saturation, and cardiac output and inversely proportional to body oxygen consumption. Accordingly, the score consists of four components: (1) minimum inhaled oxygen concentration to maintain a pulse oxygen saturation ≥95%; (2) infusion rate of adrenalin required to maintain an adequate cardiac output; (3) core body temperature; and (4) history of angina and its severity. Angina is integrated into the score because the heart, an organ that consumes most of the oxygen from the blood, is most sensitive to oxygen supply/consumption imbalance in the body. This integration is supported by a prospective study[24] that enrolled 110 patients and a retrospective study of 78,974 patients,[25] which revealed that more blood transfusions were associated with fewer cardiac events or lower mortality in patients with coronary artery disease. This simple scoring system enables physicians to objectively and semi-quantitatively assess the risk of oxygen supply/consumption misbalance in the total body and heart, and to grade individual patients to five levels from 6 to 10, indicating an increased risk of oxygen supply/consumption misbalance and an increasing requirement for red-cell transfusion. By matching the five levels of hemoglobin concentration from 6 to 10 g/dL as red-cell transfusion triggers and targets, an individualized strategy can be achieved. In this study, we define the concept of “adult” as >14 years old because physical development has approached that of adults in all aspects at the age of 14. This score has been modified by replacing angina with age for pediatric (<14 years old) individualized red-cell transfusion, and a randomized controlled trial (Clinical Trial of West-China Transfusion Score for Children. ChiCTR-IRP-16007909) is currently underway in China.
The cost was considered in this study. The individualized strategy had 55% and 64% less allogeneic blood costs (P<0.001), and 6.2% (¥4100) and 9.2% (¥6300) less total in-hospital costs (P = 0.013) compared with the restrictive and liberal strategies, respectively. This may suggest underlying risks related to red-cell transfusion. Transfused red cells are 19.5 million units annually in China,[1] and about two-thirds of surgical patients follow the current Chinese transfusion guidelines [19] (same as the restrictive group in this study). Based on the above, we estimate approximately ¥16.5 billion savings in total in-hospital costs for surgery annually if this individualized strategy is adopted in the whole of China.
To our knowledge, this is a rare study to examine the safety of setting a hemoglobin level of 6 g/dL as the red-cell transfusion trigger and target for “healthy” patients. We designed this study based on the following findings. The critical hemoglobin concentration in healthy humans, where a compensatory increase in cardiac output and oxygen extraction for anemia is maximized, and a further reduction in hemoglobin concentration would decrease oxygen consumption and compromise cellular metabolism, is certainly <5 g/dL.[26-28] Doak and Hall[29] found that patients with preserved ventricular function undergoing coronary artery surgery did not have anaerobic myocardial metabolism and did not increase the incidence of myocardial ischemia with a hemoglobin concentration of 6 to 7 g/dL. The subgroup analyses in this study revealed that among the 791 patients (66.9% of total studied patients) who scored six at all assessments, the individualized strategy had fewer patients who received red-cell transfusion than the restrictive (19.6% vs. 62.2%, Figure 2A) and liberal strategies (19.6% vs. 88.8%, Figure 2B); however, similar combined in-hospital complications and mortality by day 30. These findings suggest that in patients with a score of six undergoing non-cardiac surgery, a hemoglobin concentration of 6 g/dL is safe and cost-effective as the red-cell transfusion trigger and target.
Age was not included in this score. The elderly often have poorer cardiopulmonary functions; however, their metabolic rate is lower than that of young patients. More importantly, for those who need supplemental oxygen and inotropic agents, poorer cardiopulmonary functions will be considered during scoring and should not be double-counted. Age appears to be of minor importance in the tolerance to acute anemia and response to blood transfusion.[30] A study of hip surgery,[4,5] which enrolled 2016 patients with a mean age of 81.6 years found no differences in in-hospital and long-term mortalities between liberal and restrictive strategies. A study of cardiac surgery[9] found a lower risk of the composite outcome in a restrictive strategy than a liberal strategy in patients aged ≥75 years, and subgroup analyses [Figure 2] in this study showed that among the patients aged >65 years, the individualized strategy had the least red-cell transfusion; however, similar clinical outcomes among the three strategies, supporting the view that age could not be considered as an individualized strategy.
In this trial, to avoid potential cardiac events for patients with angina and to determine which transfusion strategy is the most beneficial in clinical practice, we included the liberal strategy group as a comparator. However, we focused on the comparison between individualized and restrictive groups because most clinicians make the decision for transfusion based on the restrictive transfusion strategy. Compared with the current guidelines of restrictive strategy, individualized strategy with strict application of the West-China-Liu's Score could reduce red-cell transfusion by 31% during hospitalization, which means that patients receiving red-cell transfusion could be reduced by approximately 1.3 million/year in China. The number of red cell units per capita could be reduced by 50%, which means that approximately 1600 tons of red-cell suspension could be saved annually, and 4.2 of blood donors could be reduced, which would largely alleviate the current “blood shortage” problems such as insufficient blood supply. Moreover, the direct cost saved by reducing red-cell transfusion is approximately ¥500/person, and the total in-hospital cost saved is approximately ¥4000/person; that is, the annual medical cost could be reduced by ¥30 billion.
This study had several limitations. First, two-thirds of the enrolled patients were ASA I to II (with West-China-Liu's Score 6 at all measurements), and patients at high risk of oxygen delivery/consumption misbalance might not be included. However, this study aimed to perform elective non-cardiac surgery, and this population represented a real-world situation. Second, this open-label study is subject to bias. The restrictive strategy allowed physicians to make a transfusion decision based on their experience and patient condition. We defined this group as a restrictive strategy because the average hemoglobin level before all transfusions (7.65 ± 1.26 g/dL) was within the hemoglobin threshold range for most previous restrictive strategies.[4-10,13,24]
In conclusion, a practical individualized red-cell transfusion strategy using the West-China-Liu's Score resulted in a greater decrease in the red-cell transfusion rate compared with restrictive and liberal strategies, and without compromising patient safety in elective non-cardiac surgeries.
Acknowledgements
We thank the physicians and clinical staff of all the centers participating in this study.
Funding
This work was supported by grants from the National Key Research and Development Program of China (No. 2018YFC2001800), the 1-3-5 Project for disciplines of excellence, West China Hospital, and Sichuan University Education Foundation.
Conflicts of interest
None.
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