Abstract
BACKGROUND
Perioperative hemorrhage impacts patient outcomes and health care resource utilization, yet the risks of transfusion therapies are significant. In patients with preoperative thrombocytopenia, the effects of prophylactic preoperative platelet (PLT) transfusion on perioperative bleeding complications remain uncertain.
STUDY DESIGN AND METHODS
This is a retrospective cohort study of noncardiac surgical patients between January 1, 2008, and December 31, 2011. Propensity-adjusted analyses were used to evaluate associations between preoperative thrombocytopenia, preoperative PLT transfusion, and the outcomes of interest, with a primary outcome of perioperative red blood cell (RBC) transfusion.
RESULTS
A total of 13,978 study participants were included; 860 (6.2%) had a PLT count of not more than 100 × 109/L with 71 (8.3%) receiving PLTs preoperatively. Administration of PLTs was associated with higher rates of perioperative RBC transfusion (66.2% vs. 49.1%, p 0.0065); however, in propensity-adjusted analysis there was no significant difference between groups (odds ratio [OR] [95% confidence interval {95% CI}], 1.68 [0.95–2.99]; p =0.0764]. Patients receiving PLTs had higher rates of intensive care unit (ICU) admission (OR [95% CI], 1.95 [1.10–3.46]; p =0.0224) and longer hospital lengths of stay (estimate [95% bootstrap CI], 7.2 [0.8–13.9] days; p =0.0006) in propensity-adjusted analyses.
CONCLUSION
Preoperative PLT transfusion did not attenuate RBC requirements in patients with thrombocytopenia undergoing noncardiac surgery. Moreover, preoperative PLT transfusion was associated with increased ICU admission rates and hospital duration. These findings suggest that more conservative management of preoperative thrombocytopenia may be warranted.
Perioperative hemorrhage necessitating red blood cell (RBC) transfusion is an undesirable surgical complication, as RBC transfusion has consistently been associated with adverse patient outcomes.1–7 In addition, the economic toll of transfusion is increasingly well recognized, with nearly 3 million units of RBCs transfused perioperatively each year in the United States, representing more than $2.25 billion.8,9 Furthermore, hospital blood supplies are limited with more than one-quarter of US hospitals reporting surgical delays due to insufficient blood supplies and 10% of hospitals reporting at least 1 day per year where surgical blood needs cannot be met.8 It is therefore imperative in this era of increased scrutiny on health care quality that transfusion practices be uniquely tailored to clinical scenarios in which transfusion may provide evidence-based improvement in patient outcome.
Preoperative platelet (PLT) counts and coagulation tests have long been used as a marker of perioperative bleeding risk; however, the value of this practice remains unclear.10 Prior studies have shown that routine preoperative coagulation tests, including PLT counts, do not reliably predict surgical bleeding complications,11–15 prompting the 2012 American Society of Anesthesiologists Task Force on Preanesthesia Evaluation to recommend against this practice unless clearly indicated by patient history and physical examination.16 However, recent evidence suggests that pre-operative thrombocytopenia is associated with significantly higher risk of blood transfusion and death in noncardiac surgery, prompting the authors to question recommendations against routine preoperative screening.17
In clinical practice, administration of PLTs in those with thrombocytopenia is frequently performed in the preoperative period in an attempt to mitigate perioperative bleeding complications including RBC requirements, surgical blood loss, and reoperation for bleeding. However, evidence to support or guide such perioperative transfusion practices is lacking.18 As such, the decision to transfuse in the perioperative period is often based on the gestalt or clinical experience of the surgeon or anesthesiologist rather than by quality evidence suggesting benefit. Moreover, PLT transfusions are associated with substantial patient risk, including a myriad of allergic, infectious, and inflammatory transfusion reactions.19,20
This investigation was designed to determine the relationship between preoperative PLT transfusion and perioperative bleeding complications in patients with thrombocytopenia undergoing noncardiac surgery in a large, tertiary care center. We hypothesized that while preoperative thrombocytopenia (i.e., PLT count ≤ 100 × 109/L) would be predictive of perioperative RBC requirements, prophylactic PLT administration would not attenuate this risk. In addition, we aimed to assess the impact of preoperative PLT transfusion on other patient-important outcomes.
MATERIALS AND METHODS
This is a retrospective cohort study conducted under the approval of the Mayo Clinic (Rochester, MN) Institutional Review Board. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were used in the design and conduct of this study, as well as in the reporting of results.21
Study population
Inclusion criteria for this investigation included adult patients at least 18 years of age, undergoing noncardiac surgery between January 1, 2008, and December 31, 2011, at a single tertiary care center, and the presence of an international normalized ratio (INR) and PLT count available in the medical record in the 30-day interval preceding surgery. Exclusion criteria included lack of valid research authorization, American Society of Anesthesiologists Physical Status (ASA PS) VI classification, and prior inclusion in the study.
Outcome variables
The primary outcome of interest was the need for RBC transfusion in the early perioperative period. To qualify, the RBC transfusion initiation time was required to occur during the operative encounter or within 24 hours after discharge from the operating room environment. RBC transfusions initiated before entering the operating room were not included in the outcome evaluation. Secondary outcome measures included intraoperative RBC transfusion, defined as RBC transfusion initiated in the operating room environment, estimated blood loss as recorded in the anesthetic record, and return to the operating room within 24 hours for a primary indication of bleeding. Additional patient-important outcomes such as intensive care unit (ICU) length of stay, need for ventilatory support, duration of hospital stay, and hospital mortality were also evaluated.
Predictor variables
The primary predictor variables for this investigation were preoperative thrombocytopenia (defined as a PLT count ≤ 100 × 109/L) and the presence of a preoperative PLT transfusion in those with thrombocytopenia. For patients with multiple preoperative PLT count values, the value closest to the time of surgery was utilized. The presence and timing of all perioperative transfusion episodes were extracted from the electronic health record. Qualifying preoperative PLT transfusions were defined as those administered after the qualifying PLT count and within 24 hours of the surgical procedure. As our aim was to specifically investigate the impact of preoperative PLT administration, intraoperative and postoperative PLT transfusions were not considered in the analyses. This design (exclusion of intraoperative and postoperative PLT transfusion episodes) was also endorsed to avoid the potential for cause-effect inversion with the outcomes of interest. To further ensure against cause-effect inversion, the timing of PLT transfusion was defined as the actual transfusion initiation time as documented in the electronic health record rather than the time of PLT issue from the blood bank. Patient demographics, baseline clinical characteristics, and procedural and anesthesia-related details were also extracted from the electronic medical record.
Data sources
Screening for potential study participants was performed using the Perioperative Datamart. This is an institutional resource that captures and records pertinent data for all patients who are admitted to an acute care environment (operating room, ICU, progressive care unit) at the study’s participating institution.22 In addition to containing detailed information regarding the surgical encounter, this robust data warehouse also contains information on baseline demographics and clinical characteristics, fluid and transfusion therapies, as well as a vast amount of related information that is pertinent to the perioperative course (e.g., perioperative medications and laboratory values, postoperative outcomes, and lengths of stay). Additional baseline characteristics pertinent to this investigation but not available in the Perioperative Datamart were obtained from a second validated database, the Mayo Clinic Life Sciences System (MCLSS).23 These databases have previously undergone extensive validation and accuracy has been shown to be superior to manual data collection alone.24
Statistical analysis
The sample size was estimated by assuming a perioperative RBC transfusion rate of 30% (historical data from the participating institution) and an estimated prophylactic PLT transfusion rate of 25% in those with a PLT count of less than 100 × 109/L, which would require a sample size of approximately 600 study subjects with preoperative thrombocytopenia to identify an odds ratio (OR) of 0.5 in those who receive prophylactic PLT transfusion compared to those who do not (two-sided alpha of 0.05, β =0.20). In an effort to adequately power the investigation for a priori subgroup and sensitivity analyses (e.g., PLT thresholds of 75 × 109 and 50 ×109/L), a 4-year time period was chosen that would obtain an estimated sample size of 1200 patients.
Baseline demographics, clinical characteristics, and procedure-related information were summarized and presented as median (25%–75% interquartile range [IQR]) for continuous data elements and frequencies (%) for categorical data, respectively. Univariate hypothesis testing for continuous variables was performed using the Wilcoxon rank-sum test. Univariate hypothesis testing for categorical variables was performed with Pearson’s chi-squared tests or Fisher exact tests as appropriate.
To explore the relationship between preoperative PLT count and the outcomes of interest, a PLT count of not more than 100 ×109/L was used as a threshold for the diagnosis of thrombocytopenia. This threshold was employed for two reasons: 1) ASA practice guidelines indicate that a PLT count of more than 100 ×109/L rarely requires transfusion, while significant clinical equipoise exists for management of the surgical patient with a PLT count of not more than 100 ×109/L,25 and 2) our experience suggests that the decision to transfuse PLTs is frequently based on threshold values, with 100 ×109/L being commonly used in local practice. Recognizing that transfusion strategies may vary significantly by local practice,26 sensitivity analyses using PLT counts of 75 ×109 and 50 ×109/L were planned a priori. Univariate and multivariable logistic regression analyses were performed to assess the relationship between preoperative thrombocytopenia and perioperative RBC transfusion and reoperation for bleeding.
With regard to the primary aim of this investigation, relationships between preoperative PLT transfusion and perioperative bleeding complications were explored with univariate and multivariable analyses. Recognizing that observational studies risk unequal distributions of key confounding variables due to lack of subject randomization, propensity-adjusted analyses were planned a priori. Briefly, logistic regression was used to calculate propensity scores for preoperative PLT transfusion utilizing all hypothesized confounding variables. Visual inspection of the distribution of propensity scores according to preoperative PLT transfusion revealed adequate overlap between groups throughout the range of observed values. Patients were stratified into quintiles of the propensity distribution.27 Cochran-Mantel-Haenszel statistics and linear models were used to verify that potential confounding variables did not differ between those receiving preoperative PLT transfusions versus those that did not after adjusting for propensity strata. Conditional logistic regression was then used to assess the relationship of early perioperative RBC transfusion with preoperative PLT transfusion. Similar analyses were performed for secondary outcomes using conditional logistic regression for binary outcomes and mixed linear models for hospital length of stay. ICU length of stay and duration of mechanical ventilation were analyzed for patients who required these interventions with the rank-sum test used to compare those who did and did not receive preoperative PLT transfusion.
To further assess the robustness of the study findings, multiple additional sensitivity analyses were planned a priori. These prespecified analyses included: 1) restriction to study participants undergoing elective surgery; 2) restriction to study participants undergoing general surgery; and 3) restriction to patients with a PLT count of 75 × 109 and 50 × 109/L, respectively. All statistical analyses were performed with computer software (SAS, Version 9.3, SAS Institute, Cary, NC).
RESULTS
A total of 13,978 patients met inclusion criteria and were included in this investigation (Fig. 1). Of these, 860 (6.2%) had a PLT count of not more than 100 × 109/L before their surgical procedure. Among these, 71 (8.3%) received a qualifying preoperative PLT transfusion administered before entry into the operating suite. Of note, no patient with preoperative thrombocytopenia received a PLT transfusion after entry into the operating suite and before surgical incision. The median (IQR) time between PLT count measurement and surgical onset was 24.4 (7.7–141.9) hours. In those who received a preoperative PLT transfusion as defined by the study protocol, the median (IQR) time from initiation of the last qualifying PLT component to the onset of the surgical procedure was 1.0 (0.5–2.7) hours. The longest recorded interval between initiation of the last qualifying PLT component and the onset of the surgical procedure was 9.1 hours.
Fig. 1.
Study population flow diagram.
Comparison of baseline clinical, demographic, and procedural characteristics for those who received preoperative PLTs and those who did not are shown in Table 1. Several important between-group differences were identified. Briefly, patients receiving preoperative PLT transfusion had higher ASA PS and lower preoperative hemoglobin (Hb) and PLT values. They were also more likely to undergo emergency surgery and had shorter surgical durations. Those receiving preoperative PLTs had a higher incidence of hematologic malignancies and chronic pulmonary disease but a lower incidence of liver disease and nonhematologic malignancies. After propensity adjustment, there were no significant differences between groups.
TABLE 1.
Baseline demographic and clinical characteristics of patients with preoperative thrombocytopenia
| Variable* | No therapy (n =789) | Preoperative PLTs (n =71) | p value†
|
|
|---|---|---|---|---|
| Unadjusted | Stratified | |||
| Demographics | ||||
| Age (years) | 61.0 (52.0, 71.0) | 63.0 (53.0, 72.0) | 0.5006 | 0.7843 |
| Body mass index‡ | 27.5 (24.3, 32.3) | 27.9 (23.7, 32.2) | 0.9502 | 0.8970 |
| Male sex | 487 (62) | 43 (61) | 0.8473 | 0.7998 |
| ASA PS | <0.0001 | 0.4011 | ||
| 1 | 4 (1) | 0 (0) | ||
| 2 | 113 (14) | 5 (7) | ||
| 3 | 412 (52) | 27 (38) | ||
| 4 | 247 (31) | 32 (45) | ||
| 5 | 13 (2) | 7 (10) | ||
| Comorbidities | ||||
| Myocardial infarction | 72 (9) | 5 (7) | 0.5559 | 0.9701 |
| Congestive heart failure | 109 (14) | 12 (17) | 0.4737 | 0.8931 |
| Peripheral vascular disease | 14 (2) | 2 (3) | 0.5335 | 0.9766 |
| Cerebrovascular disease | 76 (10) | 10 (14) | 0.2310 | 0.8544 |
| Dementia | 9 (1) | 1 (1) | 0.8402 | 0.9064 |
| Chronic pulmonary disease | 66 (8) | 11 (15) | 0.0439 | 0.7578 |
| Connective tissue disease | 28 (4) | 5 (7) | 0.1422 | 0.9288 |
| Ulcer disease | 22 (3) | 2 (3) | 0.9888 | 0.7676 |
| Mild liver disease | 342 (43) | 13 (18) | < .0001 | 0.9419 |
| Diabetes mellitus | 243 (31) | 18 (25) | 0.3390 | 0.9155 |
| Hemiplegia | 1 (0) | 0 (0) | 0.7641 | |
| Moderate to severe renal disease | 139 (18) | 14 (20) | 0.6575 | 0.8919 |
| Diabetes with end organ damage | 61 (8) | 5 (7) | 0.8345 | 0.8806 |
| Tumor | 238 (30) | 10 (14) | 0.0042 | 0.9786 |
| Leukemia | 42 (5) | 10 (14) | 0.0030 | 0.6770 |
| Lymphoma | 51 (6) | 9 (13) | 0.0491 | 0.9782 |
| Moderate to severe liver disease | 182 (23) | 6 (8) | 0.0043 | 0.9399 |
| Metastatic solid tumor | 220 (28) | 9 (13) | 0.0055 | 0.9937 |
| AIDS | 0 (0) | 0 (0) | ||
| Perioperative medications | ||||
| Aspirin | 403 (51) | 34 (48) | 0.6066 | 0.9608 |
| Clopidogrel | 18 (2) | 2 (3) | 0.7743 | 0.9702 |
| Coumadin | 137 (17) | 12 (17) | 0.9215 | 0.9832 |
| Heparin | 154 (20) | 16 (23) | 0.5409 | 0.7624 |
| NSAIDs | 0 (0) | 0 (0) | ||
| Baseline laboratory values | ||||
| INR | 1.2 (1.1, 1.5) | 1.3 (1.2, 1.5) | 0.1759 | 0.9501 |
| Hb (g/dL) | 10.4 (9.1, 12.3) | 9.1 (8.2, 11.4) | <0.0001 | 0.5977 |
| PLT count | 73.0 (55.0, 88.0) | 49.0 (34.0, 71.0) | <0.0001 | 0.7033 |
| APTT‡ (sec) | 33.0 (29.0, 41.0) | 34.0 (29.5, 39.0) | 0.6001 | 0.5304 |
| Creatinine‡ (mg/dL) | 1.0 (0.8, 1.4) | 1.0 (0.7, 1.6) | 0.9230 | 0.6003 |
| Albumin‡ (g/dL) | 3.4 (2.9, 3.8) | 3.1 (2.7, 3.8) | 0.1653 | 0.7351 |
| Procedural characteristics | ||||
| Procedure type | <0.0001 | 0.5931 | ||
| ENT/oral | 65 (8) | 14 (20) | ||
| General | 257 (33) | 23 (32) | ||
| Neurology | 12 (2) | 4 (6) | ||
| O/G | 19 (2) | 4 (6) | ||
| Orthopedic | 92 (12) | 2 (3) | ||
| Spine | 15 (2) | 3 (4) | ||
| Thoracic | 46 (6) | 9 (13) | ||
| Transplant | 167 (21) | 2 (3) | ||
| Urology | 41 (5) | 3 (4) | ||
| Vascular | 30 (4) | 6 (8) | ||
| Other§ | 45 (6) | 1 (1) | ||
| Emergency | 198 (25) | 29 (41) | 0.0039 | 0.7936 |
| Primary anesthesia‡ | 0.4603 | 0.7661 | ||
| General | 781 (99) | 71 (100) | ||
| Regional block | 6 (1) | 0 (0) | ||
| Surgical duration (min) | 192.1 (115.9, 295.2) | 147.0 (99.4, 203.3) | 0.0016 | 0.4749 |
Continuous variables are summarized as median (Q1, Q3). Categorical variables are summarized as number (%).
p values for continuous variables are from rank sum tests. p values for categorical variables are from chi-square tests. Stratified p values correspond to the comparison of the given characteristic for the propensity-matched strata.
Body mass index was available for 751 (87%) patients. APTT was available for 618 (72%) patients. Creatinine was available for 853 (99%) patients. Albumin was available for 526 (61%) patients. Anesthesia type was available for 858 (99%) patients.
Procedure categories with less than 50 subjects were grouped into the “other” category for comparison.
AIDS =acquired immunodeficiency syndrome; APTT =activated partial thromboplastin time; ENT =ears, nose, throat; NSAIDs =nonsteroidal anti-inflammatory drugs; O/G =obstetrics/gynecology.
A total of 2847 of the study subjects (20.4%) received a perioperative RBC transfusion as defined by the study protocol. Those with PLT counts of not more than 100 × 109/L had significantly higher rates of perioperative RBC transfusion (50.2% vs. 18.4%; p <0.0001) and reoperation for bleeding (8.1% vs. 2.1%; p <0.0001) than those with PLT counts of more than 100 × 109/L. These relationships remained significant in multivariable analyses (Table 2). Preoperative thrombocytopenia was also associated with increased all-cause mortality after adjustment for between-group differences (OR [95% CI], 1.87 [1.29–2.70]; p =0.0009).
TABLE 2.
Univariate and multivariable analyses of primary and secondary outcomes in those with preoperative thrombocytopenia compared to those with PLT counts of more than 100 × 109/L
| Outcome | Univariate analysis
|
Multivariable analysis†
|
||||
|---|---|---|---|---|---|---|
| OR* | 95% CI | p value | OR* | 95% CI | p value | |
| Perioperative RBCs | 4.48 | 3.89–5.15 | <0.0001 | 2.15 | 1.72–2.68 | <0.0001 |
| Intraoperative RBCs | 3.96 | 3.42–4.58 | <0.0001 | 1.67 | 1.31–2.12 | <0.0001 |
| Reoperation | 4.12 | 3.14–5.40 | <0.0001 | 1.75 | 1.18–2.59 | 0.0053 |
| Mortality | 6.39 | 5.04–8.10 | <0.0001 | 1.87 | 1.29–2.70 | 0.0009 |
ORs are for preoperative thrombocytopenia. ORs higher than 1.00 indicate increased likelihood of the listed outcome in patients with thrombocytopenia.
Adjusted including all baseline characteristics having significant differences between patient groups with PLT counts of more than 100 × 109/L and those with PLT counts of not more than 100 × 109/L, utilizing a threshold p value of less than 0.1. Variables included in conditional logistic regression modeling—age; sex; Charlson score; perioperative warfarin, heparin; preoperative Hb, PLT count, INR, creatinine; ASA type (“ASA 1” as reference); emergency surgery; procedure type (“general surgery” as reference); anesthetic type (general vs. regional); surgical duration.
Results of unadjusted analyses evaluating the associations between preoperative PLT transfusion and perioperative bleeding compilations and other patient-important outcomes in patients with thrombocytopenia are shown in Table 3. The frequency of RBC transfusion among those who received a preoperative PLT transfusion versus those who did not was 66.2% versus 48.8% (OR [95% CI], 2.03 [1.22–3.39]; p =0.0065). In addition, preoperative PLT transfusion was associated with increased ICU admission rates, hospital length of stay, and hospital mortality. Estimates of intraoperative blood loss were available for only 52.2% of patients and were therefore excluded from related analyses given the unanticipated magnitude of missing data.
TABLE 3.
Univariate analyses of primary and secondary outcomes by the presence or absence of preoperative PLT transfusion in patients with thrombocytopenia
| Outcome* | No therapy (n =789) | Preoperative PLTs (n =71) | p value† | Estimate (95% CI)‡ |
|---|---|---|---|---|
| Perioperative RBC transfusion | 387 (49) | 47 (66) | 0.0065 | 2.03 (1.22–3.39) |
| Intraoperative RBC transfusion | 301 (38) | 32 (45) | 0.2527 | 1.33 (0.82–2.17) |
| Reoperation | 63 (8) | 7 (10) | 0.5806 | 1.23 (0.55–2.87) |
| ICU admission | 232 (30) | 41 (58) | <0.0001 | 3.26 (1.99–5.36) |
| ICU length of stay (days), n =273§ | 1.8 (0.8, 3.8) | 2.6 (1.2, 3.9) | 0.2659 | 0.12 (−0.73 to 0.86) |
| Postoperative MV | 56 (8) | 8 (14) | 0.1006 | 1.95 (0.88–4.31) |
| Duration of MV (days), n =64§ | 1.1 (0.1, 5.1) | 6.5 (2.0, 17.2) | 0.0618 | 5.8 (−1.8 to 13.3) |
| Hospital LOS (days), n =859§ | 8.7 (3.5, 17.3) | 15.1 (6.5, 41.1) | <0.0001 | 9.3 (3.1–15.9) |
| Mortality | 80 (10) | 19 (27) | <0.0001 | 3.20 (1.80–5.67) |
Data are reported as number (%) for binary outcomes and median (Q1, Q3) for continuous outcomes.
p values are from logistic regression for binary outcomes and the rank-sum test for continuous outcomes.
For binary outcomes the estimate is for the OR for preoperative PLT transfusion versus no therapy. For continuous outcomes the estimate is the difference in mean (preoperative PLTs minus no therapy) with the 95% CI calculated from 1000 bootstrap samples.
ICU length of stay is summarized only for those patients who were admitted to the ICU and duration of mechanical ventilation is summarized only for those patients who received mechanical ventilation postoperatively.
MV =mechanical ventilation; LOS =length of stay.
In total, 853 of 860 study subjects were assigned a propensity score for preoperative PLT transfusion and were subsequently stratified into quintiles based upon their propensity score. Subsequent analyses were restricted to subjects whose propensity score resided within the range of propensity scores that overlapped between those that were transfused preoperatively and those that were not. In total, 71 patients receiving a preoperative PLT transfusion were propensity stratified as were 482 study subjects who did not receive a qualifying preoperative PLT transfusion. Propensity adjustment was effective in addressing baseline covariate imbalances (Table 1, Fig. 2).
Fig. 2.
Propensity-adjusted analysis of the thrombocytopenic cohort showing quintiles of propensity for preoperative PLT transfusion among patients receiving (
) or not receiving (
) a preoperative PLT transfusion.
Among this propensity-stratified cohort, 47 (66.2%) of the PLT transfusion study subjects received a perioperative RBC transfusion compared with 231 (47.9%) of those who did not receive a PLT transfusion preoperatively. Conditional logistic regression on the propensity-adjusted cohort did not identify a statistically significant difference in perioperative RBC transfusions (OR [95% CI], 1.68 [0.95–2.99]; p =0.0764). Those who received a preoperative PLT transfusion had a higher rate of ICU admission and longer hospital lengths of stay (Table 4). As a sensitivity analysis, the relationship between prophylactic PLT transfusion and the volume of RBC transfusion was also evaluated finding no significant difference between propensity-adjusted groups (Table S1, available as supporting information in the online version of this paper). Preoperative PLT transfusions in patients undergoing non-emergency surgery and utilizing lower PLT transfusion thresholds (i.e., ≤ 75 × 109/L and ≤50 × 109/L) were associated with increased rates of perioperative RBC transfusion (Table S2, available as supporting information in the online version of this paper).
TABLE 4.
Conditional regression analysis in the propensity-stratified cohort
| Outcome* | No therapy (n =482) | Preoperative PLTs (n =71) | p value† | Estimate (95% CI)† |
|---|---|---|---|---|
| Perioperative RBC transfusion | 231 (48) | 47 (66) | 0.0764 | 1.68 (0.95–2.99) |
| Intraoperative RBC transfusion | 178 (37) | 32 (45) | 0.7100 | 1.11 (0.64–1.94) |
| Reoperation | 37 (8) | 7 (10) | 0.6846 | 0.82 (0.31–2.17) |
| ICU admission | 174 (36) | 41 (58) | 0.0224 | 1.95 (1.10–3.46) |
| ICU length of stay (days), n =215 | 1.9 (0.9, 4.1) | 2.6 (1.2, 3.9) | 0.6971 | −0.04 (−0.7 to 0.8) |
| Postoperative MV | 33 (7) | 8 (14) | 0.7936 | 1.14 (0.43–3.00) |
| Duration of MV (days), n =41 | 2.0 (0.1, 8.6) | 6.5 (2.0, 17.2) | 0.2112 | 3.8 (−4.0 to 12.3) |
| Hospital LOS (days) | 9.3 (3.8, 21.3) | 15.1 (6.5, 41.1) | 0.0006 | 7.2 (0.8–13.9) |
| Mortality | 70 (15) | 19 (27) | 0.5968 | 1.20 (0.62–2.32) |
Data are reported as number (%) for categorical outcomes and median (Q1, Q3) for continuous outcomes.
Estimates and p values are from stratified logistic regression for categorical outcomes and mixed-effects model for hospital length of stay. ICU length of stay and duration of mechanical ventilation are summarized for those who required these interventions and compared between groups using the rank-sum test.
LOS =length of stay; MV =mechanical ventilation.
DISCUSSION
In this investigation, we aimed to evaluate the relationship between prophylactic PLT transfusion and perioperative RBC requirements in those with a preoperative PLT count of not more than 100 × 109/L. While preoperative thrombocytopenia was associated with increased perioperative bleeding complications, preoperative PLT transfusion did not mitigate these risks. In propensity adjusted analyses, there was no evidence for improved patient outcomes with preoperative PLT transfusion.
Thrombocytopenia is relatively common in the pre-operative period, occurring in 6% of patients in the present investigation. Similar to recently published data from Glance and colleagues,17 preoperative thrombocytopenia was associated with adverse patient outcomes including increased perioperative RBC requirements, higher rates of reoperation for bleeding, and greater hospital mortality. While the precise mechanism associating thrombocytopenia with poor patient outcomes remains unclear and causality cannot be established based on these data alone, there are several plausible explanations for poor outcomes in the setting of preoperative thrombocytopenia including a potential increase in perioperative blood loss in those with low starting PLT counts, a higher rate of transfusion-associated complications, and more severe systemic disease (diagnosed or occult) in patients with thrombocytopenia with PLT count serving as a surrogate marker for disease or as an inherent disease manifestation.
It would then seem logical that correction of thrombocytopenia preoperatively would prevent perioperative bleeding complications. However, results from the present investigation suggest that preoperative PLT transfusions do not have their intended effect, as perioperative RBC requirements were not significantly different between those who received preoperative PLTs and those who did not. When utilizing lower PLT transfusion thresholds of 75 × 109 and 50 × 109/L, preoperative administration of PLTs was associated with increased rates of perioperative RBC transfusion.
There are several theoretical mechanisms to explain the lack of observed benefit after treatment of preoperative thrombocytopenia. The first explanation assumes that the relationship between preoperative PLT transfusion and perioperative bleeding complications is a reflection of inherent heterogeneity of provider-specific transfusion practices. In other words, it may be that providers inclined to transfuse PLTs preoperatively will also be more likely to transfuse RBCs in the perioperative period. It is also possible that the aforementioned results are confounded by residual indication bias regarding the decision to administer preoperative PLTs or perioperative RBCs. It should be noted that the precise etiology of thrombocytopenia was not delineated in this investigation, and patient responses to PLT transfusion may depend on the underlying reason for thrombocytopenia.28 PLT administration is also associated with a variety of transfusion-related reactions, including febrile nonhemolytic, hemolytic, allergic, anaphylactic, transient immune-mediated thrombocytopenia (also referred to as passive alloantibody thrombocytopenia), transfusion-related acute lung injury (TRALI), and septic complications.29 It is possible that management of these transfusion-associated reactions could contribute to increased perioperative RBC requirements, although this is unlikely given the low incidence of these reactions. Finally, given the lack of association between preoperative PLT transfusions and the outcomes of interest with propensity adjustment, it may simply be that PLT transfusions are not effective in preventing bleeding complications in the studied surgical population.
Notable strengths of this investigation include a large sample size, a heterogeneous surgical population, innovative data extraction strategies with precise determinations of event timings, and a robust statistical approach with propensity adjustments and multiple sensitivity analyses planned a priori. However, this study also has important limitations. The first major limitation is the observational study design with the associated inherent risks for residual bias and confounding. As an example, precise determinations of the circumstances influencing the decision to transfuse when confronted with preoperative thrombocytopenia remains an important limitation. By the same token, transfusion practices were likely impacted by unique considerations relating to the anesthesiologist or surgeon providing care. In addition, the relationship between prophylactic PLT transfusion and perioperative bleeding complications represents an association, and direct causality cannot be inferred. As this study relies on retrospective observational data, it is possible that unmeasured bias and confounding remain despite the robustness of the data extraction strategies and methodical statistical approach. Moreover, this investigation represents only a single institution’s experience. Confirmation of these results in differing care locations will be needed to confirm the generalizability of the study findings. Additionally, the exclusion of intraoperative PLT transfusions could have impacted the study results. However, this exclusion was intentional and prespecified in the study protocol to prevent cause-effect inversion with the outcomes of interest. As mentioned previously, it must also be noted that estimates of intraoperative blood loss were missing for approximately 50% of cases, including simple procedures with low bleeding risk and longer procedures with high bleeding risk. Hence, estimated blood loss could not be reliably used as an outcome measure. Finally, data were not available to adequately assess PLT recovery responses after prophylactic transfusion, and hence it is unclear if outcomes in patients who remained thrombocytopenic despite preoperative transfusion differed from those who achieved higher PLT counts after transfusion. Certainly, the results of this study would greatly benefit from validation in a large multicenter cohort or a randomized clinical trial.
In conclusion, preoperative thrombocytopenia is associated with increased perioperative RBC requirements. However, attempts to mitigate bleeding complications with preoperative PLT transfusions do not result in improved outcomes. In light of these findings, more conservative management of preoperative thrombocytopenia may be warranted.
Supplementary Material
Table S1. Number of RBC units transfused by the presence or absence of preoperative platelet transfusion in the propensity-adjusted cohort.
Table S2. Sensitivity analyses evaluating the associations between preoperative platelet administration and perioperative RBC transfusion.
Acknowledgments
This study was funded by an NIH grant to Dr. Daryl Kor (R01 HL121232), in addition to support from the Mayo Clinic Department of Anesthesiology and the Critical Care Integrated Multidisciplinary Practice, Rochester, Minnesota.
ABBREVIATIONS
- ASA PS
American Society of Anesthesiologists Physical Classification Score
- ICU
intensive care unit
- INR
international normalized ratio
- IQR
interquartile range
Footnotes
CONFLICT OF INTEREST
The authors have disclosed no conflicts of interest.
References
- 1.Bernard AC, Davenport DL, Chang PK, et al. Intraoperative transfusion of 1 U to 2 U packed red blood cells is associated with increased 30-day mortality, surgical-site infection, pneumonia, and sepsis in general surgery patients. J Am Coll Surg. 2009;208:931–7. 937 e1–2. doi: 10.1016/j.jamcollsurg.2008.11.019. discussion 938-9. [DOI] [PubMed] [Google Scholar]
- 2.Glance LG, Dick AW, Mukamel DB, et al. Association between intraoperative blood transfusion and mortality and morbidity in patients undergoing noncardiac surgery. Anesthesiology. 2011;114:283–92. doi: 10.1097/ALN.0b013e3182054d06. [DOI] [PubMed] [Google Scholar]
- 3.Hein OV, Birnbaum J, Wernecke KD, et al. Three-year survival after four major post-cardiac operative complications. Crit Care Med. 2006;34:2729–37. doi: 10.1097/01.CCM.0000242519.71319.AD. [DOI] [PubMed] [Google Scholar]
- 4.Jung SW, Hwang S, Namgoong JM, et al. Incidence and management of postoperative abdominal bleeding after liver transplantation. Transplant Proc. 2012;44:765–8. doi: 10.1016/j.transproceed.2012.01.011. [DOI] [PubMed] [Google Scholar]
- 5.Marik PE, Corwin HL. Efficacy of red blood cell transfusion in the critically ill: a systematic review of the literature. Crit Care Med. 2008;36:2667–74. doi: 10.1097/CCM.0b013e3181844677. [DOI] [PubMed] [Google Scholar]
- 6.Murphy GJ, Reeves BC, Rogers CA, et al. Increased mortality, postoperative morbidity, and cost after red blood cell transfusion in patients having cardiac surgery. Circulation. 2007;116:2544–52. doi: 10.1161/CIRCULATIONAHA.107.698977. [DOI] [PubMed] [Google Scholar]
- 7.Napolitano LM, Kurek S, Luchette FA, et al. Clinical practice guideline: red blood cell transfusion in adult trauma and critical care. Crit Care Med. 2009;37:3124–57. doi: 10.1097/CCM.0b013e3181b39f1b. [DOI] [PubMed] [Google Scholar]
- 8.The 2011 national blood collection and utilization survey. Washington (DC): Department of Health and Human Services; 2011. [Google Scholar]
- 9.Shander A, Hofmann A, Ozawa S, et al. Activity-based costs of blood transfusions in surgical patients at four hospitals. Transfusion. 2010;50:753–65. doi: 10.1111/j.1537-2995.2009.02518.x. [DOI] [PubMed] [Google Scholar]
- 10.García-Miguel FJ, Serrano-Aguilar PG, López-Bastida J. Pre-operative assessment. Lancet. 2003;362:1749–57. doi: 10.1016/s0140-6736(03)14857-x. [DOI] [PubMed] [Google Scholar]
- 11.Ramsey G, Arvan DA, Stewart S, et al. Do preoperative laboratory tests predict blood transfusion needs in cardiac operations? J Thorac Cardiovasc Surg. 1983;85:564–9. [PubMed] [Google Scholar]
- 12.Kaplan EB, Sheiner LB, Boeckmann AJ, et al. The usefulness of preoperative laboratory screening. JAMA. 1985;253:3576–81. [PubMed] [Google Scholar]
- 13.Dzankic S, Pastor D, Gonzalez C, et al. The prevalence and predictive value of abnormal preoperative laboratory tests in elderly surgical patients. Anesth Analg. 2001;93:301–8. doi: 10.1097/00000539-200108000-00013. 2nd contents page. [DOI] [PubMed] [Google Scholar]
- 14.Houry S, Georgeac C, Hay JM, et al. A prospective multicenter evaluation of preoperative hemostatic screening tests. The French Associations for Surgical Research. Am J Surg. 1995;170:19–23. doi: 10.1016/s0002-9610(99)80245-1. [DOI] [PubMed] [Google Scholar]
- 15.Rohrer MJ, Michelotti MC, Nahrwold DL. A prospective evaluation of the efficacy of preoperative coagulation testing. Ann Surg. 1988;208:554–7. doi: 10.1097/00000658-198811000-00002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Apfelbaum JL, Connis RT, Nickinovich DG, et al. Practice advisory for preanesthesia evaluation: an updated report by the American Society of Anesthesiologists Task Force on Pre-anesthesia Evaluation. Anesthesiology. 2012;116:522–38. doi: 10.1097/ALN.0b013e31823c1067. [DOI] [PubMed] [Google Scholar]
- 17.Glance LG, Blumberg N, Eaton MP, et al. Preoperative thrombocytopenia and postoperative outcomes after non-cardiac surgery. Anesthesiology. 2014;120:62–75. doi: 10.1097/ALN.0b013e3182a4441f. [DOI] [PubMed] [Google Scholar]
- 18.Kumar A, Mhaskar R, Grossman BJ, et al. Platelet transfusion: a systematic review of the clinical evidence. Transfusion. 2015;55:1116–27. doi: 10.1111/trf.12943. [DOI] [PubMed] [Google Scholar]
- 19.Heddle NM, Blajchman MA, Meyer RM, et al. A randomized controlled trial comparing the frequency of acute reactions to plasma-removed platelets and prestorage WBC-reduced platelets. Transfusion. 2002;42:556–66. doi: 10.1046/j.1537-2995.2002.00094.x. [DOI] [PubMed] [Google Scholar]
- 20.Savage WJ, Tobian AA, Fuller AK, et al. Allergic transfusion reactions to platelets are associated more with recipient and donor factors than with product attributes. Transfusion. 2011;51:1716–22. doi: 10.1111/j.1537-2995.2010.03009.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.von Elm E, Altman DG, Egger M, et al. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370:1453–7. doi: 10.1016/S0140-6736(07)61602-X. [DOI] [PubMed] [Google Scholar]
- 22.Herasevich V, Kor DJ, Li M, et al. ICU data mart: a non-iT approach. A team of clinicians, researchers and informatics personnel at the Mayo Clinic have taken a homegrown approach to building an ICU data mart. Healthc Inform. 2011;28:4–5. [PubMed] [Google Scholar]
- 23.Chute CG, Beck SA, Fisk TB, et al. The enterprise data trust at Mayo Clinic: a semantically integrated warehouse of biomedical data. J Am Med Inform Assoc. 2010;17:131–5. doi: 10.1136/jamia.2009.002691. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Singh B, Singh A, Ahmed A, et al. Derivation and validation of automated electronic search strategies to extract Charlson comorbidities from electronic medical records. Mayo Clin Proc. 2012;87:817–24. doi: 10.1016/j.mayocp.2012.04.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.American Society of Anesthesiologists Task Force on Perioperative Blood Transfusion and Adjuvant Therapies. Practice guidelines for perioperative blood transfusion and adjuvant therapies: an updated report by the American Society of Anesthesiologists Task Force on Perioperative Blood Transfusion and Adjuvant Therapies. Anesthesiology. 2006;105:198–208. doi: 10.1097/00000542-200607000-00030. [DOI] [PubMed] [Google Scholar]
- 26.Qian F, Osler TM, Eaton MP, et al. Variation of blood transfusion in patients undergoing major noncardiac surgery. Ann Surg. 2013;257:266–78. doi: 10.1097/SLA.0b013e31825ffc37. [DOI] [PubMed] [Google Scholar]
- 27.Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41–55. [Google Scholar]
- 28.Samama CM, Djoudi R, Lecompte T, et al. Perioperative platelet transfusion. Recommendations of the French Health Products Safety Agency (AFSSAPS) 2003. Minerva Anestesiol. 2006;72:447–52. [PubMed] [Google Scholar]
- 29.Kiefel V. Reactions induced by platelet transfusions. Transfus Med Hemother. 2008;35:354–8. doi: 10.1159/000151350. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1. Number of RBC units transfused by the presence or absence of preoperative platelet transfusion in the propensity-adjusted cohort.
Table S2. Sensitivity analyses evaluating the associations between preoperative platelet administration and perioperative RBC transfusion.