Abstract
Background:
Information on transfusion-associated outcomes is limited in sub-Saharan Africa. We sought to characterize predictors of mortality in transfused patients with acute care surgical conditions in Malawi.
Materials and Methods:
We performed a retrospective propensity-matched analysis of patients with acute care surgical conditions at Kamuzu Central Hospital in Malawi from 2013-2021. We compared outcomes between patients who did and did not receive transfusions.
Results:
A total of 7,395 patients were included. Transfused patients (n=1,086) were older (median 43 years with interquartile range [IQR] 30-59, versus 39 years [IQR 27-53] in the non-transfused group, p<0.01), had a higher proportion of females (41% versus 27%, p<0.01), presented earlier to the hospital (median 2.9 versus 3.7 days, p=0.02), and with lower hemoglobin levels (27% versus 1% <7 gram/deciliter, p<0.01). They had a lower rate of surgical intervention (48% versus 59%, p<0.01) but a higher rate of complications (62% versus 33%, p<0.01). Crude in-hospital mortality was 25.5% for the transfused group and 12.8% for the non-transfused group (p<0.01). After propensity matching, transfused patients had three times the odds of mortality compared to non-transfused patients (odds ratio 3.3, 95% confidence interval 2.3, 4.8).
Conclusion:
In this propensity-matched study, transfused surgical patients were more likely to experience in-hospital mortality. These results suggest that the transfusion requirement reflects critical illness and warrants further investigation in this low-resource setting.
Keywords: Transfusion, anemia, surgery, Malawi
Introduction
Essential surgical care is a vital initiative of the World Health Organization and an integral component of the Sustainable Development Goals. Recent estimates suggest that 11% of the global disease burden can be treated with surgery, and surgical conditions accounted for 16.9 million lives lost, or a third of deaths worldwide in 2010 [1]. There is a disproportional surgical morbidity and mortality burden in low- and middle-income countries (LMICs), where healthcare delivery systems are underdeveloped within a milieu of limited surgical capacity [2-4]. Despite increasing emphasis on developing surgical capacity, little information is available regarding surgical outcomes [5]. This is especially important in LMICs, where comorbidities are under-reported and their impact on outcomes poorly understood [6].
Anemia is a public health problem worldwide, with the most significant burden in LMICs. Anemia affects 1.8 billion people and accounts for 50 million years lived with disability (YLD) [7]. In sub-Saharan Africa (SSA), malnutrition, helminth infections, human immunodeficiency virus (HIV) infection, road traffic injury, and hemoglobinopathies are other important causes of severe anemia [8-10]. Allogeneic blood transfusion has long been accepted as a way to rapidly correct the physiologic abnormalities associated with anemia and improve patient outcomes, and it remains the cornerstone of anemia treatment. At the same time, blood transfusions have well-recognized challenges, including the need to type and crossmatch and the potential transmission of diseases, such as hepatitis B and C, human immunodeficiency virus, and prions [11]. However, anemia is beset with cardiovascular sequelae and is associated with increased morbidity and mortality among surgical patients in high- and low-income settings.
Transfusion-related outcomes among surgical patients are not well-characterized in SSA. Given the high burden of chronic anemia and the prevalence of preoperative anemia in the surgical population within an environment of low allogeneic blood availability, we aim to evaluate the association between transfusion in acute care surgical patients and mortality in Malawi.
Methods
Malawi is located in southeastern Africa, with a population of 19 million people, of whom half live in poverty [12]. Malawi’s health system is organized into three levels: community health centers, district hospitals, and central hospitals, linked by referrals to higher levels of care [13]. Surgical services are available at tertiary facilities, with some district hospitals having limited surgical capacity [8]. This study is based at Kamuzu Central Hospital (KCH), a 1000-bed tertiary referral center serving approximately 9 million people in central Malawi. A team of attendings, residents, and clinical officers provides surgical care at KCH in the emergency department, wards, and operating rooms.
An acute care surgery registry has been prospectively collecting data, and we performed a retrospective review of all acute care surgical patients between 2013 and 2021. Demographic and clinical information were collected. We compared outcomes in transfused and non-transfused patients. Bivariate analyses were performed with Student’s t-test for normally distributed continuous variables, chi-squared test for categorical variables, and Kruskal-Wallis test for ordinal variables. To assess the normality of continuous variables, skewness and kurtosis tests were used.
Propensity matching was estimated using a logistic regression model that included all potential confounders (age, sex, time to presentation at the initial facility, transfer status, shock index, hemoglobin levels, and time to the operating room). The reduced model was determined after backward stepwise regression. To control for baseline differences between the transfused and non-transfused cohorts, we weighted the cohorts using inverse probability of treatment weights (IPTW) derived from the propensity score. We used IPTW to avoid losing study subjects, which could occur during the matching process. To confirm the equalization of differences in baseline covariates between the transfused versus non-transfused cohorts after applying the propensity score, we performed a balance assessment of our IPTW samples using mean standardized differences. Logistic regression analysis was then used to evaluate blood transfusion as a predictor of mortality in the propensity-matched cohorts. Complications include wound infections, abdominal dehiscence, urinary tract infections, and re-operation. Due to limited diagnostic adjuncts, deep vein thrombosis and pneumonia are unable to be reliably captured.
Statistical analyses were performed in Stata 17.0 (College Station, Texas). The Malawi National Health Science Research Committee and the University of North Carolina Institutional Review Board approved this study. Informed consent for participation in this study was waived by both research ethics committees.
Results
A total of 7,395 patients were included. The transfused group included 1,086 patients, and the non-transfused group included 6,309 patients (Table 1). The transfused group was older, with a median age of 43 (interquartile range [IQR] 30-59) versus 39 (IQR 27-53) in the non-transfused group (p<0.01). The transfused group also had a higher proportion of women (40.8% versus 27.4%, p<0.01). The median time to presentation at KCH was shorter for the transfused group (2.9 days) compared to the non-transfused group (3.7 days, p=0.02). The median time from presentation at KCH to the operating room was longer for the transfused group (1 [IQR 0-4] versus 0 [IQR 0-1]). The transfused group had a higher proportion of patients who were in severe shock (32.2% versus 28.6% with shock index >1.4) or no shock (15.6% versus 7.0% with shock index ≤0.6, p<0.01) and who had hemoglobin level < 7 gram/deciliter [g/dl] (27.0% versus 1.0%, p<0.01). Among patients with hemoglobin level < 7 g/dl, 81.9% received a blood transfusion. The most common indication for surgery for the non-transfused group was inguinal hernia repair, followed by small bowel surgery (Table 2). In comparison, in the transfused group, the most common indication was ileostomy, followed by other types of small bowel surgery.
Table 1.
Demographic and clinical characteristics of patients with acute care surgical conditions, by receipt of transfusion
| Transfused n=1,086 |
Non-Transfused n=6,309 |
P Value | |
|---|---|---|---|
| Age, mean in years ± standard deviation | 44.1 ± 18.3 | 40.9 ± 18.1 | <0.01 * |
|
| |||
| Sex | |||
| Male, no. (%) | 641 (59.2%)) | 4,580 (72.6%) | |
| Female, no. (%) | 442 (40.8%) | 1,728 (27.4%) | <0.01 * |
|
| |||
| Time to presentation at KCH, median days (interquartile range) | 2.9 (0.7, 8.3) | 3.7 (1.6, 9.2) | 0.02 * |
|
| |||
| Transfer | |||
| Yes, no. (%) | 802 (74.1%) | 4,583 (72.9%) | |
| No, no. (%) | 281 (26.0%) | 1,700 (27.1%) | 0.45 |
|
| |||
| Time from presentation at KCH to operating room, mean days ± standard deviation | 4.6 ± 11.5 | 1.9 ± 21.2 | 0.14 |
|
| |||
| Shock index at presentation to KCH | |||
| No shock (≤0.6), no. (%) | 986 (15.6%) | 76 (7.0%) | |
| Mild shock (0.6-1.0), no. (%) | 2,677 (42.4%) | 460 (42.4%) | |
| Moderate shock (>1.0 and ≤1.4), no. (%) | 614 (9.7%) | 239 (22.0%) | |
| Severe shock (>1.4), no. (%) | 2,032 (32.2%) | 311 (28.6%) | <0.01 * |
|
| |||
| Hemoglobin level, gram/deciliter | |||
| ≥ 8 | 655 (64.3%) | 5,862 (98.3%) | <0.01 * |
| ≥ 7 and <8 | 89 (8.7%) | 41 (0.7%) | |
| < 7 | 275 (27.0%) | 61 (1.0%) | |
|
| |||
| Surgery | |||
| Yes, no. (%) | 516 (47.6%) | 3,745 (59.4%) | |
| No, no. (%) | 569 (52.4%) | 2,557 (40.6%) | <0.01 * |
|
| |||
| Complications | |||
| Yes, no. (%) | 674 (62.1%) | 2,099 (33.3%) | |
| No, no. (%) | 412 (37.9%) | 4,210 (66.7%) | <0.01 * |
Abbreviations: KCH Kamuzu Central Hospital
Statistically significant
Table 2.
Indications for surgery, by receipt of transfusion
| Transfused n=1,086 |
Non-Transfused n=6,309 |
P Value | |
|---|---|---|---|
| Small bowel repair/resection/anastomosis | 53 (10.7%) | 372 (10.5%) | |
| Ileostomy | 55 (11.1%) | 151 (4.2%) | |
| Ileostomy reversal | 5 (1.0%) | 76 (2.1%) | |
| Large bowel repair/resection/anastomosis | 22 (4.4%) | 252 (7.1%) | |
| Colostomy/colostomy revision | 22 (4.4%) | 101 (2.8%) | |
| Colostomy reversal | 2 (0.4%) | 53 (1.5%) | |
| Appendectomy | 10 (2.0%) | 265 (7.4%) | |
| Mesosigmoidopexy | 0 (0.0%) | 24 (0.7%) | |
| Splenectomy | 5 (1.0%) | 6 (0.2%) | |
| Graham patch | 19 (3.8%) | 176 (5.0%) | |
| Gastrectomy | 1 (0.2%) | 8 (0.2%) | |
| Release of adhesions | 25 (5.0%) | 172 (4.8%) | |
| Abdominal washout | 21 (4.2%) | 68 (1.9%) | |
| Biopsy | 11 (2.2%) | 73 (2.1%) | |
| Decompression/de-rotation | 8 (1.6%) | 124 (3.5%) | |
| Negative exploratory laparotomy | 1 (0.2%) | 61 (1.7%) | |
| Inguinal hernia repair | 6 (1.2%) | 610 (17.1%) | |
| Umbilical hernia repair | 1 (0.2%) | 68 (1.9%) | |
| Ventral hernia repair | 0 (0.0%) | 15 (0.4%) | |
| Abdominal closure | 4 (0.8%) | 23 (0.7%) | |
| Debridement | 37 (7.5%) | 121 (3.4%) | |
| Incision and drainage | 9 (1.8%) | 57 (1.6%) | |
| Amputation, above knee | 14 (2.8%) | 20 (0.6%) | |
| Amputation, below knee | 29 (5.8%) | 44 (1.2%) | |
| Partial or complete mastectomy | 2 (0.4%) | 57 (1.6%) | |
| Axillary dissection | 0 (0.0%) | 3 (0.1%) | |
| Urological procedures | 1 (0.2%) | 18 (0.5%) | |
| Other | 133 (26.8%) | 540 (15.2%) | <0.01* |
Statistically significant
Fewer patients in the transfused group underwent surgical intervention (47.6% versus 59.4%, p<0.01), though more of them had complications (62.1% versus 33.3%, p<0.01). Crude in-hospital mortality was 25.5% for the transfused group and 12.8% for the non-transfused group (p<0.01). Over the study period, predicted mortality for patients with acute care surgical conditions has declined for transfused patients and slightly increased for non-transfused patients (Figure 1). The median age of patients has increased over time (median of 32 [IQR 21-42] in 2013 versus a median of 42 [IQR 28-57] in 2021).
Figure 1.
Predicted mortality after presenting to Kamuzu Central Hospital with acute care surgical conditions by receipt of transfusion.
Weighted analysis showed that transfused and non-transfused patients were balanced across these baseline characteristics (Table 3). After propensity matching, the odds ratio of mortality for transfused patients is 3.3 (95% confidence interval 2.3, 4.8).
Table 3.
Multivariate logistic regression of predictors of transfusion for acute care surgical conditions, before and after propensity score weighted matching
| Unweighted | Weighted | |||||
|---|---|---|---|---|---|---|
| OR | (95% CI) | P value | OR | (95% CI) | P value | |
| Age categories (ref = 0 to ≤ 5 years) | ||||||
| > 5 and ≤ 15 years | 0.6 | (0.2, 1.4) | 0.21 | 0.5 | (0.1, 2.0) | 0.33 |
| > 15 and ≤ 45 years | 0.3 | (0.1, 0.5) | <0.01 * | 0.5 | (0.1, 1.6) | 0.24 |
| > 45 and ≤ 60 years | 0.3 | (0.1, 0.7) | <0.01 * | 0.4 | (0.1, 1.5) | 0.20 |
| > 60 years | 0.4 | (0.2, 0.9) | 0.03 * | 0.9 | (0.2, 3.6) | 0.87 |
|
| ||||||
| Sex (ref = male) | 2.0 | (1.6, 2.5) | <0.01 * | 1.0 | (0.7, 1.3) | 0.79 |
|
| ||||||
| Transfer (ref = no) | 1.1 | (0.8, 1.5) | 0.52 | 1.1 | (0.7, 1.7) | 0.64 |
|
| ||||||
| Shock index at presentation to KCH (ref = no shock ≤0.6) | ||||||
| Mild (0.6-1.0) | 2.0 | (1.3, 3.0) | <0.01 * | 1.4 | (0.9, 2.3) | 0.18 |
| Moderate (>1.0 & ≤1.4) | 3.0 | (1.9, 4.9) | <0.01 * | 1.5 | (0.8, 2.7) | 0.19 |
| Severe (>1.4) | 2.0 | (1.3, 3.2) | <0.01 * | 1.3 | (0.8, 2.2) | 0.31 |
|
| ||||||
| Hemoglobin level (ref = ≥ 8 gram/deciliter) | ||||||
| ≥ 7 and < 8 | 10.0 | (5.5, 18.0) | <0.01 * | 0.9 | (0.5, 1.6) | 0.69 |
| < 7 | 31.1 | (18.2, 53.1) | <0.01 * | 1.1 | (0.6, 1.9) | 0.75 |
|
| ||||||
| Type of surgery (ref = negative laparotomy) | ||||||
| Small bowel repair/resection/anastomosis | 8.0 | (1.1, 59.5) | 0.04 * | 0.6 | (0.1, 4.2) | 0.59 |
| Ileostomy | 20.4 | (2.7, 152.3) | <0.01 * | 0.6 | (0.1, 4.2) | 0.58 |
| Ileostomy reversal | 5.7 | (0.6, 51.0) | 0.12 | 0.9 | (0.1, 8.8) | 0.96 |
| Large bowel repair/resection/anastomosis | 6.2 | (0.8, 47.8) | 0.08 | 0.6 | (0.1, 4.4) | 0.60 |
| Colostomy/colostomy revision | 13.1 | (1.7, 101.4) | 0.01 * | 0.6 | (0.1, 4.2) | 0.57 |
| Colostomy reversal | 3.5 | (0.3, 41.0) | 0.31 | 0.8 | (0.1, 9.1) | 0.84 |
| Appendectomy | 2.2 | (0.3, 17.9) | 0.46 | 0.5 | (0.1, 4.3) | 0.54 |
| Splenectomy | 28.0 | (2.4, 326.4) | 0.01 * | 0.7 | (0.1, 6.9) | 0.75 |
| Graham patch | 7.7 | (1.0, 59.7) | 0.05 * | 0.4 | (0.1, 3.4) | 0.44 |
| Gastrectomy | 7.5 | (0.4, 142.0) | 0.18 | 0.3 | (0.0, 4.5) | 0.39 |
| Release of adhesions | 7.7 | (1.0, 58.5) | 0.05 * | 0.6 | (0.1, 4.2) | 0.58 |
| Abdominal washout | 21.3 | (2.8, 165.1) | <0.01 * | 0.7 | (0.1, 5.3) | 0.72 |
| Biopsy | 6.0 | (0.7, 49.9) | 0.10 | 0.7 | (0.1, 6.3) | 0.75 |
| Decompression/de-rotation | 5.2 | (0.6, 43.2) | 0.13 | 0.5 | (0.1, 4.6) | 0.56 |
| Inguinal hernia repair | 0.8 | (0.09, 6.65) | 0.82 | 0.3 | (0.0, 2.2) | 0.23 |
| Umbilical hernia repair | 0.6 | (0.04, 10.4) | 0.74 | 0.7 | (0.0, 11.8) | 0.81 |
| Abdominal closure | 8.6 | (0.88, 84.7) | 0.06 | 0.6 | (0.1, 5.9) | 0.68 |
| Debridement | 14.5 | (1.9, 110.6) | 0.01 * | 0.5 | (0.1, 3.8) | 0.52 |
| Incision and drainage | 8.8 | (1.05, 73.3) | 0.05 * | 0.7 | (0.1, 6.4) | 0.77 |
| Amputation, above knee | 18.2 | (2.1, 159.1) | <0.01 * | 0.6 | (0.1, 5.1) | 0.63 |
| Amputation, below knee | 24.2 | (3.1, 190.6) | <0.01 * | 0.5 | (0.1, 3.9) | 0.52 |
| Partial/complete mastectomy | 1.8 | (0.2, 20.8) | 0.63 | 0.7 | (0.1, 7.6) | 0.75 |
| Urological procedures | 2.5 | (0.1, 56.4) | 0.56 | 0.6 | (0.0, 8.1) | 0.67 |
| Other | 10.9 | (1.5, 80.4) | <0.02 * | 0.6 | (0.1, 4.1) | 0.58 |
Abbreviations: CI confidence interval, OR odds ratio, KCH Kamuzu Central Hospital
Statistically significant
Discussion
The baseline prevalence of anemia in sub-Saharan Africa is high. In perioperative patients with anemia, blood transfusion can be lifesaving and is the logical therapeutic strategy for patients with acute hemorrhage, hemodynamic instability, or inadequate oxygen delivery. This propensity-matched analysis shows that allogeneic blood transfusion is independently associated with increased mortality in this cohort of acute care surgical patients. However, predicted mortality over time for patients who received transfusions has decreased.
We found that transfused patients had a higher rate of mortality in this study. This finding is consistent with the literature, where transfusion has been identified as a predictor of mortality in critically ill patients [14]. Previous studies have identified a correlation between transfusion and outcomes such as increasing short- and long-term mortality, healthcare-related infections, multiorgan failure, and acute respiratory distress syndrome [15,16]. While the mechanism underlying this relationship is poorly understood, blood product-related immunomodulation has been proposed [17,18]. A recent study also suggests a role for persistent inflammation and immunosuppression secondary to transfusions in critically ill patients [18]. Immunomodulation may help explain the increased mortality among transfused patients in this study within the context of non-leukocyte-reduced blood, which is ubiquitous in Malawi. The synergistic interactions between anemia and transfusion and their association with mortality have been previously observed in patients with colorectal cancer and undergoing cardiac surgery [19].
In this study, the rate of surgical intervention in the transfused group is lower than in the non-transfused group. The observed lower rate of surgeries in this group can be partially attributed to challenges related to lack of resources. For example, staffing shortages and operating room availability may have led to in-hospital delays in surgical treatment, resulting in increased mortality [20]. In addition, transfused patients may have had a higher severity of illness requiring initial resuscitation. While necessary, these initial resuscitative efforts may have contributed to additional surgical delay, which in turn can contribute to increased mortality.
More broadly, from a perioperative standpoint, anemia is an independent risk factor for complications. In high-income settings, preoperative anemia is associated with higher rates of acute kidney injury, infection, mortality, and readmission rates [9,21,22]. Findings were similar for patients undergoing both elective procedures and emergency surgery. In comparison, patients in LMICs experienced more complications even though they tended to be younger and healthier [23,24]. Given the epidemiology of anemia in SSA, these findings suggest that anemia may be a modifiable risk factor for patients undergoing elective procedures.
In this study, transfused patients experienced a decline in predicted mortality over time, while non-transfused patients had an increase in predicted mortality. This change can be partly attributed to improved capacity in caring for acute care surgery patients in the last decade with the establishment of a surgery residency program. In this context, patients who require blood transfusions are increasingly being appropriately triaged, and improved clinical management is correlated with decreasing mortality over time. In addition, with the advent of the Malawi Blood Transfusion Service and the prioritization of blood banking by the Ministry of Health on a national level, blood safety for transfused patients has increased [25]. At the same time, blood bank centralization has inadvertently contributed to the worsening blood shortage in Malawi for acutely hemorrhaging patients, with decreasing blood transfusions per patient over time [26]. In comparison, predicted mortality for non-transfused patients has increased over time, which may reflect an aging population and patients with higher severity of illness who present to the hospital.
In this context, the optimal transfusion target for patients with anemia remains an active area of research. Previously, restrictive targets have been shown to have similar outcomes to more liberal transfusion strategies for cardiac and non-cardiac surgical patients [27]. In recent years, the World Health Organization has advocated the multimodal approach of patient blood management (PBM) to improve outcomes, increase stewardship of blood products as scarce resources, and strengthen health system governance [28]. In SSA, many challenges hinder the implementation of PBM, from the shortage of blood and unreliable storage infrastructure to inefficient coordination and distribution of blood products [29]. In addition, decisions about when or whether to administer blood products are fraught with individual bias. They are influenced by heterogeneous patient comorbidities, surgical team preferences, and input from other specialists such as anesthesiologists. These gaps highlight the importance of tailored approaches to developing safe blood systems according to the local context.
Results from this study must be interpreted with limitations. First, our study is a retrospective analysis of a prospectively collected registry. In addition, data on complications are limited due to the minimal capacity for diagnostic adjuncts such as laboratory testing at KCH. Nevertheless, this study provides important information about the association between blood transfusions and outcomes in a surgical patient population.
Conclusion
In this propensity-matched study, transfused surgical patients were more likely to experience in-hospital mortality than non-transfused patients, though the odds of mortality have decreased over time. These results suggest that the transfusion requirement reflects critical illness and warrants further investigation in this low-resource setting.
Grant support:
The National Institutes of Health Fogarty International Center (Grant #D43TW009340) supported this study.
Footnotes
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Conflict of interest: The authors have no conflicts of interest.
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