Abstract
Background.
Acute kidney injury (AKI) is a common complication postheart transplantation and is associated with significant morbidity and increased mortality.
Methods.
We conducted a single-center, retrospective, observational cohort study of 109 consecutive patients undergoing heart transplantation between September 2019 and September 2021 to determine major risk factors for, and the incidence of, severe postoperative AKI as defined by Kidney Disease Improving Global Outcomes criteria in the first 48-h posttransplantation and the impact that this has on mortality and dialysis dependence.
Results.
One hundred nine patients were included in our study, 83 of 109 (78%) patients developed AKI, 42 (39%) developed severe AKI, and 37 (35%) required renal replacement therapy in the first-week posttransplantation. We found preoperative estimated glomerular filtration rate (eGFR), postoperative noradrenaline dose, and the need for postoperative mechanical circulatory support to be independent risk factors for the development of severe AKI. Patients who developed severe AKI had a 19% 12-mo mortality compared with 1% for those without. Of those who survived to hospital discharge, 20% of patients in the severe AKI group required dialysis at time of hospital discharge compared with 3% in those without severe AKI.
Conclusion.
Severe AKI is common after heart transplantation. Preoperative kidney function, postoperative vasoplegia with high requirements for vasoactive drugs, and graft dysfunction with the need for mechanical circulatory supports were independently associated with the development of severe AKI in the first-week following heart transplantation. Severe AKI is associated with a significantly increased mortality and dialysis dependence at time of hospital discharge.
Heart transplantation is a treatment option available for some patients with end stage cardiac disease that can substantially improve survival and quality of life.1 This procedure is commonly associated with complications, one of the most concerning of which is the development of acute kidney injury (AKI).
The kidneys are vulnerable organs to injury following heart transplantation due to many factors including preexisting impairment (particularly from cardiorenal interactions and comorbid conditions), susceptibility to low or nonpulsatile flow, venous congestion, and exposure to nephrotoxic drugs.
The reported incidence of AKI following heart transplantation varies between 14% and 83% and reported rates of renal replacement therapy (RRT) range from 5% to 46%.2–29 The consequences of developing AKI can be severe due to complex cardiorenal interactions and the impact on inflammatory cascades among numerous other effects. It has been shown that severe renal impairment in the early postoperative period is associated with increased early and late mortality, mechanical ventilation duration, length of stay, and healthcare-associated costs.2–29
We aimed to investigate the incidence of severe AKI in adult heart transplant recipients in our institution and analyze the association of plausible risk factors with the development of severe AKI. In addition, we aimed to assess the impact of severe AKI on outcomes such as early survival, dialysis dependence, duration of mechanical ventilation, intensive care unit (ICU) length of stay, and hospital length of stay.
MATERIALS AND METHODS
We conducted a single-center, retrospective, observational cohort study of consecutive patients who underwent isolated orthotopic heart transplantation between September 2019 and September 2021 at St Vincent’s Hospital Sydney. Those who were >18 y old or who were on any form of RRT in the immediate preoperative period were excluded.
We performed a search of multiple local databases developed specifically and maintained for the cardiothoracic transplant program at this center and electronic medical records used in the ICU and broader hospital medical records to collect detailed demographic, baseline clinical, intraoperative, postoperative, and outcome data with a particular focus on risk factors suspected to be associated with the development of AKI.
Patients who undergo heart transplantation at our institution receive a standardized immunosuppression protocol (Table S1, SDC, http://links.lww.com/TXD/A617). For defining and staging AKI, we used the Kidney Disease Improving Global Outcomes (KDIGO) guidelines30 and also collected data to grade AKI based on the RIFLE criteria31 to analyze definition concordance and to enable comparisons with prior studies. eGFR was calculated using the CKD-EPI formula.32 Baseline eGFR was based on the most recently documented serum creatinine before transplantation. We used the Inotrope Score (IS) as defined by Kobashigawa et al33 and Vasopressor Inotrope Score as defined by Gaiea et al.34
The primary aim of this study was to determine the incidence of postoperative severe AKI and to identify the risk factors for its development. The primary outcome measure was the incidence of KDIGO stage 3 AKI in the first-week following heart transplantation. Secondary outcome measures were ICU, hospital, 90-d mortality, and 12-mo mortality, dialysis at ICU discharge, 28 d, 90 d, and at hospital discharge, ICU and hospital length of stay, and duration of invasive mechanical ventilation.
For the statistical analysis, we used XLSTAT software by Addinsoft. Demographic and clinical patient data were grouped into those with stage 0–2 AKI and those with stage 3 AKI according to KDIGO criteria. We used Student t tests or Mann-Whitney U test for continuous variables and Chi-square or Fisher Exact test for categorical variables to detect any associations of data between these groups and the incidence of AKI. We considered a 2-sided P value of <0.05 significant, with 95% confidence intervals. A Bonferroni correction was applied to address the risk of type 1 error from multiplicity of testing. The data have been presented as median with interquartile range for continuous variables or as a count with percentile for categorical variables.
We used subject-specific background knowledge to guide variable selection for multivariable logistic regression analysis in view of their redundancy, availability, and chronology for building a multivariable model. We limited the ratio between the number of independent variables and the number of events in the less frequent outcome to 1:10 to minimize the risk of over-fitting the data. Variables were only included if they were not missing for >10% of the cohort and not known to correlate with each other. Multicollinearity was further assessed with calculation of variance inflation factors. Residual diagnostic plots of quantile residuals were inspected for violation of assumptions.35 We followed the advice of Heinze et al36 to fit a Firth’s penalized-likelihood logistic regression model with profile penalized-likelihood confidence intervals provided by the R package logistf in case of complete separation of individual variables.37
Data collection was carried out under The Intensive Care Observation Program and with strict compliance to the ISHLT ethics statement.38 The Intensive Care Observation Program is a retrospective observational program, which allows sampling of data from existing data already collected as part of routine clinical care and carries ethical approval from the hospital Human Research Ethics Committee.
RESULTS
Between September 2019 and September 2021, 114 isolated orthotopic heart transplantations were performed. Following exclusion of 2 patients aged <18 y and 3 patients who needed RRT preoperatively, data of 109 patients were included for analysis (Figure 1).
FIGURE 1.
Population flow chart.
Eighty-three (76%) patients developed AKI based on the KDIGO criteria, 30 patients (28%) stage 1, 11 patients (10%) stage 2, and 42 patients (39%) stage 3 AKI. Using the RIFLE AKI criteria 88 patients (81%) developed AKI, 31 patients (28%) developed stage 1 (risk), 15 patients (14%) stage 2 (injury), and 42 patients (39%) stage 3 (failure) AKI.
Patients with severe AKI were older and had a higher BMI, which was predominantly due to differences in weight rather than height. They had a higher rate of ischemic than nonischemic heart disease (P = 0.04) as an indication for transplant, had a lower preoperative eGFR, and a higher baseline creatinine. There were no significant differences in preoperative echocardiographic or right heart catheter results (Table 1).
TABLE 1.
Baseline characteristics and preoperative parameters
| Characteristic | Missing data | KDIGO stage | P | ||
|---|---|---|---|---|---|
| All patients | 0–2 | 3 | KDIGO stage | ||
| (n = 109) | (n = 67) | (n = 42) | 3 vs 0-2 | ||
| Demographics | |||||
| Male n (%) | 0 (0) | 86 (79) | 52 (78) | 34 (81) | 0.68 |
| Age (y) | 0 (0) | 58 (47–65) | 55 (46–64) | 62 (50–67) | 0.02 |
| Weight (kg) | 0 (0) | 80 (67–91) | 75 (66–91) | 84 (73–91) | 0.12 |
| Height (cm) | 0 (0) | 174 (165–180) | 174 (165–180) | 174 (163–180) | 0.86 |
| BMI (kg/m2) | 0 (0) | 26.6 (23.3–29.4) | 25.8 (22.6–28.2) | 27.9 (24.8–30.0) | 0.02 |
| Clinical baseline | |||||
| Indication for HTx | 0 (0) | 0.13 |
|||
| Ischemic | 34 (31) | 16 (24) | 18 (43) | ||
| Congenital | 6 (6) | 3 (4) | 3 (7) | ||
| Valvular | 1 (1) | 1(1) | 0 (0) | ||
| Other nonischemic | 68 (62) | 47 (70) | 21 (50) | ||
| Frailty Vulnerable/Severe | 34 (31) | 55 (73) | 30 (70) | 25 (78) | 0.42 |
| Hypertension | 0 (0) | 23 (21) | 14 (21) | 9 (21) | 0.95 |
| Diabetes | 0 (0) | 31 (28) | 22 (33) | 9 (21) | 0.20 |
| eGFR (mL/min/1.73m2) | 0 (0) | 61 (48–83) | 71 (54–86) | 54 (44–71) | 0.002 |
| Creatinine (µmol/L) | 0 (0) | 103 (89–133) | 98 (87–125) | 119 (96–147) | 0.02 |
| Cardiac function | |||||
| LV EF% | 4 (4) | 20 (15–30) | 20 (15–230 | 20 (15–26) | 0.70 |
| mPAP (mm Hg) | 5 (5) | 27 (21–34) | 27 (21–33) | 27 (21–34) | 0.90 |
| PCWP (mm Hg) | 5 (5) | 17 (13–25) | 18 (13–26) | 17 (14–24) | 0.99 |
| TPG (mm Hg) |
5 (5) | 8 (6–10) | 8 (6–10) | 8 (6–11) | 0.92 |
| PAPi | 5 (5) | 1.7 (1.3–2.7) | 1.9 (1.1–2.8) | 1.6 (1.3–2.3) | 0.65 |
| CI (L/min/m2) | 16 (15) | 2.1 (1.7–2.4) | 2.0 (1.7–2.5) | 2.2 (1.8–2.3) | 0.76 |
Values are expressed as median (interquartile range) or n (%).
BMI, body mass index; CI, cardiac index; eGFR, estimated glomerular filtration rate; HTx, heart transplant; IHD, ischemic heart disease; LV EF, left ventricular ejection fraction; mPAP, mean pulmonary artery pressure; PAPi, pulmonary artery pulsatility index; PCWP, pulmonary capillary wedge pressure; TPG, transpulmonary gradient.
Cardiopulmonary bypass (CPB) time and duration of operation were longer in the severe AKI group. Intraoperative peak lactate concentration was higher and total intraoperative urine output lower in this group (Table 2).
TABLE 2.
Intraoperative parameters
| Characteristic | Missing data | KDIGO stage | P | ||
|---|---|---|---|---|---|
| All patients | 0–2 | 3 | KDIGO stage | ||
| (n = 109) | (n = 67) | (n = 42) | 3 vs 0–2 | ||
| Prior sternotomy | 0 (0) | 57 (52) | 31 (46) | 26 (62) | 0.11 |
| VAD explant | 0 (0) | 40 (37) | 24 (36) | 16 (38) | 0.81 |
| DCDD donor | 0 (0) | 36 (33) | 20 (30) | 16 (38) | 0.37 |
| Ischemic time (min) | 3 (3) | 197 (149–250) | 191 (149–235) | 225 (152–262) | 0.14 |
| Cross clamp time min) | 0 (0) | 81 (72–95) | 79 (71–95) | 84 (77–94) | 0.07 |
| CPB time (min) | 14 (13) | 150 (131–183) | 143 (126–171) | 167 (146–211) | 0.002 |
| Operation time (h) | 1 (1) | 5.6 (4.6–6.4) | 5.3 (4.4–6.2) | 5.9 (5.4–6.9) | 0.01 |
| Peak lactate (mMol/L) | 0 (0) | 4.0 (2.7–5.7) | 3.5 (2.6–4.8) | 5.2 (3.2–7.5) | 0.001 |
| Total intraoperativeurine output (ml) | 21 (19) | 400 (290–628) | 500 (300–800) | 350 (180–500) | 0.005 |
| Red blood cell transfusion (units) | 0 (0) | 1 (0–2) | 1 (0–2) | 2 (0–4) | 0.21 |
| FFP transfusion (units) | 0 (0) | 2 (2–3) | 2 (2–3) | 2 (2–3) | 0.30 |
| Cryoprecipitate transfusion ṇ(units) | 0 (0) | 5 (4–8) | 5 (4–7) | 6 (4–8) | 0.15 |
| Platelet transfusion (units) | 0 (0) | 1 (1–2) | 1 (1–2) | 1 (1–2) | 0.22 |
| PCC administration (units) | 0 (0) | 1500 (0–2500) | 1500 (0–2250) | 2000 (0–2500) | 0.56 |
Values are expressed as median (interquartile range) or n (%).
CPB, cardiopulmonary bypass; DCDD, donation after circulatory determination of death; FFP, fresh frozen plasma; PCC, prothrombin complex concentrate; VAD, ventricular assist device.
On arrival to ICU, patients who developed severe AKI had a lower Cardiac Index, a lower Cardiac Power Output Index, and a higher lactate concentration. Within the first postoperative, 48 h patients with severe AKI had a significantly lower minimum mean arterial pressure and a higher peak lactate. They had significantly higher adrenaline, noradrenaline, and vasopressin dosage requirements, a higher Vasoactive Inotrope Score and a higher IS. Patients with severe AKI were significantly more likely to require mechanical circulatory support and to have more often left and right ventricular impairment on echocardiography. Patients with severe AKI had a lower minimum hemoglobin level and required significantly more blood product transfusions within the first 48 h (Table 3). No patients reached therapeutic or toxic calcineurin inhibitor levels in the 48-h timeframe.
TABLE 3.
Parameters on arrival to ICU and in the first 48 h of ICU admission
| Characteristic | Missing data |
KDIGO stage | P | ||
|---|---|---|---|---|---|
| All patients | 0–2 | 3 | KDIGO stage | ||
| (n = 109) | (n = 67) | (n = 42) | 3 vs 0–2 | ||
| Hemodynamics ICU arrival | |||||
| MAP (mm Hg) | 0 (0) | 71 (64–79) | 73 (65–79) | 69 (62–76) | 0.19 |
| CVP (mm Hg) | 0 (0) | 11 (8–14) | 11 (9–14) | 13 (8–14) | 0.83 |
| mPAP (mm Hg) | 2 (2) | 24 (20–28) | 25 (20–28) | 24 (20–27) | 0.84 |
| HR (bpm) | 0 (0) | 101 (97–111) | 101 (97–111) | 103 (100–111) | 0.39 |
| CI (L/min/m2) | 2 (2) | 3.0 (2.3–3.4) | 3.1 (2.5–3.5) | 2.8 (1.8–3.3) | 0.02 |
| PAPi | 2 (2) | 1.5 (0.9–1.9) | 1.5 (1.0–2.0) | 1.3 (0.8–1.9) | 0.50 |
| CPOi (W/m2) | 2 (2) | 0.5 (0.4–0.5) | 0.5 (0.4–0.5) | 0.4 (0.3–0.5) | 0.02 |
| SvO2 (%) | 8 (7) | 72 (67–79) | 73 (68–78) | 70 (62–79) | 0.15 |
| Lactate (mMol/L) | 0 (0) | 4.9 (3.2–7.1) | 4.1 (2.8–5.7) | 5.6 (4.1–8.5) | 0.01 |
| Hb (g/L) | 0 (0) | 105 (94–115) | 105 (97–117) | 102 (93–112) | 0.25 |
| TTE findings first 48 h | |||||
| LV dysfunction any | 12 (11) | 27 (26) | 11 (17) | 16 (40) | 0.01 |
| LV dysfunction mod–severe | 12 (11) | 16 (16) | 6 (10) | 10 (25) | 0.03 |
| RV dysfunction any | 12 (11) | 45 (43) | 22 (34) | 23 (58) | 0.02 |
| RV dysfunction mod–severe | 12 (11) | 25 (24) | 9 (14) | 16 (40) | 0.003 |
| Mod-to-severe graft dysfunctiona | 12 (11) | 29 (28) | 11 (17) | 18 (45) | 0.002 |
| Hemodynamics first 48 h: ICU | |||||
| Lowest MAP | 0 (0) | 59 (54–62) | 60 (58–62) | 56 (51–60) | 0.0003 |
| Highest CVP | 0 (0) | 22 (19–27) | 23 (19–25) | 22 (19–29) | 0.97 |
| Highest mPAP | 2 (2) | 32 (29–35) | 32 (29–35) | 31 (29–35) | 0.43 |
| Lowest CI | 2 (2) | 2.0 (1.8–2.3) | 2.1 (1.8–2.3) | 1.9 (1.6–2.2) | 0.10 |
| Lowest SvO2 | 5 (5) | 54 (49–60) | 54 (49–60) | 54 (48–60) | 0.82 |
| Peak lactate | 0 (0) | 7.0 (5.6–9.8) | 6.5 (5.1–8.6) | 8.0 (6.7–10.8) | 0.004 |
| Time to lactate <3 (hrs) | 0 (0) | 14 (11–18) | 14 (10–17) | 16 (11–20) | 0.14 |
| Maximal vasoactive dose 48 h | |||||
| Milrinone (µg/kg/min) | 0 (0) | 0.25 (0.20–0.35) | 0.25 (0.19–0.34) | 0.26 (0.20–0.37) | 0.45 |
| Dobutamine (µg/kg/min) | 0 (0) | 0 (0–2.51) | 0 (0–3.27) | 0 (0–0) | 0.12 |
| Adrenaline (µg/kg/min) | 0 (0) | 0.06 (0.05–0.09) | 0.05 (0.04–0.07) | 0.08 (0.06–0.11) | 0.0006 |
| Noradrenaline (µg/kg/min) | 0 (0) | 0.22 (0.14–0.33) | 0.19 (0.14–0.24) | 0.30 (0.21–0.44) | 0.0002 |
| Vasopressin (unit/kg /h) | 0 (0) | 0.02 (0–0.03) | 0 (0–0.03) | 0.03 (0.00–0.03) | <0.0001 |
| VIS | 0 (0) | 31.7 (21.3–44.3) | 28.2 (19.7–34.6) | 41.7 (31.1–60.8) | <0.0001 |
| IS | 0 (0) | 31.1 (21.2–41.2) | 28.3 (20.7–33.9) | 38.8 (30.2–58.4) | <0.0001 |
| Mechanical Circulatory Support | |||||
| VA-ECMO or IABP use in 48 h | 0 (0) | 11 (10) | 0 (0) | 11 (26) | <0.0001 |
| Transfusions first 48 h | |||||
| Lowest Hb | 0 (0) | 79 (74–87) | 80 (75–90) | 76 (72–81) | 0.03 |
| RBC transfusion | 0 (0) | 0 (0–1) | 0 (0–0) | 1 (0–2) | <0.0001 |
| Fresh frozen Plasma transfusion | 0 (0) | 0 (0–0) | 0 (0–0) | 0 (0–0) | 0.002 |
| Cryoprecipitate transfusion | 0 (0) | 0 (0–0) | 0 (0–0) | 0 (0–0) | 0.001 |
| Platelet transfusion | 0 (0) | 0 (0–0) | 0 (0–0) | 0 (0–0) | 0.06 |
Values are expressed as median (interquartile range) or n (%).
aPrimary Graft Dysfunction defined by Kobashigawa et al.33
CI, cardiac index; CPOi, cardiac power output index; CVP, central venous pressure; Hb, hemoglobin; IABP, intra-aortic balloon pump; IS, Inotrope Score; MAP, mean arterial pressure; PAPi, pulmonary artery pulsatility index; SvO2, mixed venous oxygen saturation; VA-ECMO, veno-arterial extra corporeal membrane oxygenation; VIS, Vasoactive Inotrope Score.
A Bonferroni correction was applied to the comparison of 66 parameters, setting a significant P value of <0.0008. With this correction, in the first 48 h of ICU, the severe AKI group had significantly higher doses of noradrenaline, adrenaline and vasopressin, higher red blood cell transfusion, and lower MAP.
RRT was required in 37 patients in the first 7 d (34% of all patients, 88% of the severe AKI group). By hospital discharge, 2 of the 67 stage 0–2 AKI survivors and 7 of the 35 severe AKI survivors were dialysis dependent. Twenty-two percent of survivors in the severe AKI group were dialysis dependent at 90-d posttransplantation. Overall hospital mortality was 6.4%, 0% in the stage 0–2 AKI and 17% in the severe AKI group. Ninety-day mortality was 5% overall, 0% in the stage 0–2 AKI, and 12% in the severe AKI group. Twelve-month mortality was 8% overall, 1% in the stage 0–2 AKI group, and 22% in the severe AKI group. Median ICU length of stay, hospital length of stay, and median mechanical ventilation time were longer in the severe AKI group (Table 4).
TABLE 4.
Patient outcomes
| Characteristic | Missing data | KDIGO stage | P Value | ||
|---|---|---|---|---|---|
| All patients | 0–2 | 3 | KDIGO stage | ||
| (n = 109) | (n = 67) | (n = 42) | 3 vs 0–2 | ||
| Renal Outcomes | |||||
| RRT use first 48 h | 0 (0) | 28 (26) | 0 (0) | 28 (67) | |
| RRT in ICU | 0 (0) | 36 (33) | 0 (0) | 36 (86) | |
| RRT in first 7 d | 0 (0) | 37 (34) | 0 (0) | 37 (88) | |
| Dialysis at ICU d/c alive | 0 (0) | 28 (26) | 0 (0) | 28 (72) | |
| Dialysis >28 d alive | 0 (0) | 17 (16) | 2 (3) | 17 (44) | |
| Dialysis >90-d alive | 0 (0) | 8 (7) | 1 (1) | 8 (22) | |
| Dialysis at Hosp d/c alive | 0 (0) | 7 (6) | 2 (3) | 7 (20) | |
| Other Secondary Outcomes | |||||
| Ventilation (h) | 0 (0) | 36 (18–114) | 21 (16–37) | 135 (62–323) | <0.0001 |
| ICU length of stay (h) | 0 (0) | 116 (77–217) | 90 (68–120) | 234 (148–482) | <0.0001 |
| Hospital length of stay (d) | 0 (0) | 27 (16–47) | 20 (14–35) | 43 (26–96) | <0.0001 |
| ICU mortality | 0 (0) | 3 (3) | 0 (0) | 3 (7) | 0.05 |
| 90-d mortality | 0 (0) | 5 (5) | 0 (0) | 5 (12) | 0.01 |
| Hospital mortality | 0 (0) | 7 (6) | 0 (0) | 7 (17) | 0.001 |
| 12-mo mortality | 0 (0) | 9 (8) | 1 (1) | 8 (19) | 0.01 |
Values are expressed as median (interquartile range) or n (%).
D/C, discharge; RRT, renal replacement therapy.
eGFR, noradrenaline dose, and the need for mechanical circulatory support were all independently associated with the risk of developing severe AKI in a multiple regression analysis (Table 5).
TABLE 5.
Multivariable logistic regression analysis
| Factor | OR | 95% CI | P |
|---|---|---|---|
| Preoperative eGFR (per 10 mL/min/1.73m2) | 0.72 | 0. 55–0.93 | 0.01 |
| Red Blood Cell transfusion ICU (per unit) | 1.53 | 0. 80–2.87 | 0.16 |
| Noradrenaline dose (per 0.1mcg/kg/min) | 1.55 | 1. 16–2.16 | 0.002 |
| Mechanical circulatory Support | 27.74 | 2. 30–4119.3 | 0.01 |
eGFR, estimated glomerular filtration rate.
DISCUSSION
Severe AKI in the first-week postprocedure was common in heart transplant recipients in our center. We found a complex interplay between several factors, where an at-risk population has a homeostatic disturbance during transplantation, which results in a phenotype of either graft dysfunction, significant vasoplegia, or a combination of both, leading to the development of severe AKI. Among numerous risk factors preoperative eGFR, noradrenaline dose, and the need for mechanical circulatory support were independently associated with its development. Early severe AKI was associated with an increased rate of hospital death, dialysis dependence at time of hospital discharge, and increased ventilation duration, ICU, and hospital length of stay.
To define AKI in our study, we used the KDIGO criteria,30 which was created to standardize and unify AKIN and RIFLE definitions with the advantage of improving the sensitivity of both.39 Studies which report on AKI following heart transplantation adopt variably either RIFLE,6,27,28,40 AKIN,10,41,42 or KDIGO3,4,7,8,11,12,15,16,21–24 criteria with the latter showing the highest sensitivity.26 We did not find a difference in the classification rate for severe AKI between the KDIGO and the RIFLE criteria.
Reported rates of AKI postcardiac transplantation vary between 14%6 and 83%4 with rates of severe AKI between 6%6,24 and 46%3,16 in the recent literature. At a rate of 78% for AKI and 39% for severe AKI, our study had quite high incidences. RRT was commenced within 1 wk of transplantation in 35% of our cohort putting it at the higher end of the spectrum along with numerous other studies.3,11,16,27,28 The significant heterogeneity in AKI rates that exists between studies has a number of possible explanations including variations in study sample sizes, adoption of different definitions, timepoints used for the assessment of renal function, recipient selection criteria, indications for initiating RRT, and the highly variable process of heart transplantation itself (donor selection, retrieval processes, surgical factors, immunosuppression regimes, and postoperative practices).
Regarding the timing of AKI, 28 patients (67% of all stage 3 AKI) were on RRT within 48 h. One RRT patient in the stage 3 AKI group had creatinine rise above the threshold of 354.6 µMol/L within 48 h (this patient never received RRT). Thus, 29 patients out of 42 (69%) were diagnosed with severe AKI within 48 h. Twenty-four (83%) of the stage 3 AKI patients had a urine output of <0. 3 mL/kg/h for >24 h. Therefore, severe AKI occurred commonly early and was most often associated with persistent oliguria resulting in the need for RRT.
In our cohort, older age was associated with the development of severe AKI, which was also found by others.10,11,17,20,23,28 With regards to our population, the median age of our transplant recipients was 58 y, this is older than the average recipient age of 55 y from international registry data,43 which may have contributed to the our overall high incidence of kidney injury in our study population.
We found an association between BMI and the development of severe AKI. Obesity has consistently been associated with the development of AKI following cardiac surgery in general44–46 and specifically after heart transplantation surgery.3,7,9,12,14,17
Similar to other studies, severe AKI was associated with both operation time and CPB time.3,5,8,15,16,27 Mechanisms explaining the association between CPB time and AKI and include perioperative renal ischemia-reperfusion injury, hemolysis and pigment nephropathy, oxidative stress, and systemic inflammation associated with CPB.47–49 Interestingly, in contrast to the finding of some studies,13,18,19 we did not find an association between LVAD explant and the development of severe AKI in our cohort, which had a mean LVAD duration of 9.3 mo SD 7.0 mo.
We did not find an association between donation after circulatory death (DCD) and development of severe AKI. Previous studies from our institution have reported rates of delayed graft function and need for mechanical circulatory support in the DCD population in the range of 22% to 35%,50,51 which we anticipated would lead to a significant association with the development of severe AKI. All of our DCD heart transplants were preserved with Transmedics OCS. Out of the 36 DCD donor heart recipients in our study, only 2 (6%) patients went on to require VA-ECMO and 1 (3%) patient required IABP in the postoperative period perhaps demonstrating improvements in organ retrieval, management of ischemia-reperfusion, and optimization of ex situ cardiac perfusion.
Our cohort had a very low rate of postoperative bleeding with only 3 patients requiring emergency return to theater for bleeding and a very low number of total transfusions being given. The severe AKI group received 78% of the 80 units of packed red blood cells, 87% of the 31 units of fresh frozen plasma, 95% of the 41 units of cryoprecipitate, and 77% of the 13 units of platelets. Most of these blood products were administered to a small number of patients in the severe AKI group. Others have found an association between transfusion and AKI postheart transplantation.3,9,27 Karkouti summarizes a large number of observational studies investigating the association of blood transfusion with AKI in cardiac surgery patients and summates that each unit of blood transfusion is independently associated with a 10% to 20% risk of AKI.52
We found preoperative eGFR to be an independent risk factor for the development of severe AKI, this has been frequently shown by others.2,5,7,12,13,17–19,22,23,26 Our results highlight the importance of routine examination of preoperative renal function and incorporating these results into risk stratification models to aid the selection process, communicating risks to patients and to implement protective strategies in the perioperative period. From our receiver operator characteristic curve, we found that an eGFR of 55 mL/min/1.73m2 had a 55% sensitivity and 75% specificity for the development of severe AKI (Figure S1, SDC, http://links.lww.com/TXD/A617).
The dose of noradrenaline as well as that of vasopressin and adrenaline in the early postoperative phase was associated with the later development of severe AKI. We did not find any other studies independently associating noradrenaline dose with the development of AKI; however, there have previously been association found between adrenaline and AKI postheart transplantation.3 Similarly, the Vasopressor Inotrope Score score has previously been shown to be an independent risk factor for the development of AKI.16,25 The dosage of noradrenaline likely reflects the severity of vasoplegia, which is a commonly encountered complication for patients who have undergone heart transplantation.53 From our receiver operator characteristic curve, we found a cutoff of 0.25 µg/kg/min had a 64% sensitivity and 78% specificity for the development of severe AKI (Figure S2, SDC, http://links.lww.com/TXD/A617).
AKI is very common in patients on mechanical circulatory support.54 Consistent with this, we found that mechanical circulatory support in the first 48-h postheart transplantation was independently associated with the development of severe AKI, which has be reported by others.9,21 All patients in our study who required mechanical circulatory support developed severe AKI and more than half of the severe AKI group had moderate-to-severe graft dysfunction or required mechanical support.
The high odds ratio and extreme confidence intervals for mechanical circulatory support in our multivariable analysis, due to it exhibiting complete separation,37 has the potential to confound the results of our model. For this reason, we conducted a sensitivity analysis by fitting a logistic regression model excluding the MCS variable. The area under the curve of model predictions exhibited a small decrease, which is anticipated upon the removal of a covariate from a model (Figures S1 and S2, SDC, http://links.lww.com/TXD/A617). Notably, the RBC variable emerged as significant in the absence of MCS (Table S2, SDC, http://links.lww.com/TXD/A617), which could be attributed to a confounding association with the MCS variable. The other variables in the model without MCS have similar values to the full model.
Patients with severe AKI in our study had a mortality rate similar or lower to that reported by a number of other studies.3,6,7,9,12,13,15–17,23,27 The association of severe AKI and mortality highlights the significance of developing this complication. Mechanical ventilation duration was 6 times longer in the severe AKI group reflecting the complexity of this patient group and possibly also the interactions between renal impairment and respiratory function. Increased ICU length of stay and time of mechanical ventilation highlight the resource implications of patients who develop severe AKI.
It is acknowledged that there are several limitations to our study. Being a single-center study, the clinical management of patients in our institution may vary to that of other centers, limiting generalizability. We collected data on risk factors during the first 48 h, it is acknowledged that other factors between 48 h and 7 d may also contribute to the development of severe AKI, in particular calcineurin inhibitor levels, which may reach supratherapeutic levels by this time point (a recognized risk for AKI development). The study is retrospective and as such susceptible to missing data, the quantity of missing data is outline in Tables 1 to 4, the multivariable logistic regression did not include variables with missing data. The small total number of patients limited the number of independent variables for building a multivariable model. The authors of this study did not have access to donor medical records, which limited exploring the impact of donor factors on the development of severe AKI. Finally, for our data collection, we recorded if a patient required RRT; however, the indication for the commencement was often not recorded, it is possible that different indications for commencing RRT are associated with disparate outcomes.
In conclusion, this retrospective single-center study found that severe AKI is very common in heart transplant recipients. Severe AKI has significant implications on patient centered outcomes, in particular, an increased hospital mortality and dependence on dialysis at the time of hospital discharge. Preoperative kidney function, postoperative vasoplegia with high requirements for vasoactive drugs and graft dysfunction with the need for mechanical circulatory supports were independently associated with the development of acute severe AKI in the first-week following orthotopic heart transplantation.
ACKNOWLEDGMENTS
We wish to thank the following people:
-Sandra Lopez Yern for assistance with data collection for this study.
-Coralie Williams, Stats Central (University New South Wales), for assistance with statistical calculations.
Supplementary Material
Footnotes
D.G. did study design, data collection and analysis, and writing of the article. S.A.-S. participated in study design, data collection and analysis, and writing of the article. P.M.D. did writing of the article. P.N. participated in study design and writing of the article.
D.G. and S.A.-S. have contributed equally as first authors.
P.M.D. received reports peer-reviewed research funding from NHMRC and NSW Health. He reports industry supported research funding to his institution from Amgen and Novartis and consultancy fees paid to him from AstraZeneca, Boehringer-Ingelheim, and Novartis. The other authors declare no conflicts of interest.
Supplemental digital content (SDC) is available for this article. Direct URL citations appear in the printed text, and links to the digital files are provided in the HTML text of this article on the journal’s Web site (www.transplantationdirect.com).
Contributor Information
Suhel Al-Soufi, Email: Suhel.Al-Soufi@svha.org.au.
Peter MacDonald, Email: peter.macdonald@svha.org.au.
REFERENCES
- 1.Chambers D, Zuckermann A, Cherikh W, et al. The International Thoracic Organ Transplant Registry of the International Society for heart and lung transplantation: 37th adult heart transplantation report-2020; focus on deceased donor characteristics. 2020. [DOI] [PMC free article] [PubMed]
- 2.Alba A, Bain E, Ng N, et al. Complications after heart transplantation: hope for the best, but prepare for the worst. Int J Transplant Res Med. 2016;2:22 [Google Scholar]
- 3.Aliyev A, Ayhan A, Zeyneloglu P, et al. HLA sensitization in end-stage heart failure patients supported by extracorporeal membrane oxygenation. Transplantation. 2018;102:S63. [Google Scholar]
- 4.Bianco J, Strang M, Denault A, et al. Acute kidney injury after heart transplant: the importance of pulmonary hypertension. J. Cardiothorac Vasc Anesthesia. 2021;35:2052–2062. [DOI] [PubMed] [Google Scholar]
- 5.Boyle J, Moualla S, Arrigain S, et al. Risks and outcomes of acute kidney injury requiring dialysis after cardiac transplantation. Am J Kidney Dis. 2006;48:787–796. [DOI] [PubMed] [Google Scholar]
- 6.De Santo L, Romano G, Amarelli C, et al. Implications of acute kidney injury after heart transplantation: what a surgeon should know. Eur J Cardiothorac Surg. 2011;40:1355. [DOI] [PubMed] [Google Scholar]
- 7.Fortrie G, Manintveld O, Caliskan K, et al. Acute kidney injury as a complication of cardiac transplantation: Incidence, risk factors, and impact on 1-year mortality and renal function. Transplantation. 2016;100:1740–1749. [DOI] [PubMed] [Google Scholar]
- 8.García-Gigorro R, Renes-Carreño E, Peiretti M, et al. Incidence, risk factors and outcomes of early acute kidney injury after heart transplantation: an 18-year experience. Transplantation. 2018;102:1901–1908. [DOI] [PubMed] [Google Scholar]
- 9.Gašparović H, Svetine L, Lončarić F, et al. Preponderance of microbial isolates among heart transplantation recipients requiring renal replacement therapy: a propensity score adjusted analysis. Croat Med J. 2018;59:224–231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Gude E, Andreassen A, Arora S, et al. Acute renal failure early after heart transplantation: risk factors and clinical consequences. Clin Transplant. 2010;24:E207–E213. [DOI] [PubMed] [Google Scholar]
- 11.Gültekin B, Beyazpinar D, Ersoy O, et al. Incidence and outcomes of acute kidney injury after orthotopic cardiac transplant: a population-based cohort. Exp Clin Transplant. 2015;13:26–29. [DOI] [PubMed] [Google Scholar]
- 12.Guven G, Brankovic M, Constantinescu A, et al. Preoperative right heart hemodynamics predict postoperative acute kidney injury after heart transplantation. Intensive Care Med. 2018;44:588–597. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Ivey-Miranda J, Flores-Umanzor E, Farrero-Torres M, et al. Predictors of renal replacement therapy after heart transplantation and its impact on long-term survival. Clin Transplant. 2018;32:e13401. [DOI] [PubMed] [Google Scholar]
- 14.Jahangirifard A, Ahmadi Z, Khalili N, et al. Early post-operative acute kidney injury after cardiac transplantation: incidence and predictive factors. Clin Transplant. 2021;35:11. [DOI] [PubMed] [Google Scholar]
- 15.Jiang Y, Kong X, Xue F, et al. Incidence, risk factors and clinical outcomes of acute kidney injury after heart transplantation: a retrospective single centre study. J Cardiothorac Surg. 2020;15:302. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Jocher B, Schilling J, Fischer I, et al. Acute kidney injury post-heart transplant: an analysis of perioperative risk factors. Clin Transplant. 2021;35:e14296. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Kilic A, Grim J, Shah A, et al. An easily calculable and highly predictive risk index for postoperative renal failure after heart transplantation. J Thorac Cardiovasc Surg. 2014;148:1099. [DOI] [PubMed] [Google Scholar]
- 18.Kim D, Choi J, Cho Y, et al. Impact of preoperative renal replacement therapy on the clinical outcome of heart transplant patients. Sci Rep. 2021;11:13398. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Kolsrud O, Karason K, Holmber E, et al. Renal function and outcome after heart transplantation. J Thorac Cardiovasc Surg. 2018;155:1593–1604.e1. [DOI] [PubMed] [Google Scholar]
- 20.Nadkarni G, Chauhan K, Patel A, et al. Temporal trends of dialysis requiring acute kidney injury after orthotopic cardiac and liver transplant hospitalizations. BMC Nephrol. 2017;18:244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Nicoara A, Kretzer A, Cooter M, et al. Association between primary graft dysfunction and acute kidney injury after orthotopic heart transplantation – a retrospective, observational cohort study. Transpl Int. 2020;33:887–894. [DOI] [PubMed] [Google Scholar]
- 22.Roest S, Hesselink D, Klimczak-Tomaniak D, et al. Incidence of end-stage renal disease after heart transplantation and effect of its treatment on survival. ESC Heart Failure 2020;7:533–541. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Romeo F, Varelab C, Vulcanaoa N, et al. Acute kidney injury after cardiac transplantation: Foe or common innocent bystander? Transplant Proc. 2018;50:1489–1495. [DOI] [PubMed] [Google Scholar]
- 24.Sikma M, Hunault C, Kirkels J, et al. Association of whole blood tacrolimus concentrations with kidney injury in heart transplantation patients. Eur J Drug Metab Pharmacokinet. 2018;43:311–320. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Tadros H, Lopez-Colon D, Bleiweis M, et al. Postoperative vasoactive inotropic score is predictive of outcomes in pediatric heart transplantation. Clin Transplant. 2020;34:e13986. [DOI] [PubMed] [Google Scholar]
- 26.Thongprayoon C, Lertjitbanjong P, Hansrivijit P, et al. Acute kidney injury in patients undergoing cardiac transplantation: a meta-analysis. Medicines. 2019;6:108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Tjahjono R, Connellan M, Granger E. Predictors of acute kidney injury in cardiac transplantation. Transplant Proc. 2016;48:167–172. [DOI] [PubMed] [Google Scholar]
- 28.Türker M, Zeyneloglu P, Sezgin A, Pirat A, Arslan G. RIFLE criteria for acute kidney dysfunction following heart transplantation: incidence and risk factors. Transplant Proc. 2013;45:3534–3537. [DOI] [PubMed] [Google Scholar]
- 29.Wang T, Lin C, Wei H, Wu M. Long-term outcomes and risk factors of renal failure requiring dialysis after heart transplantation: A nationwide cohort study. J Clini Med. 2020;9:2455. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Kellum J, Lameire N, Aspelin P, et al. Kidney disease: improving global outcomes (KDIGO) acute kidney injury work group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int Suppl. 2012;2:1–138. [Google Scholar]
- 31.Bellomo R, Kellum J, Ronco C. Defining and classifying acute renal failure: from advocacy to consensus and validation of the RIFLE criteria. Intensive Care Med. 2007;33:409–413. [DOI] [PubMed] [Google Scholar]
- 32.Levey A, Stevens L, Schmid C, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604–612. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Kobashigawa J, Zuckermann A, Macdonald P, et al. Report from a consensus conference on primary graft dysfunction after cardiac transplantation. J Heart Lung Transplant. 2014;33:327–340 [DOI] [PubMed] [Google Scholar]
- 34.Gaies M, Gurney J, Yen A, et al. Vasoactive-inotropic score as a predictor of morbidity and mortality in infants after cardiopulmonary bypass. Pediatr Crit Care Med. 2010;11:234–238. [DOI] [PubMed] [Google Scholar]
- 35.Dunn P, Smyth G. Randomized quantile residuals. J Comput Graphic Statist. 1996;5:236–244. [Google Scholar]
- 36.Heinze G, Schemper M. A solution to the problem of separation in logistic regression. Stat Med. 2002;21:2409–2419. [DOI] [PubMed] [Google Scholar]
- 37.Mansournia M, Geroldinger A, Greenland S, et al. Separation in logistic regression: causes, consequences, and control. Am J Epidemiol. 2018;187:864–870. [DOI] [PubMed] [Google Scholar]
- 38.Holm A, Fedson S, Courwright A, et al. International society for heart and lung transplantation statement on transplant ethics. J Heart Lung Transplant. 2022;41:1307–1308. [DOI] [PubMed] [Google Scholar]
- 39.Bagshaw S, George C, Bellom R. ANZICS database management committee. A comparison of the RIFLE and AKIN criteria for acute kidney injury in critically ill patients. Nephrol Dial Transplant. 2008;23:1569–1574. [DOI] [PubMed] [Google Scholar]
- 40.Crudele V, Cacciatore F, Grimaldi V, et al. Human leukocyte antigen-DR mismatch is associated with increased in-hospital mortality after a heart transplant. Exp Clin Transplant. 2013;11:346–351. [DOI] [PubMed] [Google Scholar]
- 41.Giglio Canelhas de Abreu L, Proença Vieira L, Gomes T, et al. Clinical and nutritional factors associated with early mortality after heart transplantation. Transplant Proc. 2017;49:874–877. [DOI] [PubMed] [Google Scholar]
- 42.Jahangirifard A, Ahmadi Z, Naghashzadeh F, et al. Prophylactic fibrinogen decreases postoperative bleeding but not acute kidney injury in patients undergoing heart transplantation. Clin Appl Thromb Hemost. 2018;24:998–1004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Khush K, Cherikh W, Chambers D, et al. The International Thoracic Organ Transplant Registry of the International Society for Heart and Lung Transplantation: thirty-sixth adult heart transplantation report—2019; focus theme: donor and recipient size match. J Heart Lung Transplant. 2019;38:1056–1066. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Shi N, Liu K, Fan Y, et al. The association between obesity and risk of acute kidney injury after cardiac surgery. Front Endocrinol. 2020;11:534294. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Wigfield C, Lindsey J, Muñoz A, et al. Is extreme obesity a risk factor for cardiac surgery? An analysis of patients with a BMI > or = 40. Eur J Cardiothorac Surg. 2006;29:434–440. [DOI] [PubMed] [Google Scholar]
- 46.Zou Z, Zhuang Y, Liu L, et al. Role of body mass index in acute kidney injury patients after cardiac surgery. Cardiorenal Med. 2018;8:9–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Andersson L, Bratteby L, Ekroth R, et al. Renal function during cardiopulmonary bypass: influence of pump flow and systemic blood pressure. Eur J Cardiothorac Surg. 1994;8:597–602. [DOI] [PubMed] [Google Scholar]
- 48.Mamikonian L, Mamo L, Smith B, et al. Cardiopulmonary bypass is associated with hemolysis and acute kidney injury in neonates, infants, and children. Pediatr Crit Care Med. 2014;15:e111–e119. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.O’Neal J, Shaw A, Billings F. Acute kidney injury following cardiac surgery: current understanding and future directions. Critical Care. 2016;20:187. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Chew H, Iyer A, Connellan M, et al. Outcomes of donation after circulatory death heart transplantation in Australia. J Am Coll Cardiol. 2019;73:1447–1459. [DOI] [PubMed] [Google Scholar]
- 51.Dhital K, Ludhani P, Scheuer S, et al. DCD donations and outcomes of heart transplantation: the Australian experience. Indian J Thorac Cardiovascu Surg. 2020;36:224–232. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Karkouti K. Transfusion and risk of acute kidney injury in cardiac surgery. Br J Anaesth. 2012;109:i29–i38. [DOI] [PubMed] [Google Scholar]
- 53.Parikh A, Anyanwu A, Mancini D. Vasodilatory shock after heart transplantation: the enigma continues. J Card Fail. 2022;28:627–629. [DOI] [PubMed] [Google Scholar]
- 54.Thongprayoon C, Cheungpasitporn W, Lertjitbanjong P, et al. Incidence and impact of acute kidney injury in patients receiving extracorporeal membrane oxygenation: a meta-analysis. J Clini Med. 2019;8:981. [DOI] [PMC free article] [PubMed] [Google Scholar]