Printer Friendly

Never events and hospital-acquired conditions after kidney transplant.

Introduction

The quality and safety of patient care in hospitals are important aims of National Quality Forum (NQF) in the U.S. (1,2) As adverse, serious events that are largely preventable, never events (NE) and hospital-acquired conditions (HAC) are reliable measurements of the quality and safety of patient care. (1,2) NEs and HACs also have a significant financial impact on the U.S. healthcare system. (3) It has been estimated that payments for surgical NE amounted to over $1.3 billion from 1990-2010. (4) Eliminating surgical NEs is necessary to limit harm to patients. (4) Understanding the impact and frequency of these conditions can help to design the best preventative strategies.

NE was defined in 2006 by NQF, which includes 28 reportable events in healthcare. (2) The list includes obvious unacceptable errors; however, not all the events are indicative of obvious negligence. (2) A goal of quality improvement is the reduction of NEs to zero. In this line, Centres for Medicare and Medicaid Services (CMS) adopted the non-reimbursement policy for some of the events with the name of "non-reimbursable serious hospital-acquired conditions" in order to motivate hospitals to accelerate improvement of patient safety. (2) Investigating patient characteristics and operative factors with the events may help improve current prevention strategies. Using a nationwide database, this study aims to investigate predictors and outcomes of NE and HAC after kidney transplantation using appropriate events for the kidney transplant procedure according to both NQF and CMS lists.

Methods

An analysis of the Nationwide Inpatient Sample (NIS) database from 2002-2012 was used in this study. NIS is an inpatient care database according to hospital discharge data in the U.S. acquired by the Healthcare Cost and Utilization Project (HCUP) of the Agency for Healthcare Research and Quality, Rockville, MD. It is an annually compiled database that consists of approximately 8 million inpatient stays from approximately 1000 hospitals each year. (5) Informed consent is obtained from individual patients within the individual hospitals' patient consent forms. For the purposes of this study, NIS was queried using the Ninth Revision of the International Classification of Disease (ICD-9-CM) procedure code of 55.69 to identify kidney transplantation cases. ICD-9 diagnosis codes, which were reported in principal diagnosis of patients, were also used to identify relevant diagnoses of patients. This study investigated NEs and HACs after kidney transplantation using the ICD-9 diagnosis codes, which were reported as the second to 25th diagnosis of patients in the database. Details of the codes used to identify NE and HAC are reported in Table 1. The definition of complications (NE and HAC) were made according to ICD-9 diagnosis codes, which is available online. (6)

Patient variables include demographic data (age, sex, and race), patient diagnosis, comorbidities (hypertension, coagulopathy, and diabetes mellitus), hospitalization length, total hospital charges, and admission type (elective vs. nonelective). Patient loss of function before surgery and risk of mortality (mild, moderate, major, and extreme) were according to the classification of the NIS database. (5) The primary endpoints were rates of NE and HAC after kidney transplantation. Secondary endpoints were predictors and outcomes of NE and HAC after kidney transplantation. Risk adjusted analysis was performed to investigate predictors and outcomes of NE and HAC.

Statistical analysis

Data was analyzed using the Statistical Package for Social Sciences (SPSS) software, Version 22 (SPSS Inc., Chicago, IL, U.S.). The main analysis was multivariate analysis using logistic regression. The associations of NE and HAC with mortality and morbidity of patients were examined using a multivariable logistic regression model. We included all the variables of the study as covariates in the model. The estimated adjusted odds ratio (AOR) with a 95% confidence interval (CI) was calculated for each correlation. Statistical hypotheses were tested using p<0.05 as the level of statistical significance.

Results

We sampled 35 058 patients who underwent kidney transplant from 2002-2012 accordng to the NIS database. Of these, 60.2% were male. The median age of patient was 50 years. Also, the majority of patients were Caucasian (53.8%). Deficiency anemia (41.2%) and fluid and electrolyte disorders (31.8%) were the most common reported comorbid conditions of patients. The median hospitalization length of patients was six days. The most common reported reasons of renal failure and need for kidney transplant were hypertension (42%) and diabetes (34.7%). Demographics and clinical characteristics of patients are shown in Table 2.

Among patients who underwent kidney transplant, 11 (0.03%) had NEs and all of the events were due to retained foreign bodies. Overall, 138 patients had postoperative HAC, of which falling was the most common event (44.9%), followed by poor glycemic control (21.7%), vascular catheter-associated infection (21%), catheter-associated urinary tract infection (8%), stages III and IV pressure ulcers (2.9%), and ABO incompatible blood transfusion (2.2%) (Fig. 1).

The mortality and morbidity of patients who underwent kidney transplantation were 0.5% and 24.3%, respectively. Patients with HAC or NE had significantly higher mortality (1.4% vs. 0.5%; p=0.04) and morbidity (45.6% vs. 24.2%; p<0.01). HAC and NE after surgery were significantly associated with an increased mean length of stay (13 vs. 7 days; p<0.01) and hospital charges of patients ($231 801 vs. $146 717; p<0.01). Also, patients with NE or HAC had a higher risk of unplanned reoperation (AOR 1.92; p=0.04), prolonged ileus (AOR 2.28; p<0.01), pneumonia (AOR 3.31; p<0.01), acute myocardial infarction (AOR 2.72; p<0.01), and respiratory failure (AOR 3.69; p<0.01) (Table 3).

Risk adjusted analysis of factors associated with postoperative NE and HAC are reported in Table 4. A significantly higher risk of HAC or NE events was seen for patients who had a severe disease before surgery (AOR 3.25; p<0.01) and patients who were expected to have more loss of function before surgey (AOR 1.62; p=0.03). When investigating patients who had catheter-related urinary tract infection, factors such as age (AOR 0.96; CI 0.92-0.99; p=0.04), female gender (AOR 15.48; CI 1.92-124.41; p=0.01), and severity of loss of function before surgey (AOR 9.70; CI 1.01 -94.88; p=0.04) were significantly associated with catheter-related urinary tract infection. Also, severity of loss of function before surgey was significantly associated with falling (AOR 3.14; CI 1.48-6.67; p<0.01), retained foreign body (AOR 7.58; CI 1.24-46.28; p=0.02), and vascular catheter-associated infection (AOR 6.82; CI 1.22-38.05; p=0.02). Poor glycemic control was significantly associated with patient's age (AOR 0.94; CI 0.91-0.98; p<0.01).

Discussion

This study found a significant increase in mortality, morbidity, hospitalization length, and total hospital charges of patients with NEs and HACs after kidney transplant. Also, the risks of other postoperative complications, such as prolonged ileus, pneumonia, acute myocardial infarction, and respiratory failure, increase in presense of NE and HAC. We reinforce the literatures reports on the severity effect of NE and HAC events on patient outcomes, as well as the significant increase in total hospital charges related to the events. (7-9) Our study results show the severity of loss of function before surgey is a reliable factor to find patients at high risk for postoperative NE and HAC (Table 4). We found the risk of NE and HAC for patients with major or extreme loss of function before surgey is more than three times that of patients with minor or moderate loss of function before surgery. Patient characteristics have been reported as important predictors of the occurrence of a NE in the literature. (10) Although preventive sterategies should be done for all surgical patients, some high-risk patients may benefit from frequent assessments to decrease the risk of NE during hospitalization. For example, creating a mandatory checklist that should be filled out frequently during hospitalization by the responsible surgeon may be useful in high-risk patients. (2)

We found a significant association between catheter-related urinary tract infection and age, female gender, and severity of loss of function before surgey, which is in line with literaure reports; (11,12) however, we could not evaluate correlation between urinary stent and length of using urinary catheter and urinay tract infection. It is estimated that up to 69% of catheter-related urinary tract infection can be prevented using appropriate infection prevention strategies, such as the removal of the catheter as soon as possible or avoidance of its use. (12-14) Considering 38% of physicians were not aware of the status of urinary catheter use for their patients, (12,15) reminder systems, including face-to-face reminders involving staff nurses and virtual reminders involving the use of electronic devices, may help decrease the risk of catheter-related urinary tract infection. (12)

Our study results show falling is the most common preventable HAC in kidney transplant patients. The overall reported rate of fall after general surgery procedures is 1.6% in literature; (16) we found a rate of 0.2% postoperative falls for kidney transplant patients--lower than for general surgeries. Although a fall seems like a simple event, in the literature it represents a failure of multiple physiological systems and also a marker for increased perioperative mortality and morbidity and postoperative delirium. (16-19) Recognition of fall risk factors and identifying high-risk patients for fall will help design postoperative fall prevention programs. Factors like older age, functional dependence, and lower albumin levels have been reported to be associated with falls. (16) We also found a higher risk of fall for patients who had more loss of function before surgey. Interestingly, 66% of patients who fell had diabetes as a result of kiney failure. Diabetes with peripheral neuropathy can increase chance of fall after surgery. Minimizing polypharmacy and avoiding individual medications that increase the risk of delirium, increasing the presence of family members or sitters at the bedside, minimizing environmental hazards, and occupational and physical therapy training in high-risk patients, especialy in diabetetic patients with peripheral neuropathy, may decrease the risk of fall in high-risk patients.

We found vascular catheter-associated infection as the third most common HAC after kidney transplant. It has been estimated that there are 15 million central vascular catheter days for patients hospitalized at intensive care units each year in the U.S. (20,21) There are multiple studies that addressed catheter-related bloodstream infections in literature. (20,21) Factors such as the duration of catheterization and use of a semipermeable transparent dressing have been reported to be independently associated with positive cultures of catheters. (22) We found a significantly higher risk of vascular catheter-associated infection in patients who had more loss of function before surgey. Following guidelines for the prevention of intravascular catheter-related infections can decrease the risk of vascular catheter-associated infection in surgical patients. (21) Some evidence-based recommendations include: educating and designating trained healthcare personnel and assessing their knowledge and adherence to guidelines, correcting selection of catheters and sites, hand hygiene and aseptic techniques, maximal sterile barrier precautions, and appropriate catheter site dressing regimens. (21)

Our study results show poor glycemic control is the second most common HAC in kidney transplant patient and it is reversly associated with patient's age. Perioperative hyperglycemia has been reported as an adverse outcome predictor in surgical patients even in the non-diabetic population. (23,24) It has been reported that postoperative blood glucose greater than 140 mg/dL is present in as many as 40% of non-cardiac surgery patients and 25% of those patients have a blood glucose level greater than 180 mg/dL. (24) Checking the blood glucose in the morning of surgery in patients with and without a history of diabetes is recommended. (23) Blood glucose level of 150 mg/dl has been reported as the cutoff point for increasing risks of mortality, morbidity, and hospitalization length, particularly in those who do not have a prior diagnosis of diabetes. (24) Perioperative immunosupresive medications, such as corticosteroids and prograf, also can increase blood sugar of transplanted patients and make control of blood sugar in such patients difficult; however, further studies are indicated to determine whether strict perioperative blood glucose management improves clinical outcomes in transplanted patients.

Study limitations

There are limitations to the study. Detection of adverse events in the NIS database is limited to the ICD-9-CM coding system and coding error is possible. (25,26) Despite our attempts to adjust for all possible confounders, we could not measure some variables that contribute to patient outcomes, such as warm and cold ischemia time, presence of urinary stent, effects of perioperative immunosupresive medications, and length of use of urinary catheter. The NIS dataset misses some potentially important explanatory variables, such as anatomic or laboratory data. Also, The NIS has no ability to follow patient outcomes longitudinally. Despite these limitations, the advantage of using the NIS database is the broad national geographic representation across all regions of the country and also the possibility of reporting weighted results as national outcomes.

Conclusion

HAC and NE after kidney transplantation are uncommon; however, they are associated with a significant increase in mortality, morbidity, hospitalization length, and hospital charges. Quality improvement initiatives should target HAC and NE in order to successfully reduce or prevent these events. The severity of loss of function before surgey is a reliable factor to identify patients at high risk for postoperative NE and HAC. Falling is the most common preventable HAC in kidney transplant patients. The severity of loss of function before surgey is significantly associated with falling, retained foreign body, catheter-related urinary tract infection, and vascular catheter-associated infection. The risks of poor glycemic control and catheter-related urinary tract infection significantly increase in the elderly. Following guideline recommendations in the prevention of HAC and NE may decrease the rates of NE and HAC in high-risk patients.

Competing interests: The authors report no competing personal or financial interests.

This paper has been peer-reviewed.

References

(1.) Teufack SG, Campbell P, Jabbour P, et al. Potential financial impact of restriction in "never event" and peri-procedural hospital-acquired condition reimbursement at a tertiary neurosurgical centre: A single-institution prospective study. J Neurosurg 2010;1 12:249-56. https://doi.org/10.3171/2009.7.JNS09753

(2.) Lembitz A, Clarke TJ. Clarifying "never events and introducing "always events." Patient Saf Surg 2009;3:26. https://doi.org/10.1186/1754-9493-3-26

(3.) Nero DC, Lipp MJ, Callahan MA. The financial impact of hospital-acquired conditions. J Health Care Finance 2012;38:40-9.

(4.) Mehtsun WT, Ibrahim AM, Diener-West M, et al. Surgical never events in the United States. Surgery 2013;153:465-72. https://doi.org/10.1016/j.surg.2012.10.005

(5.) HCUP Nationwide Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). 2000-2010. Agency for Healthcare Research and Quality, Rockville, MD. Available at www.hcup-us.ahrq.gov/nisoverview.jsp. Accessed October 19, 2017.

(6.) The International Classification of Diseases Nr, Clinical Modification: ICD-9-CM. 4th ed. Washington, DC, Services USDoHaH, 1991 Aahwidc.

(7.) Shah NK, Farber A, Kalish JA, et al. Occurrence of "never events" after major open vascular surgery procedures. J Vasc Surg 2016;63:738-45.e728. https://doi.org/10.1016/j.jvs.2015.09.024

(8.) Wen T, He S, Attenello F, et al. The impact of patient age and comorbidities on the occurrence of "never events" in cerebrovascular surgery: An analysis of the Nationwide Inpatient Sample. J Neurosurg 2014;121:580-6. https://doi.org/10.3171/2014.4.JNS131253

(9.) Wen T, Pease M, Attenello FJ, et al. Evaluation of effect of weekend admission on the prevalence of hospital-acquired conditions in patients receiving cervical fusions. World Neurosurg 2015;84:58-68. https://doi.org/10.1016/j.wneu.2015.02.028

(10.) Fry DE, Pine M, Jones BL, et al. Patient characteristics and the occurrence of never events. Arch Surg 2010;145:148-51. https://doi.org/10.1001/archsurg.2009.277

(11.) Guggenbichler JP, Assadian O, Boeswald M, et al. Incidence and clinical implication of nosocomial infections associated with implantable biomaterials--catheters, ventilator-associated pneumonia, urinary tract infections. GMS Krankenhhyg Interdiszip 2011;6:Doc18.

(12.) Tambyah PA, Oon J. Catheter-associated urinary tract infection. Curr Opin Infect Dis 2012;25:365-70. https://doi.org/10.1097/QCO.0b013e32835565cc

(13.) Reed D, Kemmerly SA. Infection control and prevention: A review of hospital-acquired infections and the economic implications. Ochsner J 2009;9:27-31.

(14.) Rebmann T, Greene LR. Preventing ventilator-associated pneumonia: An executive summary of the Association for Professionals in Infection Control and Epidemiology, Inc, elimination guide. Am J Infect Control 2010;38:647-9. https://doi.org/10.1016/j.ajic.2010.08.004

(15.) Saint S, Wiese J, Amory JK, et al. Are physicians aware of which of their patients have indwelling urinary catheters? Am J Med 2000;109:476-80. https://doi.org/10.1016/S0002-9343(00)00531-3

(16.) Church S, Robinson TN, Angles EM, et al. Postoperative falls in the acute hospital setting: Characteristics, risk factors, and outcomes in males. Am J Surg 2011;201:197-202. https://doi.org/10.1016/j.amjsurg.2009.12.013

(17.) Robinson TN, Eiseman B, Wallace JI, et al. Redefining geriatric preoperative assessment using frailty, disability, and comorbidity. Ann Surg 2009;250:449-55. https://doi.org/10.1097/SLA.0b013e3181b45598

(18.) Dasgupta M, Dumbrell AC. Preoperative risk assessment for delirium after noncardiac surgery: A systematic review. J Am Geriatr Soc 2006;54:1578-89. https://doi.org/10.1111/j.1532-5415.2006.00893.x

(19.) Robinson TN, Raeburn CD, Tran ZV, et al. Postoperative delirium in the elderly: Risk factors and outcomes. Ann Surg 2009;249:173-8. https://doi.org/10.1097/SLA.0b013e31818e4776

(20.) Mermel LA. Prevention of intravascular catheter-related infections. Ann Intern Med 2000;132:391-402. https://doi.org/10.7326/0003-4819-132-5-200003070-00009

(21.) O'Grady NP, Alexander M, Burns LA, et al. Guidelines for the prevention of intravascular catheter-related infections. Clin Infect Dis 2011;52:e162-93. https://doi.org/10.1093/cid/cir257

(22.) Richet H, Hubert B, Nitemberg G, et al. Prospective, multicentre study of vascular catheter-related complications and risk factors for positive central catheter cultures in intensive care unit patients. J Clin Microbiol 1990;28:2520-5.

(23.) Kwon S, Thompson R, Dellinger P, et al. Importance of perioperative glycemic control in general surgery: A report from the Surgical Care and Outcomes Assessment Program. Ann Surg 2013;257:8-14. https://doi.org/10.1097/SLA.0b013e31827b6bbc

(24.) Frisch A, Chandra P, Smiley D, et al. Prevalence and clinical outcome of hyperglycemia in the perioperative period in noncardiac surgery. Diabetes Care 2010;33:1783-8. https://doi.org/10.2337/dc10-0304

(25.) Lorence DP, Ibrahim IA. Benchmarking variation in coding accuracy across the United States. J Health Care Finance 2003;29:29-42.

(26.) Berthelsen CL. Evaluation of coding data quality of the HCUP National Inpatient Sample. Top Health Inf Manage 2000;21:10-23.

Zhobin Moghadamyeghaneh, MD; Linda J. Chen, MD; Mahmoud Alameddine, MD; Anupam K. Gupta, MD; George W. Burke, MD; Gaetano Ciancio, MD

Department of Surgery, Division of Transplant Surgery, Jackson Memorial Hospital/University of Miami, Miami, FL, United States

Correspondence: Dr. Gaetano Ciancio, Department of Surgery, Division of Transplant Surgery, Jackson Memorial Hospital/University of Miami, Miami, FL, United States; gciancio@med.miami.edu

Cite as: Can Urol Assoc J 2017;11(11):F431-6 http://dx.doi.org/10.5489/cuaj.4370

Published online November 1, 2017

http://dx.doi.org/10.5489/cuaj.4370

Please Note: Illustration(s) are not available due to copyright restrictions.
Table 1. Hospital-acquired conditions and never events identification
codes

Diagnosis                      ICD-9 codes

Hospital-acquired
conditions (HAC)
 Air embolism                  999.1
 Blood incompatibility         999.60, 999.61, 999.62, 999.63, 999.69
 Pressure ulcer stages         707.23, 707.24
 III & IV
 Falls and trauma              800-829, 830-839, 850-854, 925-929,
                               940-949,991-994
 Catheter-associated           996.64
 urinary tract infection
 Vascular catheter-associated  999.31, 999.32, 999.33
 infection
 Poor glycemic control         250.10-250.13, 250.20-250.23,
                               251.0, 249.10-249.11, 249.20-249.21
Never events
 Retained foreign body         E871.0, E871.9, 998.4, 998.7
 Wrong operation on            E876.5
 correct patient
 Wrong operation intended      E876.6
 for another patient
Correct operation on wrong     E876.7
body part/site

Table 2. Demographics and clinical characteristics of patients
underwent kidney transplant with or without never events (NE) and
hospital-acquired conditions (HAC)

Variables                               Patients         Patients
                                        with NE          without
                                        or HAC           NE or HAC

Age               Mean[+ or -]standard  48[+ or -]16     47[+ or -]15
                  deviation (years)
                  Median (years)        50               50
Sex               Female                41.5%            39.8%
                  White                 65.9%            44.6%
                  Black or African      20.3%            18.3%
                  American
Race              Hispanic               8.9%            12.8%
                  Asian                  0.8%             3.8%
                  Other or               4.1%            20.5%
                  unknown
                  Fluid and             37.7%            31.8%
                  electrolyte
                  disorders
                  Coagulopathy          12.3%             7.1%
                  Deficiency            40.4%            41.2%
                  anemia
                  Diabetes              47.6%            23.9%
                  Liver disease          5.5%             3.1%
                  Weight loss            2.1%             1.2%
Comorbidity       Hypertension          14.4%            10.8%
                  Chronic                5.4%             5.6%
                  pulmonary
                  disease
                  Obesity                5.5%             7.5%
                  Congestive             5.4%             4.9%
                  heart failure
                  Peripheral             7.5%             4.8%
                  vascular
                  disorders
                  Minor likelihood       7.9%            32.5%
                  of dying
Preoperative      Moderate              47.4%            46.7%
expected          likelihood of
mortality         dying
                  Major likelihood      30.7%            17.8%
                  of dying
                  Extreme               14%               3.1%
                  likelihood of
                  dying
                  Minor loss of          3.5%            15.7%
                  function
Preoperative      Moderate loss         27.2%            46.6%
                  of function
loss of function  Major loss of         45.6%            32.2%
                  function
                  Extreme loss of       23.7%             5.5%
                  function
                  Hypertension          23.1%            42.1%
                  Diabetes              63.9%            34.6%
                  mellitus
                  Previous kidney
Indication        transplant             5.4%             6.1%
of kidney         failure
transplant        Polycystic             1.4%             3.3%
                  kidney disease
                  Lupus                 0%                1.5%
                  erythematous
                  Other                  6.1%            12.4%
Admission type    Elective              54.4%            54.8%
                  Non-elective          45.6%            45.2%
Hospitalization   Mean[+ or -]standard  13[+ or -]11     7[+ or -]7
length            deviation (days)
                  Median (days)         8                6
Total hospital    Mean[+ or -]standard  $231 801         $146 717
charges           deviation             [+ or -]216 093  [+ or -]97
                                                         759
                  Median                $156 647         $124 184
                  Mortality              1.4%             0.5%
Outcomes          Overall               45.6%            24.2%
                  morbidity

Variables                               P

Age               Mean[+ or -]standard  <0.01
                  deviation (years)
                  Median (years)        ---
Sex               Female                 0.67
                  White                 <0.01
                  Black or African       0.64
                  American
Race              Hispanic               0.04
                  Asian                  0.97
                  Other or               0.04
                  unknown
                  Fluid and              0.12
                  electrolyte
                  disorders
                  Coagulopathy           0.01
                  Deficiency             0.84
                  anemia
                  Diabetes              <0.01
                  Liver disease          0.08
                  Weight loss            0.38
Comorbidity       Hypertension           0.16
                  Chronic                0.94
                  pulmonary
                  disease
                  Obesity                0.34
                  Congestive             0.74
                  heart failure
                  Peripheral             0.12
                  vascular
                  disorders
                  Minor likelihood      <0.01
                  of dying
Preoperative      Moderate              <0.01
expected          likelihood of
mortality         dying
                  Major likelihood      <0.01
                  of dying
                  Extreme               <0.01
                  likelihood of
                  dying
                  Minor loss of         <0.01
                  function
Preoperative      Moderate loss         <0.01
                  of function
loss of function  Major loss of         <0.01
                  function
                  Extreme loss of       <0.01
                  function
                  Hypertension          <0.01
                  Diabetes              <0.01
                  mellitus
                  Previous kidney
Indication        transplant             0.72
of kidney         failure
transplant        Polycystic             0.19
                  kidney disease
                  Lupus                  0.13
                  erythematous
                  Other                  0.09
Admission type    Elective               0.92
                  Non-elective           0.92
Hospitalization   Mean[+ or -]standard  <0.01
length            deviation (days)
                  Median (days)         <0.01
Total hospital    Mean[+ or -]standard  <0.01
charges           deviation
                  Median                <0.01
                  Mortality             <0.01
Outcomes          Overall               <0.01
                  morbidity

Fig. 1. Never events and hospital-acquired conditions after kidney
transplant.

Retained foreign bodies                       6.8%
Poor glycemic control                        20.4%
Vascular catheter-associated infection       19.7%
Catheter-associated urinary tract infection   7.5%
Falling                                      42.2%
Stages III and IV pressure ulcers             2.7%
ABO incompatible blood transfusion            2.0%

Note: Table made from pie chart.

Table 3. Risk adjusted analysis of postoperative complications of
patients with or without never events (NE) and hospital-acquired
conditions (HAC)

Complications            Patients with  Patients without  Adjusted
                         NE or HAC      NE or HAC         odds ratio

Mortality                 1.4%           0.5%             2.49
Overall morbidity (*)    45.6%          24.2%             2.44
Transplanted kidney      10.2%           8.2%             1.23
failure or rejection
Renal vascular            2.7%           0.6%             3.83
complications
Wound disruption          3.4%           0.5%             5.74
Hemorrhagic               7.5%           5.2%             1.28
complications
Ureter complications      4.1%           3.4%             1.19
Unplanned reoperation     5.4%           2.2%             1.92
Prolonged ileus          10.9%           4.7%             2.28
Urinary tract infection  15.6%           3.9%             4.03
Wound infection           2.7%           0.8%             2.63
Pneumonia                 4.1%           1.1%             3.31
Hospitalization           8.2%           1.1%             6.16
>30 days
Acute myocardial          6.1%           2%               2.72
infarction
Acute respiratory         4.8%           1.1%             3.69
failure
Deep vein thrombosis      0%             0.3%             0.99

Complications            95% confidence  p
                         interval

Mortality                1.01-10.31       0.04
Overall morbidity (*)    1.74-3.42       <0.01
Transplanted kidney      0.71-2.12        0.45
failure or rejection
Renal vascular           1.38-10.64       0.01
complications
Wound disruption         2.28-14.41      <0.01
Hemorrhagic              0.68-2.41        0.43
complications
Ureter complications     0.52-2.71        0.67
Unplanned reoperation    1.01-4.02        0.04
Prolonged ileus          1.34-3.88       <0.01
Urinary tract infection  2.54-6.41       <0.01
Wound infection          0.94-7.38        0.06
Pneumonia                1.43-7.67       <0.01
Hospitalization          3.22-11.79      <0.01
>30 days
Acute myocardial         1.36-5.44       <0.01
infarction
Acute respiratory        1.68-8.12       <0.01
failure
Deep vein thrombosis     0.99-1.00        0.51

(*) Includes: Transplanted kidney failure or rejection, renal vascular
complications, wound disruption, hemorrhagic complications, ureter
complications, unplanned reoperation, prolonged ileus, urinary tract
infection, unplanned reoperation, wound infection, pneumonia,
hospitalization more than 30 days, acute myocardial infarction, acute
respiratory failure, deep vein thrombosis.

Table 4. Risk-adjusted analysis of factors associated with
postoperative never events and hospital-acquired conditions

Variables                                      Adjusted    95%
                                              odds ratio  confidence
                                                          interval

Age                    Age                     0.98       0.97-0.99
Sex                    Female                  1.10       0.75-1.61
                       Obesity                 0.48       0.19-1.20
                       Coagulopathy            0.76       0.38-1.44
                       Hypertension            0.89       0.50-1.58
                       Diabetes mellitus       0.99       0.59-1.66
                       Fluid and electrolyte   0.78       0.52-1.18
                       abnormalities
Comorbidity            Chronic lung disease    0.94       0.41-2.16
                       Weight loss             0.77       0.18-3.19
                       Deficiency anemia       0.89       0.60-1.32
                       Congestive heart        0.50       0.20-1.26
                       failure
                       Peripheral vascular     1.05       0.51-2.24
                       disorders
                       Liver disease           1.32       0.53-3.29
Preoperative expected  Low or moderate        Reference   Reference
mortality              likelihood of dying
                       High or extreme high    1.62       1.03-2.55
                       likelihood of dying
Preoperative loss      Minor or moderate      Reference   Reference
of function            loss of function
                       Major or extreme        3.25       1.95-5.41
                       loss of function

                                                p

Age                    Age                     0.03
Sex                    Female                  0.61
                       Obesity                 0.12
                       Coagulopathy            0.45
                       Hypertension            0.70
                       Diabetes mellitus       0.99
                       Fluid and electrolyte   0.24
                       abnormalities
Comorbidity            Chronic lung disease    0.89
                       Weight loss             0.72
                       Deficiency anemia       0.57
                       Congestive heart        0.14
                       failure
                       Peripheral vascular     0.87
                       disorders
                       Liver disease           0.54
Preoperative expected  Low or moderate        Reference
mortality              likelihood of dying
                       High or extreme high    0.03
                       likelihood of dying
Preoperative loss      Minor or moderate      Reference
of function            loss of function
                       Major or extreme       <0.01
                       loss of function
COPYRIGHT 2017 Canadian Urological Association
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2017 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:ORIGINAL RESEARCH
Author:Moghadamyeghaneh, Zhobin; Chen, Linda J.; Alameddine, Mahmoud; Gupta, Anupam K.; Burke, George W.; C
Publication:Canadian Urological Association Journal (CUAJ)
Article Type:Report
Date:Nov 1, 2017
Words:4528
Previous Article:A nationwide analysis of re-operation after kidney transplant.
Next Article:Can zero-hour cortical biopsy predict early graft outcomes after living donor renal transplantation?
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters