Aziz M. Merchant, Rutgers-New Jersey Medical School, 185 South Orange Avenue, Suite MSB G530, Newark, NJ 07103 USA, Tel no: 973 972-0072, Fax no: 973 972-6803; E-mail:
Methods: This is a retrospective cohort study of patients undergoing acute care abdominal surgery between 2006 and 2010 extracted from the National Inpatient Sample database. Surgical outcomes examined were in-hospital mortality, surgical, and medical complications, length of stay, and total hospital charges. Sequential multivariable generalized linear regression models were used to compare the outcomes across surgical modality and type of liver disease.
Results: Unadjusted and adjusted analyses revealed that laparoscopic surgery was associated with marked reduction in mortality (92%) and surgical complications (86%) compared to open surgery, as well as a moderate yet significant reduction (60%) for medical complications, length of stay and total hospital charges. Patients with cirrhotic liver disease fared worse compared to those with non-cirrhotic and no liver disease, as expected.
Conclusion: Laparoscopic surgery provides a feasible alternative for patients with liver disease undergoing acute care surgery.
Keywords: Acute care surgery; Laparoscopic surgery; Surgical outcomes; Liver disease
One of the most marked risks of poor outcomes in cirrhotic patients is the need for emergent surgical interventions [7]. Patients with compromised liver function are known to decompensate due to the stress of both anesthesia and surgery, and in spite of significant advances mortality and morbidity continue to remain high [8]. A recent series by Del Olmo, et al comparing 135 cirrhotic patients with 86 non cirrhotic patients, all undergoing non-hepatic general surgery, showed a 16.3% 1-month cirrhotic mortality compared with 3.5% for their control [9]. In addition, various complications affect the surgical outcome of these patients, including bleeding, infection, renal insufficiency, and multisystem organ failure [10]. The underlying liver dysfunction predisposes cirrhotic patients to coagulopathy resulting in excessive perioperative bleeding, hepatic hypoperfusion, septic complications, poor wound healing, and multiorgan dysfunction. In trauma settings, numerous retrospective studies have noted excessive mortality rates among cirrhotic patients compared with their non-cirrhotic counterparts [11-13].
Recently, laparoscopy has gained traction as an important adjunct in the surgical treatment of cirrhotic patients who require acute care surgery. Cirrhosis was considered an absolute contraindication to laparoscopy because of the risk for massive bleeding during dissection [14]. However, several case-series have recently reported success with laparoscopic acute care operations, e.g., laparoscopic cholecystectomy, in selected patients with cirrhosis [15-17]. One study reports 528 patients with cirrhosis who have undergone laparoscopic cholecystectomy. Most of these patients (81%) are classified as Child-Pugh a cases, and only 1.1% are classified as C cases. The overall morbidity is 16%, and the mortality rate is less than 1%. These results compare favorably with those for open cholecystectomy and suggest that laparoscopic cholecystectomy can be performed safely for patients classified as Child-Pugh A and B cases. Though these reports, which happen to be predominantly case-series or single-center studies with a focus on one specific surgical procedure (i.e. cholecystectomy), demonstrate the safety and efficacy of laparoscopy in patients with cirrhotic liver disease, they have limited generalizability due to their scope and study design.
In our current study, we attempt to overcome some these limitations by using a large, national representative database, the National Inpatient Sample, to study surgical outcomes across all acute care abdominal surgeries and compare outcomes by patients’ liver disease status and type of surgery (laparoscopic versus open). Furthermore, we compare outcomes by type of liver disease separately within each surgical modality, as well as analyze outcomes by surgical modality within each liver disease status cohort.
Our primary exposure was liver disease status. Study patients were assigned to 3 liver disease groups: no liver disease, non-cirrhotic liver disease, and cirrhotic liver disease. The assignment was based on the presence of the following of ICD- 9-CM diagnoses codes, in position 1 to 15: non-cirrhotic liver disease (070.22, 070.23, 070.32, 070.33, 070.44, 070.54, 456.0, 456.1, 456.20, 456.21, 571.0, 571.3, 571.40, 571.8, 571.9, 572.3, and 572.8) and cirrhotic liver disease (571.2, 571.5, and 571.6). Patients with both non-cirrhotic and cirrhotic liver disease codes were assigned to the cirrhotic liver disease group. Our second primary exposure group was type of surgery: laparoscopic or open surgery.
We used several patient-level characteristics and hospitallevel characteristics in our multivariable regression analyses. Patients’ age (< 40, 50-64, 65-79, ≥ 80), gender, race (White, Black, Hispanic, Other, Unknown), type of insurance (Medicare, Medicaid, private, self-pay, other, no charge), and number of chronic comorbidities (none, one, two, three or more) from the list of 29 co-existing medical illnesses provided in the NIS database (excluding liver disease) were our patient-level variables and all of them were categorical in nature. Similarly, we had 4 categorical variables pertaining to the hospitals from which the patients were sampled. The hospital-level variables were hospital size (small, medium, large), region (Northeast, Midwest, South, and West), teaching vs non-teaching, and location (urban vs rural).
Data in the NIS database is hierarchical in nature i.e. patients are nested (or clustered) within hospitals and hence study outcomes cannot be assessed using conventional regression models which assume independence of observations. To account for the clustered nature of study design we fit generalized linear models using PROC GENMOD. REPEATED statement with SUBJECT=HOSPID was used to invoke generalized estimating equations (GEE) methods to account for the clustering of patients within hospitals and to allow computation of robust standard errors. When modelling for categorical outcomes (inhospital mortality, any surgical, and any medical complication), we assumed a binary distribution with logit-link function and exchangeable working correlation structure. We modelled the continuous outcomes (hospital length of stay and total charges) in their original form, without any transformation, using loglink and exchangeable working correlation structure. Negative binomial and gamma distributions were used to model hospital length of stay and total charges, respectively.
We fit 5 sequential models for each of our study outcomes. Our model 1, unadjusted analyses, included only liver disease status as explanatory variable. We re-ran model 1 with type of surgery alone. Sequential multivariable regression models were fit with incremental addition of explanatory variables in the following order- Model 2 (liver disease status and type of surgery); Model 3 (model2 variables + patient characteristics [age, gender, race, type of insurance, and number of comorbidities]; Model 4 (model 3 variables plus hospital characteristics [region, size, location, and teaching status]; Model 5 (model 4 variables plus interaction term between liver disease status and type of surgery). For all outcomes our saturated models had the lowest Quasi-likelihood under the Independence Model Criterion (QIC) scores. LSMEANS statement was used to obtain odds ratios for variables in the interaction term. Exponentiation of parameter estimates obtained when using LSMEANS statement along with DIFF option provided adjusted odds ratios (for categorical outcomes) and adjusted ratios (for continuous outcomes) for the other variables in the model. We presented point-estimates with 95% confidence intervals. Given our large sample size we used a conservative cutoff of p-value < 0.01 to infer statistical significance.
Characteristic |
Overall (N=893,681) |
Type of Surgery |
Liver disease status |
|||
Laparoscopic |
Open (N=448,824) |
No Liver Disease |
Non-Cirrhotic Liver Disease |
Cirrhotic Liver Disease |
||
Age categories |
||||||
< 40 |
29.6 |
38.5 |
20.8 |
30.1 |
22.9 |
5.0 |
40-64 |
38.6 |
38.1 |
39.1 |
38.0 |
57.9 |
61.3 |
65-79 |
20.4 |
15.6 |
25.1 |
20.4 |
15.5 |
25.5 |
≥ 80 |
11.4 |
7.8 |
15.0 |
11.6 |
3.7 |
8.3 |
Female |
58.5 |
61.8 |
55.2 |
58.8 |
53.9 |
40.7 |
Race |
||||||
Black |
9.6 |
8.0 |
11.2 |
9.6 |
10.3 |
8.6 |
Hispanic |
9.8 |
12.3 |
7.4 |
9.8 |
11.3 |
10.5 |
Other |
4.8 |
5.3 |
4.3 |
4.8 |
5.0 |
4.5 |
Unknown |
19.8 |
18.6 |
21.1 |
19.9 |
16.4 |
19.6 |
White |
56.0 |
55.8 |
56.1 |
56.0 |
57.0 |
56.8 |
Type of Insurance |
||||||
Medicare |
33.4 |
24.8 |
41.9 |
33.4 |
26.1 |
42.5 |
Medicaid |
11.1 |
11.6 |
10.5 |
11.0 |
14.0 |
15.8 |
Private |
41.3 |
47.2 |
35.6 |
41.4 |
44.4 |
28.7 |
Self-pay |
9.2 |
11.0 |
7.5 |
9.2 |
9.8 |
7.5 |
No Charge |
1.1 |
1.4 |
0.9 |
1.1 |
1.4 |
0.9 |
Other |
3.6 |
3.8 |
3.4 |
3.6 |
4.1 |
4.4 |
Chronic Comorbidities |
||||||
None |
30.9 |
38.8 |
23.0 |
31.5 |
14.2 |
7.1 |
One |
22.5 |
24.3 |
20.8 |
22.6 |
22.4 |
15.6 |
Two |
18.3 |
16.7 |
19.9 |
18.2 |
23.4 |
22.9 |
Three or more |
28.3 |
20.2 |
36.4 |
27.8 |
40.0 |
54.4 |
Hospital Region |
||||||
Northeast |
21.5 |
20.7 |
22.2 |
21.6 |
16.8 |
19.1 |
Midwest |
22.9 |
21.7 |
24.7 |
23.0 |
20.2 |
21.8 |
South |
44.2 |
45.2 |
43.3 |
44.1 |
48.5 |
45.9 |
West |
11.4 |
12.4 |
10.3 |
11.3 |
14.5 |
13.2 |
Hospital Bed Size |
||||||
Small |
12.0 |
12.0 |
11.9 |
12.1 |
10.1 |
9.3 |
Medium |
24.9 |
25.6 |
24.1 |
24.9 |
23.7 |
22.0 |
Large |
62.1 |
61.4 |
62.8 |
62.0 |
64.6 |
67.7 |
Urban Hospital |
85.8 |
86.4 |
85.1 |
85.7 |
89.3 |
88.2 |
Teaching Hospital |
43.1 |
40.1 |
46.0 |
43.0 |
42.7 |
51.3 |
Study Outcomes |
Overall
(N=893,681) |
Type of Surgery |
Liver disease status |
|||
Laparoscopic (N=444,857) |
Open (N=448,824) |
No Liver Disease |
Non-Cirrhotic Liver Disease |
Cirrhotic Liver Disease |
||
|
Categorical Outcomes (in %) |
|||||
In-hospital death |
3.1 |
0.5 |
5.7 |
3.0 |
2.7 |
9.3 |
Any surgical complication |
8.1 |
2.3 |
13.9 |
8.1 |
7.4 |
13.2 |
Any medical complication |
22.8 |
14.4 |
31.1 |
22.6 |
21.7 |
39.1 |
|
Continuous Outcomes |
|||||
Hospital length of stay (in days) |
|
|
|
|
|
|
Mean (SD) |
7.3 (10.1) |
4.0 (4.9) |
10.6 (12.5) |
7.2 (10.0) |
7.3 (9.7) |
10.9 (13.1) |
Median (P25-P75) |
4 (2-9) |
3 (2-5) |
7 (4-13) |
4 (2-9) |
5 (3- 8) |
7 (4-13) |
Hospital charges (in $) |
|
|
|
|
|
|
Mean (SD) |
53,878 (81,022) |
33,394 (37,264) |
74,222 (104,281) |
53,190 (79,705) |
61,733 (97,208) |
96,005 (130,438) |
Median (P25-P75) |
30,449 (18,831-55,628) |
24,724 |
41,891 (22,583-81,853) |
30,178 (18,694-5,5038) |
36,326 (22,945-61,263) |
51,016 (28,368-106,001) |
|
In-hospital death |
Any Surgical Complication |
Any Medical Complication |
|
||
Liver disease status |
||||||
Cirrhotic |
2.68 (2.47-2.91) |
<.0001 |
1.26 (1.16-1.36) |
<.0001 |
1.43 (1.36-1.51) |
<.0001 |
Non-Cirrhotic |
1.41 (1.28-1.56) |
<.0001 |
1.04 (0.98-1.12) |
0.1984 |
1.00 (0.95-1.05) |
0.9852 |
No liver disease |
REF |
. |
REF |
. |
REF |
. |
Type of surgery |
||||||
Laparoscopic |
0.13 (0.13-0.14) |
<.0001 |
0.18 (0.17-0.18) |
<.0001 |
0.58 (0.57-0.59) |
<.0001 |
Open |
REF |
. |
REF |
. |
REF |
. |
Age categories |
||||||
< 40 |
REF |
. |
REF |
. |
REF |
. |
40-64 |
2.25 (2.09-2.42) |
<.0001 |
1.46 (1.42-1.50) |
<.0001 |
1.69 (1.65-1.74) |
<.0001 |
65-79 |
4.27 (3.92-4.66) |
<.0001 |
1.32 (1.27-1.37) |
<.0001 |
3.31 (3.20-3.43) |
<.0001 |
≥ 80 |
6.87 (6.28-7.51) |
<.0001 |
1.10 (1.05-1.14) |
<.0001 |
6.35 (6.12-6.59) |
<.0001 |
Gender |
||||||
Male |
1.22 (1.19-1.26) |
<.0001 |
1.07 (1.05-1.09) |
<.0001 |
1.16 (1.15-1.18) |
<.0001 |
Female |
REF |
. |
REF |
. |
REF |
. |
Race |
||||||
Black |
0.99 (0.94-1.04) |
0.6232 |
0.98 (0.95-1.02) |
0.307 |
1.07 (1.04-1.09) |
<.0001 |
Hispanic |
0.85 (0.79-0.90) |
<.0001 |
0.92 (0.88-0.96) |
<.0001 |
0.85 (0.82-0.87) |
<.0001 |
Other |
1.03 (0.96-1.11) |
0.3798 |
1.03 (0.98-1.07) |
0.2863 |
0.90 (0.87-0.93) |
<.0001 |
Unknown |
1.12 (1.06-1.18) |
<.0001 |
0.94 (0.90-0.98) |
0.0023 |
1.02 (0.99-1.05) |
0.1336 |
White |
REF |
. |
REF |
. |
REF |
. |
Type of insurance |
||||||
Medicaid |
1.44 (1.36-1.52) |
<.0001 |
1.04 (1.01-1.08) |
0.0161 |
1.45 (1.41-1.49) |
<.0001 |
Medicare |
1.48 (1.41-1.55) |
<.0001 |
1.16 (1.13-1.20) |
<.0001 |
1.56 (1.52-1.59) |
<.0001 |
No Charge |
0.89 (0.70-1.13) |
0.3401 |
0.83 (0.74-0.93) |
0.0011 |
1.02 (0.95-1.10) |
0.5722 |
Other |
1.23 (1.10-1.37) |
0.0002 |
1.04 (0.99-1.10) |
0.123 |
1.13 (1.08-1.18) |
<.0001 |
Self-Pay |
1.24 (1.14-1.34) |
<.0001 |
0.78 (0.75-0.81) |
<.0001 |
1.03 (1.00-1.07) |
0.0318 |
Private |
REF |
. |
REF |
. |
REF |
. |
No of chronic comorbidities |
||||||
None |
REF |
. |
REF |
. |
REF |
. |
One |
1.59 (1.49-1.70) |
<.0001 |
1.41 (1.37-1.46) |
<.0001 |
1.97 (1.92-2.02) |
<.0001 |
Two |
1.98 (1.83-2.15) |
<.0001 |
1.54 (1.48-1.59) |
<.0001 |
3.02 (2.92-3.12) |
<.0001 |
Three or more |
2.91 (2.66-3.18) |
<.0001 |
1.68 (1.61-1.76) |
<.0001 |
6.82 (6.52-7.13) |
<.0001 |
Hospital bed size |
||||||
Small |
0.72 (0.67-0.77) |
<.0001 |
0.87 (0.82-0.92) |
<.0001 |
0.79 (0.76-0.83) |
<.0001 |
Medium |
0.89 (0.84-0.94) |
<.0001 |
0.91 (0.87-0.95) |
<.0001 |
0.89 (0.86-0.92) |
<.0001 |
Large |
REF |
. |
REF |
. |
REF |
. |
Hospital location |
||||||
Rural |
0.84 (0.79-0.9) |
<.0001 |
0.91 (0.86-0.96) |
0.0002 |
0.77 (0.74-0.79) |
<.0001 |
Urban |
REF |
. |
REF |
. |
REF |
. |
Hospital region |
||||||
Northeast |
1.15 (1.05-1.26) |
0.0018 |
0.77 (0.71-0.84) |
<.0001 |
0.99 (0.93-1.05) |
0.7225 |
Midwest |
0.90 (0.82-0.98) |
0.0141 |
0.81 (0.75-0.87) |
<.0001 |
1.00 (0.95-1.06) |
0.9505 |
South |
1.11 (1.03-1.21) |
0.0102 |
0.78 (0.73-0.83) |
<.0001 |
1.03 (0.97-1.08) |
0.3484 |
West |
REF |
. |
REF |
. |
REF |
. |
Teaching Hospital |
||||||
No |
0.78 (0.73-0.82) |
<.0001 |
0.77 (0.74-0.81) |
<.0001 |
0.87 (0.85-0.9) |
<.0001 |
Yes |
REF |
. |
REF |
. |
REF |
. |
Table 4 illustrates the results from our adjusted multivariable generalized linear models for the two continuous outcomes (hospital length of stay and total charges).As expected, patients with no liver disease who underwent acute care surgery had a shorter length of stay and lower hospital charges than cirrhotic and non-cirrhotic liver disease patients; cirrhotic liver disease portended the longest length of stay and highest hospital charges compared to the other two. In this adjusted model, laparoscopic surgery, younger age, Hispanic race, small and medium hospital size, rural hospital location, and non-teaching hospital status were predictive of lower hospital length of stay and total charges. In contrast, male gender, and Medicare and Medicaid insurance status were related to higher length of stay and total charges.
Our study has a number of important findings. First, inhospital mortality was higher amongst patients with cirrhotic
Hospital Length of Stay |
Hospital Total Charges |
|||
Liver disease status |
||||
Cirrhotic |
1.16 (1.13-1.20) |
<.0001 |
1.32 (1.24-1.40) |
<.0001 |
Non-Cirrhotic |
1.08 (1.06-1.10) |
<.0001 |
1.11 (1.07-1.14) |
<.0001 |
No liver disease |
REF |
. |
REF |
. |
Type of surgery |
||||
Laparoscopic |
0.47 (0.47-0.48) |
<.0001 |
0.56 (0.55-0.57) |
<.0001 |
Open |
REF |
. |
REF |
. |
Age categories |
||||
< 40 |
1.27 (1.26-1.28) |
<.0001 |
1.18 (1.17-1.19) |
<.0001 |
40-64 |
1.37 (1.35-1.40) |
<.0001 |
1.27 (1.25-1.29) |
<.0001 |
65-79 |
1.46 (1.44-1.49) |
<.0001 |
1.27 (1.25-1.30) |
<.0001 |
≥ 80 |
REF |
. |
REF |
. |
Gender |
||||
Male |
1.08 (1.07-1.09) |
<.0001 |
1.12 (1.11-1.13) |
<.0001 |
Female |
REF |
. |
REF |
. |
Race |
||||
Black |
1.08 (1.07-1.1) |
<.0001 |
1.03 (1.01-1.04) |
0.0003 |
Hispanic |
0.97 (0.96-0.98) |
<.0001 |
0.95 (0.93-0.96) |
<.0001 |
Other |
1.00 (0.99-1.02) |
0.5729 |
1.00 (0.98-1.01) |
0.6863 |
Unknown |
1.05 (1.03-1.06) |
<.0001 |
0.96 (0.94-0.99) |
0.0016 |
White |
REF |
. |
REF |
. |
Type of insurance |
||||
Medicaid |
1.23 (1.22-1.25) |
<.0001 |
1.13 (1.11-1.14) |
<.0001 |
Medicare |
1.20 (1.19-1.22) |
<.0001 |
1.16 (1.14-1.17) |
<.0001 |
No Charge |
1.06 (1.03-1.10) |
0.0005 |
1.01 (0.96-1.05) |
0.8069 |
Other |
1.09 (1.07-1.11) |
<.0001 |
1.06 (1.03-1.08) |
<.0001 |
Self-Pay |
1.02 (1.01-1.03) |
0.0012 |
1.00 (0.99-1.01) |
0.8254 |
Private |
REF |
. |
REF |
. |
No of chronic comorbidities |
||||
None |
2.11 (2.06-2.16) |
<.0001 |
1.87 (1.83-1.92) |
<.0001 |
One |
1.35 (1.34-1.37) |
<.0001 |
1.25 (1.23-1.26) |
<.0001 |
Two |
1.61 (1.59-1.64) |
<.0001 |
1.44 (1.42-1.47) |
<.0001 |
Three or more |
REF |
. |
REF |
. |
Hospital bed size |
||||
Small |
0.90 (0.88-0.92) |
<.0001 |
0.90 (0.86-0.94) |
<.0001 |
Medium |
0.84 (0.81-0.86) |
<.0001 |
0.78 (0.75-0.83) |
<.0001 |
Large |
REF |
. |
REF |
. |
Hospital location |
||||
Rural |
0.83 (0.81-0.84) |
<.0001 |
0.65 (0.63-0.68) |
<.0001 |
Urban |
REF |
. |
1 (1-1) |
. |
Hospital region |
||||
Northeast |
1.12 (1.08-1.15) |
<.0001 |
0.91 (0.84-0.98) |
0.0119 |
Midwest |
0.94 (0.91-0.97) |
0.0001 |
0.84 (0.79-0.88) |
<.0001 |
South |
1.06 (1.02-1.09) |
0.0005 |
1.03 (0.98-1.09) |
0.2451 |
West |
REF |
. |
REF |
. |
Teaching Hospital |
||||
No |
0.81 (0.79-0.83) |
<.0001 |
0.82 (0.78-0.87) |
<.0001 |
Yes |
REF |
. |
REF |
. |
Laparoscopic Surgery |
Open Surgery |
|||
Categorical Outcomes |
||||
Adjusted Odds Ratios (95% CI) |
p-value |
Adjusted Odds Ratios (95% CI) |
p-value |
|
In-hospital mortality |
||||
Cirrhotic vs No liver disease |
2.94 (2.47-3.51) |
<.0001 |
2.64 (2.43-2.88) |
<.0001 |
Non-Cirrhotic vs No liver disease |
1.13 (0.90-1.42) |
0.3003 |
1.48 (1.33-1.65) |
<.0001 |
Cirrhotic vs Non-Cirrhotic |
2.61 (1.96-3.48) |
<.0001 |
1.79 (1.57-2.04) |
<.0001 |
Any Surgical Complication |
||||
Cirrhotic vs No liver disease |
1.34 (1.16-1.54) |
<.0001 |
1.24 (1.13-1.36) |
<.0001 |
Non-Cirrhotic vs No liver disease |
0.95 (0.84-1.07) |
0.374 |
1.08 (1.00-1.18) |
0.0511 |
Cirrhotic vs Non-Cirrhotic |
1.41 (1.17-1.69) |
0.0002 |
1.14 (1.02-1.28) |
0.0227 |
Any Medical Complication |
||||
Cirrhotic vs No liver disease |
1.31 (1.22-1.40) |
<.0001 |
1.53 (1.42-1.64) |
<.0001 |
Non-Cirrhotic vs No liver disease |
0.93 (0.88-0.99) |
0.0251 |
1.09 (1.01-1.17) |
0.0215 |
Cirrhotic vs Non-Cirrhotic |
1.40 (1.28-1.53) |
<.0001 |
1.40 (1.27-1.55) |
<.0001 |
Hospital Length of Stay |
||||
Cirrhotic vs No liver disease |
1.25 (1.21-1.28) |
<.0001 |
1.11 (1.06-1.16) |
<.0001 |
Non-Cirrhotic vs No liver disease |
1.07 (1.05-1.09) |
<.0001 |
1.09 (1.05-1.13) |
<.0001 |
Cirrhotic vs Non-Cirrhotic |
1.16 (1.13-1.20) |
<.0001 |
1.02 (0.96-1.07) |
0.5593 |
Hospital Total Charges |
||||
Cirrhotic vs No liver disease |
1.14 (1.09-1.20) |
<.0001 |
1.46 (1.35-1.58) |
<.0001 |
Non-Cirrhotic vs No liver disease |
1.03 (1.00-1.04) |
0.0026 |
1.26 (1.18-1.35) |
<.0001 |
Cirrhotic vs Non-Cirrhotic |
1.11 (1.06-1.17) |
<.0001 |
1.16 (1.06-1.26) |
0.0011 |
#Conservative p-value of < 0.01 was used to determine significant associations given the large sample size.
Our results are consistent with a number of studies in the literature that compare laparoscopic and open surgical technique in acute care general surgical patients. Tsugawa, et al show that laparoscopic appendectomy resulted in fewer postoperative complications, improved postoperative pain, and lower length of stay in cirrhotic patients, as compared to open appendectomy [20]. In their prospective, randomized study, Hamad, et al concluded that laparoscopic cholecystectomy was comparable to the open approach across all measured outcomes, however, with shorter length of stay and less pain, in Childs-Pugh class A and B cirrhotics [21]. They suggest that the laparoscopic cholecystectomy is the preferred option in this class of patients with cirrhosis. Poggio, et al came to the same conclusion regarding laparoscopic surgery in compensated cirrhotics in a retrospective cohort study of 50 cholecystectomy patients [22].
The overall role of laparoscopy in emergent and urgent surgery is expanding at a rapid rate. Aside from the classic indications of appendicitis and acute cholecystitis, laparoscopy has gained traction in the treatment of diverticulitis, adhesive intestinal obstruction, perforation and/or bleeding from gastroduodenal ulcer disease, diagnosis of abdominal extremis, and even trauma. Laparoscopic peritoneal lavage has proven to be an effective emergent treatment for perforated diverticulitis with a low conversion and high efficacy rate [23-25]. Furthermore, Ming-Zhe et al showed that laparoscopic adhesiolysis for small bowel obstruction was not inferior with respect to the number of iatrogenic enterotomies, surgical site infection, pulmonary complications, or overall mortality, and this has been supported by numerous studies [26-29]. Finally, two important randomized studies, albeit with small populations, have shown the non-inferiority of laparoscopic management of perforated gastroduodenal ulcer disease [30,31]. Our data is consistent with
No liver disease |
Non-Cirrhotic liver disease |
Cirrhotic liver disease |
||||
Categorical Outcomes |
||||||
Adjusted Odds Ratios (95% CI) |
p-value |
Adjusted Odds Ratios (95% CI) |
p-value |
Adjusted Odds Ratios (95% CI) |
p-value |
|
In-hospital mortality |
||||||
Laparoscopic vs Open |
0.13 (0.13-0.14) |
<.0001 |
0.10 (0.08-0.13) |
<.0001 |
0.15 (0.12-0.18) |
<.0001 |
Any Surgical Complication |
||||||
Laparoscopic vs Open |
0.18 (0.17-0.18) |
<.0001 |
0.16 (0.14-0.18) |
<.0001 |
0.19 (0.16-0.23) |
<.0001 |
Any Medical Complication |
||||||
Laparoscopic vs Open |
0.59 (0.58-0.60) |
<.0001 |
0.50 (0.46-0.55) |
<.0001 |
0.50 (0.45-0.55) |
<.0001 |
Continuous Outcomes |
||||||
Adjusted Ratios (95% CI) |
p-value |
Adjusted Ratios (95% CI) |
p-value |
Adjusted Ratios (95% CI) |
p-value |
|
Hospital Length of Stay |
||||||
Laparoscopic vs Open |
0.47 (0.47-0.48) |
<.0001 |
0.46 (0.44-0.49) |
<.0001 |
0.53 (0.51-0.56) |
<.0001 |
Hospital Total Charges |
||||||
Laparoscopic vs Open |
0.56 (0.56-0.57) |
<.0001 |
0.46 (0.43-0.49) |
<.0001 |
0.44 (0.41-0.47) |
<.0001 |
#Conservative p-value of < 0.01 was used to determine significant associations given the large sample size.
The type of liver failure, its severity, and its sequelae can have a profound effect on outcomes after general surgery, however the literature is sparse in addressing this as it relates to acute care surgery [36]. Postoperative mortality was increased in patients who had liver cirrhosis with viral hepatitis or alcoholic liver disease, according to Lin, et al [37]. Indeed, outcomes after cardiac surgery in cirrhotics was clearly related to the Child’s Pugh classification of the cirrhosis [38]. The liver plays an important role in the regulation of nutrition and metabolism; thus, it is not unexpected that liver disease patients may have poor nutrition. Garrison et al used a multivariate analysis to predict survival after abdominal surgery in patients with liver failure, and found that poor nutrition was a significant risk factor in this set of patients, with poor nutrition presumably as a sequelae of the liver failure itself [39]. Specific aspects of liver failure that may contribute to mortality in non-liver surgery are elusive, however, Rice, et al determined that international normalized ratio greater than 1.6 and encephalopathy independently predicted mortality in this population. Interestingly, in their study, Child’s classification did not predict mortality [40].
There are several limitations to our study. Although we were able to study a large sample size, our study is limited in that it is not a randomized controlled trial. Our data lack granular information on occurrence of fatty liver disease, liver function tests, Child’s Pugh scores, and Model of End-Stage Liver Disease (MELD) scores, rendering us unable to differentiate cohorts based on liver disease severity. The data set provides in-hospital data only, with no information available about prior liver disease history or surgery history, or follow-up after discharge. Some patients will undergo acute care surgical procedures (such as appendectomy) and be discharged within 24 hours, which then makes them outpatient status at many hospitals and thus may not be included in the NIS. If this were a substantial proportion of procedures, it would likely cause our analysis to overestimate the procedural complication rate and to underestimate the proportion of patients treated in this type of outpatient setting. Although NIS is a national database with wide reaching penetration, participation is still voluntary. Therefore, our conclusions may not be wholly applicable for every hospital or provider. Nevertheless, our study represents one of the larger series and may be broadly generalizable due to the cohort of hospitals that contribute to the NIS.
Another universal drawback on the use of administrative databases that rely on ICD-9-CM codes is the lack of fidelity in ensuring an accurate diagnosis. Human errors, including but not limited to, under-reporting of an event or inaccuracy in coding or even miscoding, cannot be ruled out to impact our projected estimates. In addition, outcomes are reported for the duration of an inpatient stay; therefore, extrapolation of these data to reflect outcomes beyond this period must be done with caution. In addition, certain outcomes cannot be measured meaningfully within the inpatient time period. One example of an important long-term morbidity of hernia repair is recurrence, which occurs well beyond the inpatient time period and seems to occur progressively over time. Granular details such as the preoperative status of patients, certain symptoms in the perioperative period, use of certain medications that portend risk (e.g., anticoagulants), or symptom recurrence, among others, are not collected within this type of database, and therefore, these important factors are not taken into account in our study.
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