risk scores for surgical an anesthetic risk

1. Calculations of risk scores
Possum e
derivati,EPASS,VBHOM,surgical
apgar,Saps,Apache,Sofa….

2. • SAPS??
• APACHE??

3. Risk prediction on line
• Risk prediction in surgery
[http://www.riskprediction.org.uk/p
pindex.php].
• SFAR

4. • This site has been developed to allow surgeons to estimate risk online for
their patients undergoing surgery. This service is provided for individual
use to help surgeons more fully consent their patients by giving mortality
and other surgical risk predictions based on relevant prognostic factors
including age, disease severity and co-morbidity. Risk adjusted operative
mortality can be used as an objective measure of outcome for monitoring
performance within a centre or between centres.

5. Surgical Risk scores
• ACPGBI CRC Model - Association of Coloproctology of GB & I Colorectal Cancer Model for
mortality in colorectal cancer
• ACPGBI MBO Model - Association of Coloproctology of GB & I model for mortality
prediction in malignant bowel obstruction
• ACPGBI Lymph Node Harvesting Model - Association of Coloproctology of GB & I model for
determining the number of nodes that should be found in each resection
• St Mark's Lymph Node Positivity Model - calculates the probability of lymph node
metastases in patients undergoing local resection of rectal cancers and for patients whose
nodal harvest was not sufficient to adequately stage the rectal cancer.
• CCF CLC Model - The Cleveland Clinic Colorectal Laparoscopic Conversion Model for
prediction of conversion of lapararoscopic to open surgery in patients undergoing colonic
or rectal surgery for benign or malignant disease.
• CCF IPF Model - The Cleveland Clinic Ileal Pouch Failure Model for prediction of ileal pouch
failure in patients undergoing restorative proctocolectomy.
• CR-POSSUM - Used for predicting mortality in Colorectal Surgery (benign & malignant)
• P-POSSUM - Used for predicting mortality (& morbidity by POSSUM) in General Surgery
• O-POSSUM - Used for predicting mortality in Oesophagogastric Surgery
• Vascular-POSSUM - Used for predicting mortality in Vascular Surgery (all 4 models
available
• MUST screening tool (malnutrition)

6. calculate a mortality risk online for patients using the
ACPGBI Colorectal Cancer Model
• Calculate an ACP Score
• Choose a value in each category that matches your patient from the drop down
lists in both the physiological and operative parameters tables below. Default
values (the lowest score) are shown for each category. Simply submitting the form
as it is without changing the values (i.e. a young fit patient having a minor
operation) still gives a % risk for mortality. It is important to say in this model by
ticking the appropriate box whether or not the cancer was resected. The reason
for this is the value allocated to ASA status is dependent upon resection status.
• Parameters
– Age
– Cancer Resection Status cancer resected cancer NOT resected
– ASA Status C
– Cancer Staging :Duke’s
– Operative Urgency ;elective,urgent,emergency

7. • POSSUM:
• physiological and operative
severity scoring system for
enumeration of morbidity and
mortality

8. Calculate a CR-POSSUM Score
• Choose a value in each category that matches
your patient from the drop down lists in both
the physiological and operative parameters
tables below. Default values (the lowest score)
are shown for each category. Simply submitting
the form as it is without changing the values
(i.e. a young fit patient having a minor
operation) still gives a v.small % risk for
mortality. The more 'risky' the procedure the
more accurate is the predicted risk calculated
below.

9. CR POSSUM
• Physiological Parameters
– Age
– Cardiac :No-mild/moderate Carcdiac failure/severe CF
– Systolic BP
– Pulse Rate
– Haemoglobin
– Urea
• If calculating risk in a preoperative patient you will need to estimate the
parameters below. You can return and modify the parameters post-operatively
if required.
– Operative Parameters
– Operation Type
• Peritoneal Contamination
• Malignancy Status
• CEPOD

10. Calculate a P-POSSUM Score
Choose a value in each category that matches your patient from the drop
down lists in both the physiological and operative parameters tables
below. Default values (the lowest score) are shown for each category.
Simply submitting the form as it is without changing the values (i.e. a
young fit patient having a minor operation) still gives a % risk for
morbidity and mortality. This illustrates that even in the modified P-POSSUM
formula used in this application still overestimates risk in low risk
groups. The more 'risky' the procedure the more accurate is the predicted
risk calculated below.

11. P-POSSUM score
Physiological Parameters
Age
Cardiac
Respiratory
ECG
Systolic BP
Pulse Rate
Haemoglobin
WBC
Urea
Sodium
Potassium
GCS I
f calculating risk in a preoperative patient you will need to estimate the
parameters below. You can return and modify the parameters post-operatively
if required.
Operative Parameters :Operation Type /Number of procedures/ Operative
Blood Loss/ Peritoneal Contamination/ Malignancy Status/ CEPOD

12. Calculate an O-POSSUM Score
• Choose a value in each category that matches your patient from the drop
down lists in both the physiological and operative parameters tables
below. You must enter the patients actual age as well as selecting the
age range otherwise an error will occur. Default values (the lowest score)
are shown for each category. Simply submitting the form as it is without
changing the values (i.e. a young fit patient having a minor operation) still
gives a % risk for mortality.

13. O Possum score
• Physiological Parameters
– Age Range
– * BOTH FIELDS MUST BE COMPLETED
– Actual Age * BOTH FIELDS MUST BE COMPLETED
– Cardiac
– Respiratory
– ECG
– Systolic BP
– Pulse Rate
– Haemoglobin
– WBC
– Urea
– Sodium
– Potassium
– GCS
– If calculating risk in a preoperative patient you will need to estimate the parameters below.
You can return and modify the parameters post-operatively if required.
• Operative Parameters :Operation Type/ Malignancy Status/ CEPOD

15. Equazione di Possum(da Copeland)
• R1 rischio di mortalità
• R2:rischio di morbilità
• Una volta ottenuti i punteggi:
• - Ln (R1/1 - R1) = -7,04 + (0,13 x punteggio fisiologico) + (0,16 x
punteggio di gravità operatoria).
• - Ln (R2/1 - R2) = -5,91 + (0,16 x punteggio fisiologico) + (0,19 x
punteggio di gravità operatoria).

16. Equazioni di POSSUM
• R1:Rischio di mortalità
• R2:Rischio di morbilità:
• Una volta ottenuti i punteggi:
• R1=- Ln (R1/1 - R1) = -7,04 + (0,13 x punteggio
fisiologico) + (0,16 x punteggio di gravità op).
• R2=- Ln (R2/1 - R2) = -5,91 + (0,16 x punteggio
fisiológico) + (0,19 x punteggio di gravità op)

17. World J Surg Oncol. 2008 Apr 9;6:39. Application of Portsmouth
modification of physiological and operative severity scoring system
for enumeration of morbidity and mortality (P-POSSUM) in
pancreatic surgery. Tamijmarane A, Bhati CS, Mirza DF, Bramhall SR,
Mayer DA, Wigmore SJ, Buckels JA.
• BACKGROUND: Pancreatoduodenectomy (PD) is associated with high incidence of
morbidity and mortality. We have applied P-POSSUM in predicting the incidence of
outcome after PD to identify those who are at the highest risk of developing
complications. METHOD: A prospective database of 241 consecutive patients who had
PD from January 2002 to September 2005 was retrospectively updated and analysed. P-POSSUM
score was calculated for each patient and correlated with observed morbidity
and mortality. RESULTS: 30 days mortality was 7.8% and morbidity was 44.8%. Mean
physiological score was 16.07 +/- 3.30. Mean operative score was 13.67 +/- 3.42. Mean
operative score rose to 20.28 +/- 2.52 for the complex major operation (p < 0.001) with
2 fold increase in morbidity and 3.5 fold increase in mortality. For groups of patients
with a physiological score of (less than or equal to) 18, the O:P (observed to Predicted)
morbidity ratio was 1.3-1.4 and, with a physiological score of >18, the O:P ratio was
nearer to 1. Physiological score and white cell count were significant in a multivariate
model. CONCLUSION: P-POSSUM underestimated the mortality rate. While P-POSSUM
analysis gave a truer prediction of morbidity, underestimation of morbidity and
potential for systematic inaccuracy in prediction of complications at lower risk levels is a
significant issue for pancreatic surgery

18. Stratification of morbidity according to physiology score Horizontal lines
within boxes, boxes and error bars represent median, interquartile range and
range respectively. P < 0.001 (Kruskal Wallis Test).

19. Ding LA, Sun LQ, Chen SX, Qu LL, Xie DF. Modified
physiological and operative score for the enumeration of
mortality and morbidity risk assessment model in general
surgery. World J Gastroenterol 2007; 13(38): 5090-5095
• AIM: To establish a scoring system for predicting the incidence of postoperative complications and
mortality in general surgery based on the physiological and operative severity score for the enumeration
of mortality and morbidity (POSSUM), and to evaluate its effi cacy.
• METHODS: Eighty-four patients with postoperative complications or death and 172 patients without
postoperative complications, who underwent surgery in our department during the previous 2 years,
were retrospectively analyzed by logistic regression. Fifteen indexes were investigated including age,
cardiovascular function, respiratory function, blood test results, endocrine function, central nervous
system function, hepatic function, renal function, nutritional status, extent of operative trauma, and
course of anesthesia. Modifi ed POSSUM (M-POSSUM) was developed using significant risk factors with
its effi cacy evaluated.
• RESULTS: The significant risk factors were found to be age, cardiovascular function, respiratory
function, hepatic function, renal function, blood test results, endocrine function, nutritional status,
duration of operation, intraoperative blood loss, and course of anesthesia. These factors were all
included in the scoring system. There were signifi cant differences in the scores between the patients
with and without postoperative complications, between the patients died and survived with
complications, and between the patients died and survived without complications. The receiver
operating characteristic curves showed that the M-POSSUM could accurately predict postoperative
complications and mortality.
• CONCLUSION: M-POSSUM correlates well with postoperative complications and mortality, and is more
accurate than POSSUM

20. physiological and operative severity
score for the enumeration of mortality and morbidity
(POSSUM)
• POSSUM is limited by its somewhat subjective
nature and incomplete evaluation of cardiac
signs. We propose the modified POSSUM (M-POSSUM)
as a reasonable, practical and
objective scoring system that can be used
across a broad disease spectrum in general
surgery

22. M-POSSUM indice 0 1 2 3 4
età <60 60-69 70-79 >80
Sist circolatorio Normale:funz.cardiaca,PA,ECG Funz cardiaca grado 1:lieve
ipertens e anormalità
ECG,bradicardia o
tachic,sinoatriale,basso
voltaggio derivaz arti inf,BBB
Funz cardiaca grado 2:moderata
ipertens controllata da
terapia,extrasistoli atriale
occasionali
Funz.cardiaca grado 3:IM<3
mesi,ipertens moderata in
terapia,ritmi ectopici,modificaz
ST-T,fibrillaz.atriale.
Insufficienza cardiaca
seria,ins.cardiaca
acuta,malattia ipertensiva
Sist.respiratorio normale Fumo di vecchia
data,bronchite
cronica,asma,infezioni
respiratorie,strie polmonari
,ispessimenti
Modesta COPD,modesta
alteraz.funz.resp,modesto
enfisema
Moderata COPD,funz resp da
moderata a seriamente
anormale
Insufficienza respiratoria
Funz.epatica normale Storia di
epatite/cirrosi,bilirub
tot.<34,2 mmol/l
bilirub tot.34,2-51.3
mmol/l
bilirub tot.>51.3 mmol/l
Funz.renale normale BUN<10.1
mmol/lt,Creatinin.<170
mmol/l
BUN 10.1-15 mmol/lt,creat
170-300 mmol/l
Insuff renale in dialisi
Tratto gastrointestinale normale Storia di gastroenterite
cronica,ulcera peptica
ben controllata
Malattia gastrointest
attiva/emorragia/perforaz
di ulcera,m.di Crohn. attiva
Fistola intest.percutanea Sindr.intestino
corto,trapianto di
intestino
ematopoietico normale Piastrine /GB
lievemente diminuiti,HB
>85 gr/l
Malattia,come leucemia
,stabile;GB>14.5 *109/l
Mal.aplastica,sindr da
ipersplenismo,leucemia,e
cc.
endocrino normale Glicemia lievemente
aumentata,glucosio urinario
assente,ipertiroidismo e
ipotiroidsmo
trattati,acromegalia,gotta,mal
reumatoide
Glicemia lievemente
aumentata,glucosio urinario
presente,diabete controll da
terapia orale,ormonoterpia,gotta
attiva
Diabete instabile con terapia
orale
Nefropatia diabetica
Stato nutrizionale normale Malnutrizione lieve;albumina
30-35 gr/l,decremento di peso
<2.5 kg/m
Malnutrizione moderata;albumina
<30 gr/l,decremento di peso <2.5
-5 kg/m
cachessia
Glasgow Coma Score 15 12-14 9-11 = o <8
Ferita operatoria Minore/tempo operatorio < 2
h/emorragia<300 ml
Moderata/tempo operatorio 2-4
h/emorragia300-500 ml
Maggiore /tempo operatorio >4
h/emorragia>500
ml/escissionne di tumore
Maggiore/escissione > 3
organi/malattia tumorale non
resecabile l

23. M Possum quadro 1
indice 0 1 2 3 4
età <60 60-69 70-79 >80
Sist circolatorio Normale:funz.c
ardiaca,PA,ECG
Funz cardiaca
grado 1:lieve
ipertens e
anormalità
ECG,bradicardia
o
tachic,sinoatrial
e,basso
voltaggio
derivaz arti
inf,BBB
Funz cardiaca
grado
2:moderata
ipertens
controllata da
terapia,extrasis
toli atriale
occasionali
Funz.cardiaca
grado 3:IM<3
mesi,ipertens
moderata in
terapia,ritmi
ectopici,modific
az ST-T,
fibrillaz.atrial
e.
Insufficienza
cardiaca
seria,ins.cardiac
a
acuta,malattia
ipertensiva
Sist.respiratorio normale Fumo di
vecchia
data,bronchite
cronica,asma,in
fezioni
respiratorie,stri
e polmonari
,ispessimenti
Modesta
COPD,modesta
alteraz.funz.res
p,modesto
enfisema
Moderata
COPD,funz resp
da moderata a
seriamente
anormale
Insufficienza
respiratoria

24. M Possum quadro 2
0 1 2 3 4
Funz.epatica normale Storia di
epatite/cirrosi,
bilirub
tot.<34,2
mmol/l
bilirub
tot.34,2-51.3
mmol/l
bilirub
tot.>51.3
mmol/l
Funz.renale normale BUN<10.1
mmol/lt,Creati
nin.<170
mmol/l
BUN 10.1-15
mmol/lt,creat
170-300
mmol/l
Insuff renale in
dialisi
Tratto
gastrointesti
nale
normale Storia di
gastroenterite
cronica,ulcera
peptica ben
controllata
Malattia
gastrointest
attiva/emorrag
ia/perforaz di
ulcera,m.di
Crohn. attiva
Fistola
intest.percutan
ea
Sindr.intestino
corto,trapianto
di intestino

25. M Possum quadro 3
0 1 2 3 4
ematopoiet
ico
normale Piastrine /GB
lievemente
diminuiti,HB
>85 gr/l
Malattia,co
me
leucemia
,stabile;GB>1
4.5 *109/l
Mal.aplastica
,sindr da
ipersplenism
o,leucemia,e
cc.
endocrino normale Glicemia
lievemente
aumentata,gl
ucosio
urinario
assente,ipert
iroidismo e
ipotiroidsmo
trattati,acro
megalia,gott
a,mal
reumatoide
Glicemia
lievemente
aumentata,gl
ucosio
urinario
presente,dia
bete controll
da terapia
orale,ormon
oterpia,gotta
attiva
Diabete
instabile con
terapia orale
Nefropatia
diabetica

26. M Possum (quadro 4)
0 1 2 3 4
Stato
nutrizionale
normale Malnutrizione
lieve;albumina 30-
35
gr/l,decremento
di peso <2.5 kg/m
Malnutrizione
moderata;albumi
na <30
gr/l,decremento
di peso <2.5 -5
kg/m
cachessia
Glasgow
Coma Score
15 12-14 9-11 = o <8
Ferita
operatoria
Minore/tempo
operatorio < 2
h/emorragia<300
ml
Moderata/tempo
operatorio 2-4
h/emorragia300-
500 ml
Maggiore /tempo
operatorio >4
h/emorragia>500
ml/escissionne di
tumore maligno
Maggiore/escissio
ne > 3
organi/malattia
tumorale non
resecabile l
Decorso
anestetico
Aritmia/bassa PA
< 30 min
PA sempre
bassa,rianimazion
e
cardiopolmonare

27. Ding LA, Sun LQ, Chen SX, Qu LL, Xie DF. Modified
physiological and operative score for the enumeration of
mortality and morbidity risk assessment model in general
surgery. World J Gastroenterol 2007; 13(38): 5090-5095

28. Predictive formula of M POssum
• Logistic regression analysis yielded statistically signifi
cant equations for both morbidity and mortality.
• The morbidity equation was :
lnR/1-R = -7.287 + 0.765M-POSSUM (P =0.000)
• the mortality equation was:
lnR/1-R = -10.000 + 0.681M-POSSUM (P = 0.000).
The predictive accuracy of morbidity equation and
mortality equation was 83.6% and 94.1%, respectively

29. O-POSSUM Score
observed 30-day morbidity rate 58%
Obs. Mortality 12%
observed 1-year mortality 38% for males (mean age 79 years) and 29% for
females (mean age 84 years).
N Z Med J. 2006 May 19;119(1234):U1986. Comment in:
N Z Med J. 2006;119(1234):U1981. Audit of morbidity and mortality
following neck of femur fracture using the POSSUM scoring system.
Young W, Seigne R, Bright S, Gardner M

30. Malnutrition Universal Screening Tool (MUST)
‘MUST’ is a five-step screening tool to identify adults, who are malnourished, at risk of
malnutrition, or obese. It also includes management guidelines which can be used
to develop a care plan. The tool is being used both in hospitals and in the
community. It is easy to use and can be used by all care workers.
• Full details of this tool can be found at the following:
• http://www.bapen.org.uk/the-must.htm
• Calculate Risk
• Use the form below to estimate the risk of malnutrition. Please note that the
figures entered for weight must be in kilograms and the figure entered for height
must be in centimetres. Conversion charts for Imperial units can be found here
(opens in a new window).
• Parameters Current weight (Kg) /Current height (cms) /Previous healthy weight*
/Is the patient acutely ill and there has been or is likely to be no nutritional intake
for >5 days? /
• * This is the patients' weight when they were healthy, or the weight prior to any
unplanned weight loss in the last 3-6 months

31. Application of Portsmouth modification of physiological and operative severity scoring
system for enumeration of morbidity and mortality (P-POSSUM) in pancreatic surgery
Appou Tamijmarane*, Chandra S Bhati, Darius F Mirza, Simon R Bramhall,
David A Mayer, Stephen J Wigmore and John AC Buckels.World Journal of Surgical
Oncology • 2008, 6:39 doi:10.1186/1477-7819-6-39 Abstract Background: Pancreatoduodenectomy (PD) is associated with high incidence of
morbidity and mortality. We have applied P-POSSUM in predicting the incidence of outcome
after PD to identify those who are at the highest risk of developing complications.
• Method: A prospective database of 241 consecutive patients who had PD from January
2002 to September 2005 was retrospectively updated and analysed. P-POSSUM score was
calculated for each patient and correlated with observed morbidity and mortality.
• Results: 30 days mortality was 7.8% and morbidity was 44.8%. Mean physiological score
was 16.07 ± 3.30. Mean operative score was 13.67 ± 3.42. Mean operative score rose to
20.28 ± 2.52 for the complex major operation (p < 0.001) with 2 fold increase in morbidity
and 3.5 fold increase in mortality. For groups of patients with a physiological score of (less
than or equal to) 18, the O:P
• (observed to Predicted) morbidity ratio was 1.3–1.4 and, with a physiological score of >18,
the O:P ratio was nearer to 1. Physiological score and white cell count were significant in a
multivariate model.
• Conclusion: P-POSSUM underestimated the mortality rate. While P-POSSUM analysis gave
a truer prediction of morbidity, underestimation of morbidity and potential for systematic
inaccuracy in prediction of complications at lower risk levels is a significant issue for
pancreatic surgery.

32. E-PASS scoring
Estimation of physiologic ability
and surgical stress

33. • Estimation of Physiologic Ability and
Surgical Stress (E-PASS) scoring
system:
• E-PASS=a pre-operative risk score (PRS), a
surgical stress score (SSS), and a
comprehensive risk score (CRS), which is
calculated from the PRS and SSS.
• CRS=PRS+SSS
• E-PASS=K*CRS

34. equations of the E-PASS scoring
system
• The equations of the E-PASS scoring system are as follows (data from Haga et al1):
(1) Estimation of physiologic ability and surgical stress (E-PASS)
as a predictor of immediate outcome after elective
abdominal aortic aneurysm surgery

35. equations of the E-PASS scoring system are as follows (data from
Haga et al1):
• (1) PRS = -0.0686 + 0.00345X1 +0.323X2
+0.205X3
+0.153X4 +0.148X5 +0.0666X6,
where X1 is age; X2, the presence (1) or absence
(0) of severe heart disease; X3, the presence (1)
or absence (0) of severe pulmonary disease; X4,
the presence (1) or absence (0) of diabetes
mellitus; X5, the performance status index
(range, 0-4); and X6, the American Society of
Anesthesiologists' physiological status
classification (range, 1-5).

36. • (1) PRS = -0.0686 + 0.00345X1 +0.323X2
+0.205X3
+0.153X4 +0.148X5 +0.0666X6,
dove: X1 è etò, X2,la presenza (1) o assenza (0)
di malattia cardiaca severa; X3
la presenza (1) o
assenza (0)di malattia polmonare severa; X4, la
presenza (1) o assenza (0) di diabete mellitus;
X5, il performance status index (range, 0-4); X6,
la classificazione di stato fisico della American
Society of Anesthesiologists (ASA Ps) (range, 1-
5).

37. • Severe heart disease is defined as heart failure of New York Heart
Association class III or IV or severe arrhythmia requiring mechanical
support.
• Severe pulmonary disease is defined as any condition with a percentage
vital capacity of less than 60% and/or a percentage forced expiratory
volume in 1 second of less than 50%.
• Diabetes mellitus is defined according to the World Health Organization
criteria.
• Performance status index is defined by the Japanese Society for Cancer
Therapy.

38. SSS:surgical stress core
• (2) SSS = -0.342 + 0.0139X1 +0.0392X2 +0.352X3,
where X1 is blood loss (in grams) divided by
body weight (in kilograms); X2, the operating
time (in hours); and X3, the extent of the skin
incision (0 indicates a minor incision for
laparoscopic or thoracoscopic surgery,
including laparoscopic- or thoracoscopic-assisted
surgery; 1, laparotomy or
thoracotomy alone; and 2, laparotomy and
thoracotomy).
(

39. • 2) SSS = -0.342 + 0.0139X1 +0.0392X2 +0.352X3,
dove X1 è la perdita ematica (in grammi) diviso
per il peso corporeo (in kg); X2, tempo
operatorio ( h); X3, l’estensione della incisione
cutanea: (0 indica una incisione minore
laparoscopica o toracoscopica; 1, laparotomia
o toracototomia da sole ; 2, laparotomia e
toracotomia

40. comprehensive risk score (CRS)
• 3) CRS = -0.328 + (0.936 x PRS) + (0.976 x SSS).

41. Esempio di di EPass
• 70 anni
• Copd
• Iperteso
• Gastrect 5 h,perdite 800 ml stimate…….
• PRS = -0.0686 + 0.00345*70+0.323*0
+0.205*1 +0.153X4
+0.148*??X5 +0.0666*3,assumiamo X5=1…
• PRS=3,49
• SSS =0,4345
• CRS = -0.328 + (3,26) + (0,4240).=3,35 ,cioè mortalità
0-5%,morbilità 44%

42. Incidence of mortality and morbidity accordingto CRS. The graph appears to
demonstrate that patients in the ≥1.0 categoryare at particularly high risk
of mortality, and in the .5 to <1.0 and ≥1.0categories at particularly high risk
of morbidity. Bars show 95% confidence intervals Estimation of physiologic ability and
surgical stress (E-PASS) as a predictor of immediate outcome after elective abdominal aortic aneurysm
surgery

43. Estimation of physiologic ability and surgical stress (E-PASS) as a predictor of immediate outcome after
elective abdominal aortic aneurysm surgery

44. Br J Surg. 2007 Jun;94(6):717-21. Comment in:
Br J Surg. 2007 Oct;94(10):1308; author reply 1308-9. VBHOM, a data economic
model for predicting the outcome after open abdominal aortic aneurysm surgery.
Tang T, Walsh SR, Prytherch DR, Lees T, Varty K, Boyle JR;
Audit Research Committee of the Vascular Society of Great Britain and Ireland.
• BACKGROUND: Vascular Biochemistry and Haematology Outcome Models (VBHOM)
adopted the approach of using a minimum data set to model outcome. This study
aimed to test such a model on a cohort of patients undergoing open elective and non-elective
abdominal aortic aneurysm (AAA) repair. METHODS: A binary logistic
regression model of risk of in-hospital mortality was built from the 2002-2004
submission to the UK National Vascular Database (NVD) (2718 patients). The subset of
NVD data items used comprised serum levels of urea, sodium and potassium,
haemoglobin, white cell count, sex, age and mode of admission. The model was applied
prospectively using Hosmer-Lemeshow methodology to a test data set from the
Cambridge Vascular Unit. RESULTS: The validation set contained 327 patients, of whom
208 had elective AAA repair and 119 had emergency repair of a ruptured AAA.
Outcome following elective and non-elective AAA repair could be described accurately
using the same model. The overall mean predicted risk of death was 14.13 per cent,
and 48 deaths were predicted. The actual number of deaths was 53 (chi(2) = 8.40, 10
d.f., P = 0.590; no evidence of lack of fit). The model also demonstrated good
discrimination (c-index = 0.852). CONCLUSION: The VBHOM approach has the
advantage of using simple, objective clinical data that are easy to collect routinely. The
VBHOM data items potentially allow prediction of risk in an individual patient before
aneurysm surgery. (c) 2007 British Journal of

45. Vascular Biochemistry and Haematology Outcome
Models (VBHOM)
• serum levels of:
– urea,
–sodium and potassium,
–haemoglobin,
–white cell count,
–sex,
–age
– mode of admission.

46. Eur J Vasc Endovasc Surg. 2007 Nov;34(5):505-13. Epub 2007 Sep 14. Links
Comment in: Eur J Vasc Endovasc Surg. 2007 Nov;34(5):497-8. Comparison of risk-scoring
methods in predicting the immediate outcome after elective open abdominal aortic
aneurysm surgery.
Tang TY, Walsh SR, Fanshawe TR, Seppi V, Sadat U, Hayes PD, Varty K, Gaunt ME, Boyle
JR.
• BACKGROUND & OBJECTIVES: The aim of this study was to apply three simple risk - scoring
systems to prospectively collected data on all elective open Abdominal Aortic Aneurysm (AAA)
operations in the Cambridge Academic Vascular Unit over a 6 - year period (January 1998 to
January 2004), to compare their predictive values and to evaluate their validity with respect to
prediction of mortality and post-operative complications. METHODS: 204 patients underwent
elective open infra-renal AAA repair. Data were prospectively collected and risk assessment scores
were calculated for mortality and morbidity according to the Glasgow Aneurysm Score (GAS),
VBHOM (Vascular Biochemistry and Haematology Outcome Models) and Estimation of Physiologic
Ability and Surgical Stress (E-PASS). RESULTS: The mortality rate was 6.3% (13/204) and 59%
(121/204) experienced a post-operative complication (30-day outcome). For GAS, VBHOM and E-PASS
the receiver operating characteristics (ROC) curve analysis for prediction of in-hospital
mortality showed area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.76 to 0.92;
p<0.0001), 0.82 (95% CI, 0.68 to 0.95; p=0.0001) and 0.92 (95% CI, 0.87 to 0.97; p<0.0001)
respectively. There were also significant correlations between post-operative complications and
length of hospital stay and each of the three scores, but the correlation was substantially higher in
the case of E-PASS. CONCLUSIONS: All three scoring systems accurately predicted the risk of
mortality and morbidity in patients undergoing elective open AAA repair. Among these, E-PASS
seemed to be the most accurate predictor in this patient population.

47. Eur J Vasc Endovasc Surg. 2008 Oct 13. [Epub ahead of print] Links
Predicting Risk in Elective Abdominal Aortic Aneurysm Repair: A
Systematic Review of Current Evidence.
Patterson BO, Holt PJ, Hinchliffe R, Loftus IM, Thompson MM
• . OBJECTIVE: To examine and compare existing pre-operative risk prediction methods for
elective abdominal aortic aneurysm (AAA) repair. DESIGN: Systematic review. METHODS:
Medline, EMBASE and the Cochrane library were searched for articles that related to risk
prediction models used for elective AAA repair. RESULTS: 680 abstracts were reviewed
and after exclusions 28 articles encompassing 10 risk models were identified. The most
frequently studied of these were the Glasgow Aneurysm Score (GAS), the Physiological
and Operative Severity Score for enUmeration of Mortality (POSSUM) predictor equation
and the Vascular Biochemistry and Haematology Outcome Model (VBHOM). All models
had strengths and weaknesses and some had unique features which were identified and
discussed. CONCLUSION: The GAS appeared to be the most useful and consistently
validated score at present for open repair. Other systems were either not validated fully
or were not consistently accurate. Some had significant drawbacks which appeared to
severely limit their clinical application. Recent work has shown that no scores
consistently predicted the risk associated with endovascular aneurysm repair (EVAR). Pre-operative
risk stratification is a vital component of modern surgical practice, and we
propose the need for a comprehensive new risk scoring method for AAA repair
incorporating anatomical and physiological data.

48. Surgical Apgar score

49. Surgical Apgar Score
Regenbogen, Scott E. MD, MPH *+; Lancaster, R Todd MD *+; Lipsitz, Stuart R. ScD ++; Greenberg, Caprice
C. MD, MPH ++; Hutter, Matthew M. MD, MPH +; Gawande, Atul A. MD, MPH *++ Does the Surgical Apgar
Score Measure Intraoperative Performance? Annals of Surgery. 248(2):320-328, August 2008.
• lowest heart rate
• lowest mean arterial pressure
• estimated blood loss
• A score built from these 3 predictors has proved
strongly predictive of the risk of major postoperative
complications and death in general and vascular surgery.
• The score was thus developed using these 3 variables, and their beta coefficients
were used to weight the points allocated to each variable in a 10-point score
(Table 1).

50. Regenbogen, Scott E. MD, MPH *+; Lancaster, R Todd MD *+; Lipsitz, Stuart R. ScD ++;
Greenberg, Caprice C. MD, MPH ++; Hutter, Matthew M. MD, MPH +; Gawande, Atul
A. MD, MPH *++ Does the Surgical Apgar Score Measure Intraoperative Performance?
Annals of Surgery. 248(2):320-328, August 2008.

52. Regenbogen, Scott E. MD, MPH *+; Lancaster, R Todd MD *+; Lipsitz, Stuart R. ScD ++;
Greenberg, Caprice C. MD, MPH ++; Hutter, Matthew M. MD, MPH +; Gawande, Atul
A. MD, MPH *++ Does the Surgical Apgar Score Measure Intraoperative Performance?
Annals of Surgery. 248(2):320-328, August 2008.

53. Regenbogen, Scott E. MD, MPH *+; Lancaster, R Todd MD *+; Lipsitz, Stuart R. ScD ++;
Greenberg, Caprice C. MD, MPH ++; Hutter, Matthew M. MD, MPH +; Gawande, Atul
A. MD, MPH *++ Does the Surgical Apgar Score Measure Intraoperative Performance?
Annals of Surgery. 248(2):320-328, August 2008.

54. Regenbogen, Scott E. MD, MPH *+; Lancaster, R Todd MD *+; Lipsitz, Stuart R. ScD ++;
Greenberg, Caprice C. MD, MPH ++; Hutter, Matthew M. MD, MPH +; Gawande, Atul
A. MD, MPH *++ Does the Surgical Apgar Score Measure Intraoperative Performance?
Annals of Surgery. 248(2):320-328, August 2008.

55. Frequenza delle complicanze a seconda del Surgical Apgar
Score
Regenbogen, Scott E. MD, MPH *+; Lancaster, R Todd MD *+; Lipsitz, Stuart R. ScD ++; Greenberg, Caprice C.
MD, MPH ++; Hutter, Matthew M. MD, MPH +; Gawande, Atul A. MD, MPH *++ Does the Surgical Apgar
Score Measure Intraoperative Performance? Annals of Surgery. 248(2):320-328, August 2008.
80
70
60
50
40
30
20
10
0
Ko maggiori
0-2
3-4
5-6
7-8
9-10
%

56. Apache III
• the APACHE III is used to produce an equation predicting hospital mortality
after the first day of ICU treatment. There are 4 components: age, major
disease category (reason for ICU admission), acute (current) physiology, and
prior site of healthcare (eg, hospital floor, emergency room, etc.). The
physiologic variables require scoring of the following vital sign and laboratory
abnormalities: pulse rate, mean blood pressure, temperature, respiratory rate,
PaO2/P (A-a) O2, hematocrit, white blood cell count, creatinine, urine output,
blood urea nitrogen, serum sodium, albumin, bilirubin, glucose, acid-base
status, and neurologic status.
• The last 2 physiologic parameters are hybrid values specific to APACHE III.[3] It is
important to note that an additional scoring variable must be used to update
the APACHE III score based on changes in the patient's physiologic status.

57. references
• Knaus WA, Draper EA, Wagner DP it al. APACHE II: A severity of disease
classification system. Crit Care Med. 1985;13:818-829.
• Le Gall Jr, Lemeshow S, Saulnier F. A new Simplified Acute Physiology
Score (SAPS II) based on a European/North American multicenter study.
JAMA. 1993;270:2957-2963.
• Knaus WA, Wagner DP, Draper EA et al. The APACHE III Prognostic System.
Chest. 1991;100:1619-1636.
• Beck DH, Taylor BL, Millar B, et al. Prediction of outcome from intensive
care: A prospective cohort study comparing Acute Physiology and Chronic
Health Evaluation II and III prognostic systems in a United Kingdom
intensive care unit. Crit Care Med. 1997;25:9-15.

61. Apache II score

62. Saps II score

63. Sofa score

64. Comparison of the performance of SAPS II, SAPS 3, APACHE II, and their
customized prognostic models in a surgical intensive care unit
Y. Sakr1, C. Krauss1, A. C. K. B. Amaral2, A. Réa-Neto2, M. Specht1, K. Reinhart1 and
G. Marx1
• We compared the performance of SAPS 3 with SAPS II and the Acute Physiology and Chronic
Health Evaluation (APACHE) II score in surgical ICU patients.
• Methods: Prospectively collected data from all patients admitted to a German university
hospital postoperative ICU between August 2004 and December 2005 were analysed. The
probability of ICU mortality was calculated for SAPS II, APACHE II, adjusted APACHE II (adj-
APACHE II), SAPS 3, and SAPS 3 customized for Europe [C-SAPS3 (Eu)] using standard
formulas. To improve calibration of the prognostic models, a first-level customization was
performed, using logistic regression on the original scores, and the corresponding probability
of ICU death was calculated for the customized scores (C-SAPS II, C-SAPS 3, and C-APACHE II).
• Results: The study included 1851 patients. Hospital mortality was 9%. Hosmer and Lemeshow
statistics showed poor calibration for SAPS II, APACHE II, adj-APACHE II, SAPS 3, and C-SAPS 3
(Eu), but good calibration for C-SAPS II, C-APACHE II, and C-SAPS 3. Discrimination was
generally good for all models [area under the receiver operating characteristic curve ranged
from 0.78 (C-APACHE II) to 0.89 (C-SAPS 3)]. The C-SAPS 3 score appeared to have the best
calibration curve on visual inspection.
• Conclusions: In this group of surgical ICU patients, the performance of SAPS 3 was similar to
that of APACHE II and SAPS II. Customization improved the calibration of all prognostic
models.

65. Comparison of Apache II,Saps and Sofa scores