ABSTRACT
Objective: Systolic blood pressure, diastolic blood pressure, and the mean arterial blood pressure are useful markers that can predict morbidity and mortality among critically ill patients and may be used to predict the prognosis of patients with septic shock. Our objective was to compare the ability of percentage variations of the systolic, diastolic, and mean arterial pressures (%SBPvar, %MAPvar, and %DBPvar) to predict the primary outcome of overall 28-day intensive care unit mortality, and the secondary outcomes of early mortality (≤14 days), late mortality (>14 days), and intensive care unit length of stay.
Methods: We performed a retrospective analysis of 163 patients admitted to our adult critical care unit between April 2017 and Sep 2018 who met the inclusion criteria of availability of all required data and who survived or discharged before completing at least 1 week of admission. Independent T-test, Mann Whitney U test, and chi square test were used to express all patient variables. A receiver operating characteristic curve (ROC) followed by sensitivity analysis was generated to determine the predictive performances, and the optimal cut-off values for three propose prognosticators.
Results: The mean overall age was 58.37±9.96 years. 112 subjects (68.71%) were male and 51 subjects (31.29%) were female. The overall 28-day, early, and late ICU mortality rate were 39.26% (64 patients), 9.82% (16 patients), and 29.45% (48 patients), respectively. Our studied three prognosticators of %SBPvar, %MAPvar, and %DBPvar were significantly lower in survivors in compared with non survivors (8.96%±0.26%, 16.34%±0.65%, and 22.52%±1.10% versus 11.04%±4.61%, 21.17%±7.54%, and 35.18%±29.37%, respectively). The area under curve of ROC %MAPvar (0.818) was significantly greater than those of %SBPvar (0.769) and %DBPvar (0.265).
Conclusion: In summary, %MAPvar and %SBPvar prognosticators were an effective, no-cost bedside modalities, and discriminative prognosticators with realistic, reliable, and readily available red flag bedside assessment tools which had high sensitivity, performance, and accuracy to predict early, late, and overall 28-day ICU mortality in septic mechanically ventilated critically ill patients who were receiving norepinephrine as a vasopressor.
Key words: Blood pressure variations, Critically ill patients, Mortality, Norepinephrine, Septic shock.
JRMS December 2020; 27(3): 10.12816/0057183
Introduction
Systolic blood pressure (SBP), diastolic blood pressure (DBP), and the mean arterial blood pressure (MAP) are useful markers that can predict morbidity and mortality among intensive care unit (ICU)
Admitted patients and may be used to
predict the prognosis of patients with septic shock. Sepsis is a complex
syndrome caused by the body’s systemic response to an infection with a major
cause of high treatment cost, single or multiple organ dysfunctions.[1-4] C-reactive protein (CRP) is also a useful positive
acute-phase reactant marker that can predict morbidity and mortality among
critically ill patients. [5,6] However, the results of CRP and other severity
indices of sepsis may not be immediately available upon request, potentially
delaying effective dynamic risk stratification and goal directed management in
these unstable studied cohort. MAP which defined as 1/3 SBP + 2/3 DBP is
a readily and affordable attained comprehensive parameter that combines two
physiological pressure parameters (SBP and DBP) into a single parameter and
previously has been shown to stratify and served as an early warning
prognosticator of high risk septic patients from various aetiologies when
compared to SBP and DBP.[7-10] Having reliable indicators and
markers that would help prognosticate the survival of these patients is
invaluable and would subsequently assist in the course of effective treatment.[11,12]
Our objective was to compare the ability of %DBP, %SBP, and %MAP variations to
predict the primary outcome of overall 28-day ICU mortality, and the secondary
outcomes of early mortality (≤14 days), late mortality (>14 days), and ICU length
of stay (LOS). Also, our objective was to determine the
optimal cut-off point, sensitivity (TPR), specificity (TNR), Youden’s index
(YI), positive and negative predictive values (PPV and NPV), and accuracy
index (AI), of the three tested prognosticators.
Methods
This was a single-centre observational
retrospective study conducted in the department of adult ICU of King Hussein
Medical Hospital (KHMH) at Royal Medical Services (RMS) in Jordan. This study
was approved by our Institutional Review Board (IRB), and a requirement for
consent was waived owing to its retrospective design. This study included a
cohort of 913 critically ill patients admitted to our adult ICU via the
emergency department (ED) or via other hospital wards with any medical or
surgical problems. After excluded all patients who were died or discharged
before completed at least 1 week after admission and included all critically
ill patients who their anthropometrics, diagnostics, demographics,
hemodynamics, nutritional indices, and all required laboratory data were known,
163 critically ill patients were finally included in our study. Flow chart of
critically ill patient’s selection and data collection process is fully
illustrated in Figure 1.
All patient continuous variables were
expressed as mean± standard deviation by using the independent samples T-test
while categorical and ordinal variables were expressed as numbers with
percentages by using the chi square test or as median (interquartile range) by
using the Mann-Whitney U test, respectively. Analysis values were compared for
the two tested groups (survivors vs. non-survivors) and the non-survival group
was further analysed after being divided into 2 subgroups, early (≤14 days) and
late (>14 days) mortality. A receiver operating
characteristic (ROC) curve followed by sensitivity analysis was used to
determine the area under the ROC curves (AUROCs), predictive performances, and
the optimal cut-off values for %SBPvar, %MAPvar, and %DBPvar,
YI, TPR, TNR, PPV, NPV, and AI were also calculated. Statistical analyses
were performed using IBM SPSS ver. 25 (IBM Corp., Armonk, NY, USA) and P-values
≤0.05 were considered statistically significant.

Result
The mean overall age was 58.37±9.96 years. 112
subjects (68.71%) were male and 51 subjects (31.29%) were female. The overall
28-day, early, and late ICU mortality rate were 39.26% (64 patients), 9.82% (16 patients), and 29.45% (48 patients),
respectively. 28-day ICU mortality was
significantly higher in medically than surgically admitted patients (85.94% (55 medically patients) versus 14.06% (9 surgically patients),
respectively). Baseline pre-ICU admission
days and number of co-morbidities >1 were also significantly higher in
non-survivors than survivors (7.42±4.57 days versus 2.23±1.06 days and 65.63% (42 subjects) versus 47.47% (47 subjects), respectively). Despite baseline albumin level (ALB1)
was significantly higher in non-survivors (2.94±0.39 g/dl) than survivors (2.63±0.20 g/dl), survivors had significantly higher
average administered human albumin (H.ALB) doses and nutritional protein
density (PD) inputs and significantly lower CRP (18.89±3.16 g/day and 3.72±0.74 g/100 Cal
and 28.38±14.38 mg/dl, respectively) than non-survivors (14.06±6.09 g/day and 3.50±0.36 g/100 Cal
and 43.09±19.28 mg/dl, respectively) which ultimately resulted in significantly higher
average ALB during ICU admission in survivors (2.87±0.12 g/dl) than in non survivors
(2.57±0.13 g/dl).
The ICU and overall hospital LOS were also significantly lower in survivors non
survivors (9.23±1.06 days and 11.46±2.12
days versus 17.30±4.14 days and 24.72±1.98
days, respectively).
Table I: Demographics
and anthropometrics comparison of study’s critically ill patients.
|
Variables
|
Total
(N=163)
|
Survivors
(N=99 )
|
Non-survivors
(N=64)
|
P-Value
|
Early
Mortality
(≤14
days)
(N=16)
|
Late
Mortality (>14 days)
(N=48)
|
Age (Yrs)
|
58.37±9.96
|
58.55±9.948
|
58.09±10.053
|
0.92
(NS)
|
62.31±11.12
|
56.69±9.38
|
Gender
|
Male
|
112 (68.71%)
|
67 (67.68%)
|
45 (70.31%)
|
0.79
(NS)
|
11 (68.75%)
|
34 (70.83%)
|
Female
|
51 (31.29%)
|
32 (32.32%)
|
19 (29.69%)
|
5 (31.25%)
|
14 (29.17%)
|
Day(s)
Pre-ICU admission (day(s))
|
4.27±3.91
|
2.23±1.06
|
7.42±4.57
|
0.00
(S)
|
13.31±5.89
|
5.46±1.10
|
ICU Stay
day(s)
|
12.40±4.79
|
9.23±1.06
|
17.30±4.14
|
0.00
(S)
|
10.56±1.97
|
19.54±1.10
|
Hospital
Stay day(s)
|
16.67±6.81
|
11.46±2.12
|
24.72±1.98
|
0.00
(S)
|
23.87±3.93
|
25.00±0.00
|
Number of
comorbidities
|
0, 1
|
74 (45.39%)
|
52 (52.53%)
|
22 (34.38%)
|
0.03
(NS)
|
3 (18.75%)
|
19 (39.58%)
|
2 , 3, 4+
|
89 (54.60%))
|
47 (47.47%)
|
42 (65.63%)
|
13 (81.25%)
|
29 (60.42%)
|
Admission
class
|
Medical
|
105 (64.42%)
|
|