Fact-checked by Grok 2 weeks ago

SAPS II

The Simplified Acute Physiology Score II (SAPS II) is a severity-of-illness scoring system designed to predict in-hospital mortality risk for adult patients in intensive care units (ICUs), based on data collected during the first 24 hours of admission. It incorporates 17 variables—comprising 12 physiological parameters, patient age, type of ICU admission, and three indicators of underlying chronic diseases—to generate a total score ranging from 0 to 163, which is then converted via into a probability of . Unlike diagnosis-specific models, SAPS II operates independently of the patient's primary condition, making it applicable across diverse medical and surgical ICU populations. Developed in 1993 through a multinational collaborative involving 13,152 consecutive admissions to 137 adult ICUs across 12 countries (nine in and three in ), SAPS II was derived from a developmental of 8,549 patients and validated on 4,603 others, excluding those under 18 years, burn victims, coronary care patients, and post-cardiac surgery cases. The physiological variables include assessments of (such as , systolic , body temperature), status, values (including or , white count, serum potassium, sodium, bicarbonate, and ), urine output, level of consciousness via the , and oxygenation (PaO₂ or arterial oxygen tension relative to inspired oxygen fraction). contributes up to 17 points, admission type (medical, scheduled surgical, or unscheduled surgical) adds further weighting, and chronic comorbidities—specifically acquired immunodeficiency syndrome, metastatic cancer, and hematologic malignancy—account for up to 30 points in total. The model's predictive accuracy was demonstrated by strong discrimination, with area under the receiver operating characteristic curve (AUC) values of 0.88 in the developmental sample and 0.86 in the validation sample, alongside satisfactory calibration via Lemeshow-Hosmer goodness-of-fit tests (P = 0.883 and P = 0.104, respectively). Intended to simplify and improve upon its predecessor (SAPS I) for broader ICU benchmarking, SAPS II facilitates standardized mortality calculations to evaluate ICU and , though subsequent studies have noted potential needs for recalibration in contemporary settings due to evolving patient demographics and care practices. Despite the advent of updated systems like SAPS 3 in 2005, SAPS II remains a foundational and frequently referenced tool in critical care research and clinical auditing worldwide.

Introduction

Definition and Purpose

The Simplified Acute Physiology Score II (SAPS II) is a standardized, point-based severity-of-illness classification system developed for assessing acute physiological derangement in adult patients admitted to intensive care units (ICUs). It targets medical and surgical patients aged 18 years and older, excluding those from burn units, coronary care units, or immediately post-cardiac surgery, and relies on collected within the first hours of ICU admission to ensure timely evaluation. Unlike organ failure scores such as the Sequential Organ Failure Assessment (SOFA), which emphasize dysfunction in specific organs, SAPS II provides a broader measure of overall illness severity to support clinical decision-making. The primary purpose of SAPS II is to estimate mortality at the population or group level, enabling comparisons of patient outcomes across ICUs, of unit performance, and optimization of , rather than predicting outcomes for individual patients. This approach avoids the need for specifying a primary , making it versatile for diverse ICU populations and promoting its use in quality improvement initiatives. By quantifying severity through a simplified set of variables, the score facilitates manual calculation on paper, enhancing its practicality in resource-limited settings without reliance on complex software. SAPS II generates a total score ranging from 0 to 163 points, where higher values correspond to increasing predicted mortality, from nearly 0% for low scores to over 90% for the highest scores, derived from a model validated on multinational ICU data. This scoring framework, informed by a large of over 13,000 patients from 137 ICUs across 12 countries, underscores its role as a reliable tool for aggregate in critical care.

Historical Development

The Simplified Acute Physiology Score (SAPS) was first introduced in by Jean-Roger Le Gall and colleagues as a straightforward to assess ICU severity using 14 clinical and variables, aiming to facilitate comparisons across units without complex computations. However, SAPS I demonstrated limitations in discriminatory power due to its reliance on a smaller, less diverse , prompting the need for an updated model amid the surge in ICU research that emphasized standardized, internationally applicable tools for outcome prediction and . In response, SAPS II was developed in 1993 by Le Gall, Stanley Lemeshow, and Fabienne Saulnier as an evolution of the original, incorporating 17 variables to enhance predictive accuracy while prioritizing simplicity over more cumbersome systems like , which required diagnostic specificity and often computer support. The score was derived from a multinational database encompassing 13,152 patients across 137 adult medical and surgical ICUs in 12 countries, primarily in and , collected over six months in 1991 and 1992 to ensure broad applicability in heterogeneous settings. This design focused on ease of manual calculation using readily available data, such as 12 physiological measurements, age, type of admission, and three underlying disease factors, without mandating a primary . The seminal validation study, published in the Journal of the American Medical Association, reported strong performance with an area under the curve of 0.88 in the developmental and 0.86 in the validation for hospital mortality prediction, alongside good calibration (Hosmer-Lemeshow goodness-of-fit p=0.883 and p=0.104, respectively). Subsequent minor adaptations included a 2005 recalibration by Le Gall and team, which expanded the model with additional variables for better local fit in ICUs while preserving the core structure, addressing observed calibration drift without overhauling the foundational variables or logistic equation. No major revisions to SAPS II's framework have occurred since, maintaining its role as a for ICU severity .

Components

Physiological Variables

The physiological variables in the SAPS II score consist of 12 measurements that quantify acute derangements across multiple systems, providing an of illness severity in ICU patients. These variables were selected for their predictive value in mortality risk estimation, drawing from a large multicenter of over 13,000 patients, and emphasize parameters that are universally available without reliance on diagnostic or advanced invasive . By capturing abnormalities in , neurological status, respiratory function, renal output, and balance, they enable a comprehensive yet simplified evaluation of acute . Assessment of these variables uses the worst recorded values within the first 24 hours of ICU admission, a designed to reflect the peak intensity of physiological during the critical initial phase. Points are allocated based on predefined ranges for each variable, with escalating scores for greater deviations from normal, allowing the component to contribute up to 116 points in total and highlighting multi-system involvement in critical illness. This time-bound, worst-value approach enhances the score's sensitivity to transient but severe abnormalities common in ICU settings. Key unique aspects include the focus on routinely obtainable data, such as bedside vital signs and basic labs, to ensure feasibility across diverse healthcare environments. The respiratory variables distinguish between ventilation status and oxygenation: mechanical ventilation is scored separately from the oxygenation metric, which adjusts based on whether the patient is ventilated. The variables are:
  • Heart rate: Measured in beats per minute (bpm), with points assigned based on ranges: 11 points for <40 bpm, 2 points for 40-69 bpm, 0 points for 70-119 bpm, 4 points for 120-159 bpm, 7 points for ≥160 bpm, capturing cardiovascular instability from extreme bradycardia or tachycardia that signals autonomic dysregulation or shock.
  • Systolic blood pressure: Recorded in mmHg, scored 0 to 13 points: 13 points for <70 mmHg, 5 points for 70-99 mmHg, 0 points for 100-199 mmHg, 2 points for ≥200 mmHg, reflecting hemodynamic compromise such as hypotension in sepsis or hypertension in organ stress.
  • Body temperature: Assessed in °C, with 3 points if >38.4 °C; 0 points otherwise, indicating hyperthermia due to infection or other causes.
  • Glasgow Coma Scale (GCS): Points based on worst eye, verbal, and motor responses summed (3-15): 0 points for 13-15, 5 points for 12, 6 points for 11, 7 points for 10-9, 10 points for 8-7, 13 points for 6, 15 points for 5, 26 points for 3-4, evaluating neurological impairment from trauma, metabolic encephalopathy, or sedation effects.
  • Mechanical ventilation or CPAP: 11 points if present; 0 points otherwise, assessing the need for respiratory support as a marker of acute lung injury or failure.
  • PaO₂/FiO₂ ratio (for ventilated patients) or PaO₂ (for non-ventilated): 0 points if ≥500 mmHg (or PaO₂ ≥100 mmHg), 4 points if 200-<500 mmHg (or PaO₂ 60-<100 mmHg), 9 points if 100-<200 mmHg, 11 points if <100 mmHg (or PaO₂ <60 mmHg), quantifying oxygenation impairment.
  • Urinary output: Measured in mL over 24 hours, 0 points if ≥1000 mL, 6 points if 500-999 mL, 11 points if <500 mL, signaling renal hypoperfusion or acute kidney injury in hypovolemic or septic states.
  • Blood urea nitrogen (BUN) or urea: BUN in mg/dL or urea in mmol/L, 0 points if <28 mg/dL BUN (or <10 mmol/L urea), 6 points if 28-83 mg/dL (or 10-28 mmol/L), 10 points if ≥84 mg/dL (or ≥29 mmol/L), indicating azotemia from prerenal, renal, or postrenal causes.
  • White blood cell count (WBC): In ×10⁹/L, 12 points if <1 ×10⁹/L, 0 points if 1-29.9 ×10⁹/L, 3 points if ≥30 ×10⁹/L, detecting infection, inflammation, or bone marrow suppression.
  • Serum bicarbonate: In mEq/L, 6 points if <15 mEq/L, 3 points if 15-19 mEq/L, 0 points if ≥20 mEq/L, reflecting metabolic acidosis common in shock, renal failure, or tissue hypoperfusion.
  • Serum potassium: In mEq/L, 5 points if <2.5 mEq/L, 0 points if 2.5-4.9 mEq/L, 3 points if ≥5 mEq/L, identifying electrolyte imbalances from renal dysfunction, acidosis, or medication effects.
  • Serum sodium: In mEq/L, 5 points if <125 mEq/L, 0 points if 125-144 mEq/L, 1 point if 145-154 mEq/L, 5 points if ≥155 mEq/L, capturing dysnatremias due to fluid shifts, SIADH, or diabetes insipidus in critical illness.
These physiological metrics integrate with patient-specific factors to yield the overall SAPS II score for mortality .

Patient-Specific Factors

The patient-specific factors in the SAPS II scoring system incorporate characteristics that influence mortality risk independently of acute physiological derangements, including , type of admission to the ICU, and conditions. These elements are evaluated using data available at the time of ICU admission and contribute up to a maximum of 43 points to the total score, helping to adjust predictions for inherent vulnerabilities in diverse populations. Age is scored based on predefined brackets to reflect the heightened vulnerability to critical illness with advancing years, ranging from 0 points for patients 40 years or younger to 18 points for those 80 years or older. For instance, patients aged 40-59 years receive 7 points, those aged 60-69 years receive 12 points, while those aged 70-74 years are assigned 15 points, acknowledging the cumulative impact of age-related physiological decline on outcomes. This component underscores how older age correlates with reduced physiological reserve and higher mortality in ICU settings. The type of admission accounts for the context and urgency of ICU entry, assigning 0 points for scheduled surgical admissions (where was planned at least 24 hours prior), 6 points for medical admissions (no within the preceding week), and 8 points for unscheduled surgical admissions ( scheduled less than 24 hours before ICU ). This differentiation captures differences in preoperative optimization and acuity, with unscheduled cases often involving greater instability. Chronic health status evaluates pre-existing comorbidities that predispose patients to poorer outcomes, scored only if the condition was present before ICU admission and remains active or recently treated (e.g., malignancies treated within the previous 5 years). No points are given for absence of such conditions, while specific high-impact diseases receive targeted scores: 9 points for metastatic cancer (confirmed by , , or ), 10 points for hematologic (such as , , or ), and 17 points for AIDS (defined as HIV-positive status with complications like , , or ). If multiple chronic conditions are present, only the highest-scoring one is used to avoid double-counting. These weights prioritize severe, life-limiting diseases that elevate baseline risk without overlapping with acute variables. Collectively, these patient-specific factors address pre-ICU risks not reflected in physiological measurements, enhancing the equity and accuracy of mortality predictions across , elective surgical, and emergency surgical cohorts. When combined with physiological variables, they form the basis for the total SAPS II score.

Calculation

Point Assignment

The SAPS II raw score is computed by summing points assigned to 17 variables: 12 physiological measurements, , type of ICU admission, and status. The physiological variables contribute up to 116 points in total, up to 18 points, admission type up to 8 points, and status up to 17 points, yielding a possible total score ranging from 0 to 163. Higher total scores reflect greater illness severity, with the system's design emphasizing simplicity through integer points and predefined severity bands that avoid decimal calculations or complex weighting. Data collection for the SAPS II occurs during the first 24 hours following ICU admission (or readmission, treated as a separate event requiring recalculation of the full score). For the 12 physiological variables—heart rate, systolic blood pressure, body temperature, Glasgow Coma Scale score, oxygenation (PaO₂ or PaO₂/FiO₂ ratio), urinary output, blood urea nitrogen or serum creatinine, white blood cell count, serum potassium, serum sodium, serum bicarbonate, and serum bilirubin—the worst recorded value (either the highest or lowest, depending on the variable) within this period is used to assign points based on established severity bands. No additional weighting is applied beyond these bands, promoting ease of manual computation on paper in resource-limited settings. Points for age are assigned according to the patient's age at their last birthday: 0 points for <40 years, 7 points for 40–59 years, 12 points for 60–69 years, 15 points for 70–74 years, 16 points for 75–79 years, and 18 points for ≥80 years. Admission type contributes 6 points for medical admissions, 0 points for scheduled surgical admissions, and 8 points for unscheduled surgical admissions. Chronic health status adds 0 points if none of the specified conditions (AIDS, metastatic cancer, or hematologic malignancy) are present prior to admission; 9 points for metastatic cancer; 10 points for hematologic malignancy; 17 points for AIDS. If the patient has more than one chronic condition, assign points for the one with the highest score. Representative examples of point assignments from physiological variables illustrate the banded structure: a of ≤40 beats per minute or associated with scores 11 points, while systolic ≤70 mm scores 13 points. For cases where alternative measurements are available for a variable, the value yielding the higher point assignment is selected; for instance, if both and serum creatinine levels are measured for renal function assessment, the one placing the patient in the more severe band is used. Urinary output is assessed over the full 24-hour period (or prorated if the ICU stay is shorter), ensuring the score captures acute derangements without reliance on continuous monitoring beyond standard and labs. This summation process integrates all components into a single total, serving as the foundation for severity assessment before any probabilistic transformation.

Mortality Prediction Formula

The mortality prediction in SAPS II is derived from the total raw score S, obtained by summing points from its physiological and patient-specific components, through a logistic regression model calibrated on the original multicenter cohort. This model converts the score into a probability of hospital death using the following equation: \text{logit}(S) = -7.7631 + 0.0737 \times S + 0.9971 \times \ln(S + 1) The predicted probability p of hospital mortality is then calculated as: p = \frac{e^{\text{logit}(S)}}{1 + e^{\text{logit}(S)}} This formulation was developed via multiple logistic regression analysis on data from 13,152 intensive care unit patients across 137 centers in Europe and North America, where the observed hospital mortality was 12.7%. The model's discriminative ability was assessed with an area under the receiver operating characteristic curve of 0.88, indicating strong performance in distinguishing survivors from nonsurvivors at the group level. Importantly, the equation estimates expected mortality for cohorts rather than individual odds, and it does not incorporate adjustments for length of ICU stay or other post-admission factors. An alternative logit equation was proposed in a 2005 update specific to French intensive care units, using customized coefficients from a national cohort of 77,490 patients to address calibration drift in the original model. This update applies to an expanded SAPS II that includes additional variables (such as pre-ICU hospital stay and clinical category): \text{logit}(S) = -14.4761 + 0.0844 \times S + 6.6158 \times \ln(S + 1) However, the original 1993 equation remains the primary reference for global SAPS II applications. For scores exceeding 100, the model predicts hospital mortality over 90%, reflecting severe physiological derangement. Computation of the probability can be performed manually using pre-derived tables from the original study or via online calculators, but clinical use should prioritize aggregate predictions to mitigate risks of misinterpreting individual probabilities for treatment decisions.

Clinical Applications

Use in ICU Settings

In intensive care units (ICUs), the Simplified Acute Physiology Score II (SAPS II) is primarily employed to stratify patients by severity of illness, facilitating risk-adjusted comparisons in and quality assessments. It enables the categorization of patients for enrollment in clinical trials, ensuring balanced cohorts across arms to account for physiological derangements and comorbidities. Additionally, SAPS II supports ICU performance by comparing observed outcomes against predicted mortality rates across units or longitudinally over time, which aids in identifying variations in care quality. For , higher SAPS II scores signal greater acuity, prompting intensified monitoring and prioritization of interventions such as enhanced staffing or specialized consultations. In daily clinical practice, SAPS II is routinely calculated within the first 24 hours of ICU admission using vital signs, laboratory values, and patient history to establish a baseline severity benchmark. This score informs audits through computation of the standardized mortality ratio (SMR), defined as the ratio of observed to predicted deaths, allowing ICUs to evaluate efficiency and adjust protocols accordingly. It also contributes to readmission risk assessment; for instance, elevated SAPS II values on initial admission correlate with a 43% increased readmission likelihood per standard deviation rise in score, guiding discharge planning and follow-up intensity. While not designed for dynamic, real-time decision-making, SAPS II excels in retrospective analyses to refine care pathways post-admission. In research settings, SAPS II facilitates adjusted comparisons by controlling for illness severity in outcome studies, enhancing the validity of findings on interventions or therapies. For example, a 2025 study on ICU patients with acute pulmonary embolism demonstrated SAPS II's superior predictive accuracy for 28-day mortality compared to the Sequential Organ Failure Assessment (SOFA) score in specific cohorts, with an optimal threshold of 33 points. Globally adopted since its inception, SAPS II has been integrated into electronic health records in numerous ICUs for automated calculation from routine data, streamlining documentation and analysis. However, local recalibrations are common to improve applicability; the 2005 French update, for instance, incorporated additional variables to enhance calibration and SMR estimates in that population.

Validation and Performance

The initial validation of SAPS II was conducted in a multicenter study involving 13,152 adult patients from 137 intensive care units across 12 countries, excluding those under 18 years, victims, and patients. The model demonstrated strong discrimination with an area under the curve () of 0.88 in the developmental cohort and 0.86 in the validation cohort (95% CI: 0.84-0.88). was adequate, as assessed by the Hosmer-Lemeshow goodness-of-fit test (P = 0.104 in validation), and the standardized mortality (SMR) approximated 1.0, indicating reliable alignment between predicted and observed mortality. Subsequent studies have affirmed SAPS II's utility in diverse populations. A 2005 French multicenter analysis of 77,490 admissions from 106 intensive care units developed an expanded SAPS II model, enhancing (Hosmer-Lemeshow P = 0.81) and (AUC = 0.879) specifically for European settings, where the original score had underestimated mortality. In a 2025 retrospective cohort of 1,031 ICU patients with acute (APE), SAPS II predicted 28-day mortality with an AUC of 0.835 (95% : 0.801-0.870), outperforming the score and other systems like SOFA and III. A 2023 single-center study in a (CCU) with 871 patients further validated expanded SAPS II for in-hospital mortality prediction, showing good (AUC ≈ 0.82) and via Hosmer-Lemeshow testing, with superior performance over . Across continents, SAPS II has been validated in over 100,000 patients through numerous cohorts, maintaining relevance in 2025 despite its age. Modern validations report discrimination via ROC AUC typically ranging from 0.75 to 0.85, with calibration evaluated by the Hosmer-Lemeshow test often indicating adequate fit (P > 0.05 in recalibrated models). However, overprediction of mortality in low-risk groups is common, yielding SMR values below 1.0 (e.g., 0.87 in large samples). In elderly surgical patients, while performance may show slight decrements in discrimination compared to newer scores like SAPS III, SAPS II remains reliable for overall risk stratification. Recalibrations, such as customized versions for local populations, have preserved its utility, particularly in resource-limited settings where simpler scoring systems aid without advanced diagnostics.

Comparisons and Limitations

Comparison to Other Scores

SAPS II, developed in 1993 from an cohort of mixed medical-surgical ICU patients, contrasts with (introduced in 1985) primarily in its design for broader applicability and simplicity. While incorporates 12 physiological variables, age, and chronic health evaluations that include organ-specific subscores for conditions like or , SAPS II employs 17 variables without such organ-differentiated chronic health adjustments, focusing instead on three broad categories (AIDS, metastatic cancer, and home ). This streamlined approach makes SAPS II more suitable for settings outside the U.S.-centric data used for . Performance-wise, both scores exhibit similar discriminatory power for mortality prediction, with area under the curve () values typically ranging from 0.85 to 0.88 across validation studies, though SAPS II's fewer variables facilitate easier implementation in resource-limited environments. Compared to its successor, SAPS 3 (launched in 2005), SAPS II uses fewer variables (17 versus over 20 in SAPS 3) and lacks specific adjustments for conditions like AIDS, which SAPS 3 incorporates as a distinct factor alongside expanded physiological and treatment-related items. SAPS 3 demonstrates superior discrimination in elderly patients, achieving higher values (approximately 0.85 versus 0.80 for SAPS II) in surgical ICUs for those over 90 years old. However, studies indicate SAPS II overpredicts mortality less severely than SAPS 3 in certain surgical contexts, as evidenced by a 2010 cohort analysis showing SAPS 3's greater tendency to overestimate hospital death rates. Recent 2025 comparisons highlight SAPS II's competitive calibration in coronary care units (CCUs) for modern demographics, though it lags behind SAPS 3 overall due to outdated cohort calibration. In relation to SOFA (developed in 1996), SAPS II emphasizes static mortality risk assessment at ICU admission, whereas SOFA dynamically monitors over time using six organ-specific scores. This fundamental difference positions SAPS II as more effective for initial risk stratification, with superior predictive performance for in-hospital mortality compared to initial SOFA scores in various cohorts. A 2025 study on acute (APE) patients in ICUs reported SAPS II's of 0.835 for 28-day mortality, outperforming SOFA and other systems like APACHE III, underscoring its edge in admission-based predictions (SOFA approximately 0.75 in similar contexts). Unlike SOFA's potential for real-time updates, SAPS II remains a one-time calculation, limiting its use for ongoing monitoring but enhancing its role in early . Overall, SAPS II retains preference in low-resource or low-tech ICU settings due to its and robust initial , calibrated on diverse medical-surgical populations. It remains competitive in specialized units like CCUs, though hybrid applications combining SAPS II with dynamic tools like SOFA are increasingly common for comprehensive care. In contemporary analyses, SAPS II shows adequate performance but inferior calibration to SAPS 3 for evolving patient demographics, prompting calls for updates in high-acuity environments.

Known Limitations

One significant limitation of the SAPS II score is its calibration drift in contemporary intensive care units (ICUs), where it tends to overpredict mortality due to advancements in medical since its development in 1993. Recent studies report standardized mortality ratios (SMRs) ranging from 0.73 to 0.88, indicating that observed mortality is substantially lower than predicted, particularly in low-severity where the score underperforms. This overestimation arises from the score's reliance on from older cohorts, leading to less reliable risk stratification in modern settings with improved survival rates. The score also exhibits population-specific biases, showing reduced accuracy in certain demographic groups. In elderly patients over 90 years, discrimination decreases, with area under the curve () values dropping to around 0.75, reflecting poorer prognostic performance in very old individuals. Similarly, calibration varies across ethnicities, with systematic differences suggesting statistical bias that disadvantages non-Caucasian groups through inconsistent mortality predictions. During pandemics like , SAPS II underperforms, as evidenced by unusually low scores in nonsurvivors, highlighting its limited applicability in such scenarios. Additionally, the score lacks validation for pediatric populations and is not intended for use in children. Design-wise, SAPS II provides only a static based on the worst physiological values within the first 24 hours of ICU admission, failing to capture dynamic changes in patient status over time. It omits key and offers no adjustments for ICU length of stay or specific procedures, while readmission risks require separate rescoring without integrated tracking. The score's heavy dependence on laboratory values, such as (BUN), poses challenges in patients on , where chronic elevations may inflate scores unrelated to acute illness. As of 2025, critiques emphasize SAPS II's growing obsolescence compared to AI-enhanced prognostic models, which incorporate for superior accuracy. A recalibration in 2005 improved local calibration but has not been adopted globally, limiting its benefits. Ongoing calls advocate for an updated SAPS II+ incorporating modern variables like levels to enhance relevance, yet no official revision exists as of 2025, with continued use driven primarily by clinician familiarity.

References

  1. [1]
  2. [2]
  3. [3]
    A New Simplified Acute Physiology Score (SAPS II) Based on a ...
    The SAPS II, based on a large international sample of patients, provides an estimate of the risk of death without having to specify a primary diagnosis.
  4. [4]
    Evaluation of SOFA-based models for predicting mortality in the ICU
    Dec 17, 2008 · Models with sequential SOFA scores seem to have a comparable performance with other organ failure scores. The combination of sequential SOFA ...
  5. [5]
    Simplified Acute Physiology Score (SAPS II) Calculator - ClinCalc.com
    Nov 10, 2018 · The SAPS II score is made of 12 physiological variables and 3 disease-related variables. The worst physiological variables were collected within ...Missing: parameters | Show results with:parameters
  6. [6]
    A simplified acute physiology score for ICU patients
    SAPS was a simpler and less time-consuming method for comparative studies and management evaluation between different ICUs. © Williams & Wilkins 1984. All ...Missing: original | Show results with:original
  7. [7]
    Mortality prediction using SAPS II: an update for French intensive ...
    Oct 6, 2005 · Adding simple variables to create an expanded SAPS II model led to better calibration, discrimination and uniformity of fit, producing a tool ...Missing: recalibration | Show results with:recalibration
  8. [8]
    SAPS II (expanded)
    Type of admission · Chronic diseases · Glasgow ; Age · Syst. Blood Pressure · Heart rate ; Temperature · If MV or CPAP PaO2/FIO2(mmHg) · Urine output ; Serum Urea or BUN.
  9. [9]
    Simplified Acute Physiology Score (SAPS) II - MDCalc
    Estimates mortality in ICU patients, comparable to APACHE II. INSTRUCTIONS. Use the worst values in the past 24 hours. When to Use.
  10. [10]
    a nationwide survey of SAPS II assessing practices and its accuracy
    This nationwide survey revealed substantial variability in the SAPS II scoring results. On average, SAPS II scoring was overestimated by more than 13%.Missing: paper | Show results with:paper
  11. [11]
    Mortality prediction using SAPS II: an update for French intensive ...
    The objective of this study was to improve the Simplified Acute Physiology Score (SAPS) II for mortality prediction in ICUs, thereby improving SMR estimates.
  12. [12]
    Variation in severity-adjusted resource use and outcome in intensive ...
    Oct 18, 2021 · The non-university ICUs treated predominantly emergency (> 90%) and non-surgical admissions (74%) with higher median SAPS-II, whereas the ...Missing: monitoring | Show results with:monitoring<|separator|>
  13. [13]
    Severity of illness and risk of readmission to intensive care - PubMed
    The risk of readmission to ICU increased by 43% with each standard deviation increase in severity of illness score (regardless if measured on admission to, or ...
  14. [14]
    Prognostic value of SAPS II score for 28-day mortality in ICU patients ...
    Jul 1, 2025 · SAPS II effectively predict 28-day mortality in ICU patients with APE, outperforming other commonly used scoring systems.
  15. [15]
    Using electronic health record collected clinical variables to predict ...
    Sep 6, 2016 · Outperforms MEWS, SOFA and SAPS II for mortality prediction, with an accuracy of 80%. 1. Introduction. There is a need for accurate prediction ...
  16. [16]
    A new Simplified Acute Physiology Score (SAPS II) based ... - PubMed
    The SAPS II, based on a large international sample of patients, provides an estimate of the risk of death without having to specify a primary diagnosis.
  17. [17]
  18. [18]
    Determinants of the calibration of SAPS II and SAPS 3 mortality ...
    Apr 4, 2017 · The aim of the Simplified Acute Physiology Score (SAPS) II and SAPS 3 is to predict the mortality of patients admitted to intensive care units ( ...
  19. [19]
    Validation of APACHE II, APACHE III and SAPS II scores in in ...
    Dec 2, 2020 · We aimed to validate APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed adult ICU in Poland.Missing: motivations | Show results with:motivations<|control11|><|separator|>
  20. [20]
    The Simplified Acute Physiology Score III Is Superior to the ... - NIH
    This study demonstrates that the SAPS III has slightly better discrimination than the SAPS II and APACHE II in surgical ICU patients over 90-year old.
  21. [21]
    A calibration study of SAPS II with Norwegian intensive care registry ...
    However, the original SAPS II is poorly calibrated to current intensive care unit (ICU) populations because it draws on data, which is more than 20 years old.
  22. [22]
    Comparison of APACHE II and SAPS II Scoring Systems in ... - NIH
    The findings of the present study showed that APACHE II and SAPS II had similar value in predicting 1-month mortality of patients.Missing: motivations | Show results with:motivations
  23. [23]
    (PDF) A comparison of severity systems APACHE II and SAPS II in ...
    Aug 8, 2025 · The SAPS II includes only 17 variables: 12 physiology variables, age ... APACHE and many other scientific topics. Join for free · RG Logo.
  24. [24]
    Efficacy of Various Scoring Systems for Predicting the 28-Day ... - NIH
    Models I and II showed that the APACHE II and SAPS II scores, with AUCs of 89.9% and 86.2%, respectively, significantly influence 28-day survival (P < 0.001 ...
  25. [25]
    Comparison of the performance of SAPS II, SAPS 3, APACHE II, and ...
    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.Missing: paper | Show results with:paper
  26. [26]
    Comparison between SAPS II and SAPS 3 in predicting hospital ...
    Aug 7, 2025 · Both scores provided unreliable predictions, but unexpectedly the newer SAPS 3 turned out to overpredict mortality more than the older SAPS II.
  27. [27]
    Predictive outcomes of APACHE II and expanded SAPS II mortality ...
    Jan 15, 2023 · Expanded SAPS II and APACHE II scores have good ability to predict in-hospital mortality in CCU patients. Therefore, they can be used as a tool to predict ...Missing: motivations | Show results with:motivations
  28. [28]
    Post-Hoc Analyses of the SUP-ICU Inception Cohort Study | PLOS One
    The predictive performance of SAPS II was similar for in-hospital and 90-day mortality and superior to that of the initial SOFA score.
  29. [29]
    Validation of APACHE II and SAPS II scales at the intensive care unit ...
    Jun 28, 2019 · APACHE II and SAPS II scales have better discrimination, calibration and power to predict deaths on ICU than SOFA. Among these scales SOFA did not achieve ...
  30. [30]
    A first‐level customization study of SAPS II with Norwegian Intensive ...
    Mar 11, 2023 · ... standardized mortality ratio (SMR) of 0.73. However ... The observed SAPS II scores were similar when comparing the time period 2018–2020 ...2.1 Patients · 3 Results · 4 Discussion<|control11|><|separator|>
  31. [31]
    Predicting Outcome in Critical Care: The Current Status of SAPS II ...
    SAPS II is a simple, rapid tool used to predict mortality in critically ill patients, and is a significant predictor of mortality in ICU.Missing: monitoring | Show results with:monitoring
  32. [32]
    Short‐term mortality among very elderly cancer patients in the ...
    Oct 18, 2024 · However, research has indicated that the AUC of the SAPS-II score for predicting prognosis decreases with increasing age. The NEWS score ...
  33. [33]
    Performance of intensive care unit severity scoring systems across ...
    The systematic differences in calibration across ethnicities suggest that illness severity scores reflect statistical bias in their predictions of mortality.Missing: Caucasian | Show results with:Caucasian
  34. [34]
    Analysis of Critical Care Severity of Illness Scoring Systems in ... - NIH
    Furthermore, our results demonstrate that APACHE II, SAPS II, and ICNARC scores are also unusually low in nonsurvivors with COVID-19 (Fig. 1), and this is ...<|control11|><|separator|>
  35. [35]
    improving APACHE II, SOFA, and SAPS II scoring systems using ...
    May 5, 2025 · This study aimed to enhance mortality prediction in ICU patients by utilizing Long Short-Term Memory (LSTM) algorithms.Missing: CCU | Show results with:CCU