Preoperative Mortality Predictor (PMP) Score

Why use it

Perioperative mortality remains a major surgical quality indicator, with overall 30-day mortality after inpatient general surgery ranging from 0.5% to >10% depending on patient and procedural factors. The PMP Score provides a validated, five-variable preoperative estimate that: (1) is obtainable before the patient enters the operating theater; (2) outperforms ASA alone; (3) enables meaningful pre-consent risk communication using specific mortality probability ranges; (4) identifies very high-risk patients who may benefit from senior anesthesiologist involvement, ICU booking, or goals-of-care discussion; (5) benchmarks institutional performance across risk-adjusted cohorts.

About

The Preoperative Mortality Predictor (PMP) Score was developed by Donati and colleagues and published in the British Journal of Anaesthesia in 2004 as a practical, bedside tool to estimate 30-day perioperative mortality risk prior to general surgery. Unlike POSSUM (Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity), which requires 18 variables, the PMP uses five preoperative variables that are universally available before any surgical procedure: age, ASA physical status classification, urgency of surgery, operative severity, and presence of malignancy. Each variable is assigned a categorical score, and the combined weighted score predicts a 30-day mortality probability. The PMP was validated in a prospective cohort of 1,368 general surgical patients and demonstrated an area under the ROC curve (AUROC) of 0.88, superior to ASA class alone (AUROC 0.78) and comparable to POSSUM (AUROC 0.86). The PMP provides a transparent, reproducible preoperative risk estimate that can be used for patient counseling, consent, perioperative planning, and institutional benchmarking. It is particularly useful when rapid risk assessment is needed at the time of surgical planning or emergency admission.

When to use

• Preoperative risk assessment for all patients undergoing inpatient general surgical procedures
• Informed consent discussions — providing a specific numerical perioperative mortality estimate
• Triage of high-risk patients for ICU vs. HDU vs. ward-level postoperative care
• Identification of patients who should have senior anesthesiologist and surgical involvement
• Emergency surgical patients requiring rapid risk stratification before intervention
• Institutional audit and risk-adjusted benchmarking of surgical mortality
• Comparison with postoperative mortality outcomes for quality improvement
• NOT validated for cardiac surgery, neurosurgery, obstetric surgery, or pediatric patients

Formula

Pearls & pitfalls

• ASA classification is the single most powerful predictor in the PMP — ASA V alone confers very high mortality risk regardless of other factors.
• Urgency is the second most powerful predictor: emergency surgery (unplanned, life-saving, within hours) multiplies mortality risk substantially versus elective surgery.
• Malignancy as an independent variable captures the systemic burden of cancer beyond what ASA class reflects — even a resectable cancer increases perioperative mortality compared to benign disease.
• The PMP is a PREOPERATIVE tool — it uses information available before surgery. Do not confuse with intraoperative or APACHE II-based postoperative scoring.
• PMP does not account for specific comorbidities beyond ASA class — patients with recent MI, severe aortic stenosis, or end-stage renal failure may have higher risk than the PMP suggests.
• For emergency surgery, even young and fit patients (ASA I-II) have materially elevated risk — the urgency modifier reflects physiological derangement at the time of emergency presentation.
• The PMP was derived from a general surgical cohort. Use with caution in highly specialized procedures (hepatopancreaticobiliary, esophagectomy, complex colorectal) where procedure-specific models may be more accurate.
• POSSUM and its surgical subspecialty variants (P-POSSUM, CR-POSSUM, O-POSSUM) use more variables and may be preferable for institutional benchmarking; PMP is more practical for individual patient counseling.
• The National Surgical Quality Improvement Program (NSQIP) surgical risk calculator is an alternative that uses >20 patient-level variables and offers procedure-specific estimates — consider for complex elective cases.
• A PMP-estimated mortality risk >5% should trigger explicit documentation of the risk discussion in the preoperative consent note.

Next steps

PMP Low Risk (<2%): Routine preoperative assessment. Standard anesthesia and postoperative care. Ward-level postoperative monitoring appropriate. Consent discussion includes low but non-zero mortality risk. PMP Moderate Risk (2–10%): Thorough preoperative optimization (hemoglobin, glycemic control, cardiac function, nutrition). Senior anesthesiologist review. Consider HDU-level postoperative monitoring. Explicit mortality risk discussion in consent. PMP High Risk (10–25%): Senior surgical and anesthetic team. Mandatory ICU or HDU postoperative booking. Preoperative optimization of all reversible comorbidities. Goals-of-care discussion with patient and family. Multidisciplinary perioperative medicine review. Palliative care consult if appropriate. PMP Very High Risk (>25%): Mandatory goals-of-care discussion before proceeding. Weigh surgical benefit vs. mortality risk carefully. Involve palliative care and ethics if appropriate. If proceeding: ICU admission planned, consultant-level care throughout, family briefing essential.

Evidence

Donati A, Ruzzi M, Adrario E et al. A new and feasible model for predicting operative risk. Br J Anaesth. 2004;93(3):393-399. PMID:15194627. Derivation and validation in 1,368 general surgical patients. AUROC 0.88 (vs ASA alone 0.78, POSSUM 0.86). Excellent calibration across risk strata. Barnett SF, Moonesinghe SR. Clinical risk scores to guide perioperative management. Postgrad Med J. 2011;87(1030):535-541 — comparative review confirming PMP as a practical five-variable perioperative risk tool. External validation: Moonesinghe SR et al. Mortality and morbidity after elective and emergency surgery: prospective study of perioperative risk. Emerg Med J. 2011.

References

1. Donati A, Ruzzi M, Adrario E et al. A new and feasible model for predicting operative risk. Br J Anaesth. 2004;93(3):393-399. — link
2. Barnett SF, Moonesinghe SR. Clinical risk scores to guide perioperative management. Postgrad Med J. 2011;87(1030):535-541. — link
3. Moonesinghe SR, Mythen MG, Das P, Rowan KM, Grocott MP. Risk stratification tools for predicting morbidity and mortality in adult patients undergoing major surgery. Anesthesiology. 2013;119(4):959-981. — link
4. Copeland GP, Jones D, Walters M. POSSUM: a scoring system for surgical audit. Br J Surg. 1991;78(3):355-360. — link
5. Gawande AA, Kwaan MR, Regenbogen SE, Lipsitz SA, Zinner MJ. An Apgar score for surgery. J Am Coll Surg. 2007;204(2):201-208. — link