{
  "abstract": "Background: Prognosis prediction in adult intensive care units (ICUs) guides clinical decision-making, realistic goal-setting with families, and resource allocation, but is challenged by the marked heterogeneity of critically ill patients in multi-speciality wards. Methods: This narrative review critically analyses commonly used prognostic scoring systems by clinical application timeline. Results: Admission prognostic models, including the Acute Physiology and Chronic Health Evaluation (APACHE II/III/IV), Simplified Acute Physiology Score (SAPS II/SAPS 3) and Mortality Probability Model (MPM), estimate in-hospital mortality from acute physiological derangement and comorbidity; the Clinical Frailty Scale (CFS) adds prognostic value. During the ICU stay, organ dysfunction is tracked with the Sequential Organ Failure Assessment (SOFA/SOFA-2), designed for repeated reassessment, and the Multiple Organ Dysfunction Score (MODS), while the Therapeutic Intervention Scoring System (TISS-28) quantifies nursing workload. At discharge, the Barthel Index, Glasgow Outcome Scale (GOS) and Cerebral Performance Category (CPC) measure functional independence and neurological outcome. Admission-based mortality models use an initial assessment window and may require local recalibration, and discrimination alone does not establish clinical utility. Conclusions: Future directions include trajectory-based models, phenotyping, biomarkers, time-limited trials and machine learning. Prognostic estimates should inform multidisciplinary evaluation and shared decision-making, rather than independently determine treatment intensity or withdrawal.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Anesthesiology, Intensive Therapy and Perioperative Medicine, Department of Acute Medicine, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 41-800 Zabrze, Poland"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Piotr S. Liberski"
    },
    {
      "affs": [
        0
      ],
      "name": "Szymon Czajka"
    },
    {
      "affs": [
        0
      ],
      "name": "Krzysztof Żerdziński",
      "orcid": "0009-0003-6581-8401"
    },
    {
      "affs": [
        0
      ],
      "name": "Łukasz J. Krzych",
      "orcid": "0000-0002-5252-8398"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8ngp6sgp4sgfj.bib",
  "cited_by": 0,
  "doi": "10.3390/jcm15208073",
  "fulltext_url": null,
  "id": "8ngp6sgp4sgfj",
  "issns": [
    "2077-0383"
  ],
  "landing_url": "https://www.mdpi.com/2077-0383/15/20/8073",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2713|Sepsis Diagnosis and Treatment"
    ]
  ],
  "openalex": "W7222964195",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-17",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/8ngp6sgp4sgfj.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:00Z",
      "native_id": "10.3390/jcm15208073",
      "source": "crossref",
      "url": "https://www.mdpi.com/2077-0383/15/20/8073"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2713|Sepsis Diagnosis and Treatment",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Prognosis Prediction in Adult Intensive Care—A Critical Analysis",
  "title_text": "Prognosis Prediction in Adult Intensive Care—A Critical Analysis",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:20:00Z",
  "url": "https://research.draconitic.com/paper/8ngp6sgp4sgfj",
  "venue": "Journal of Clinical Medicine",
  "versions": []
}