Skip to main content

Advertisement

SpringerLink
Log in

A simple prediction score for in-hospital mortality in patients with nonvariceal upper gastrointestinal bleeding

  • Original Article—Alimentary Tract
  • Published:
Journal of Gastroenterology Aims and scope Submit manuscript

Abstract

Background

No prediction scores for the mortality of both inpatients and outpatients who developed nonvariceal upper gastrointestinal bleeding (UGIB) without endoscopic findings have been established. We aimed to derive and validate a novel prediction score for in-hospital mortality.

Methods

We conducted a three-stage, multicenter retrospective study. In the derivation stage, patients with nonvariceal UGIB at six institutions were enrolled to derive the prediction score by logistic regression analysis. External validation of the score was performed to analyze discrimination by patients at six other institutions. Then the performance of this score was compared with that of four existing scores.

Results

We enrolled 1380 and 825 patients in the derivation and validation cohorts, respectively. A prediction score (CHAMPS-R Score) comprising seven variables (Charlson Comorbidity Index ≥ 2, in-hospital onset, albumin < 2.5 g/dL, altered mental status, Eastern Cooperative Oncology Group performance status ≥ 2, steroids, and rebleeding) with equal-weight scores was established, with high discriminative ability in both derivation and validation cohorts (c statistic, 0.91 and 0.80, respectively). When rebeeding was excluded from the score (an onset model; CHAMPS Score), this score also achieved high discriminative ability (c statistic, 0.90 and 0.81, respectively). The prediction scores had significantly higher discriminative ability than the Glasgow Blatchford Score, AIMS65, ABC Score, and clinical Rockall Score in both cohorts (all, p < 0.05).

Conclusions

We derived and externally validated prediction scores for in-hospital mortality in patients with nonvariceal UGIB. The CHAMPS Score might be optimal for managing such patients. Its mobile application is freely available (https://apps.apple.com/app/id1565716902 for iOS and https://play.google.com/store/apps/details?id=hatta.CHAMPS for Android).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Abbreviations

UGIB:

Upper gastrointestinal bleeding

GBS:

Glasgow Blatchford Score

ECOG-PS:

Eastern Cooperative Oncology Group performance status

CCI:

Charlson Comorbidity Index

IQR:

Interquartile range

VIF:

Variance inflation factor

PPV:

Positive predictive value

NPV:

Negative predictive value

CI:

Confidence interval

BP:

Blood pressure

NSAIDs:

Nonsteroidal anti-inflammatory drugs

OR:

Odds ratio

References

  1. Laine L, Yang H, Chang SC, et al. Trends for incidence of hospitalization and death due to GI complications in the United States from 2001 to 2009. Am J Gastroenterol. 2012;107:1190–5.

    Article  Google Scholar 

  2. Wuerth BA, Rockey DC. Changing epidemiology of upper gastrointestinal hemorrhage in the last decade: a nationwide analysis. Dig Dis Sci. 2018;63:1286–93.

    Article  Google Scholar 

  3. Abougergi MS, Travis AC, Saltzman JR. The in-hospital mortality rate for upper GI hemorrhage has decreased over 2 decades in the United States: a nationwide analysis. Gastrointest Endosc. 2015;81:882–8.

    Article  Google Scholar 

  4. Hearnshaw SA, Logan RF, Lowe D, et al. Acute upper gastrointestinal bleeding in the UK: patient characteristics, diagnoses and outcomes in the 2007 UK audit. Gut. 2011;60:1327–35.

    Article  Google Scholar 

  5. Laine L, Jensen DM. Management of patients with ulcer bleeding. Am J Gastroenterol. 2012;107:345–60.

    Article  CAS  Google Scholar 

  6. Gralnek IM, Dumonceau JM, Kuipers EJ, et al. Diagnosis and management of nonvariceal upper gastrointestinal hemorrhage: European Society of Gastrointestinal Endoscopy (ESGE) Guideline. Endoscopy. 2015;47:a1-46.

    Article  Google Scholar 

  7. Blatchford O, Murray WR, Blatchford M. A risk score to predict need for treatment for upper-gastrointestinal haemorrhage. Lancet. 2000;356:1318–21.

    Article  CAS  Google Scholar 

  8. Saltzman JR, Tabak YP, Hyett BH, et al. A simple risk score accurately predicts in-hospital mortality, length of stay, and cost in acute upper GI bleeding. Gastrointest Endosc. 2011;74:1215–24.

    Article  Google Scholar 

  9. Stanley AJ, Laine L, Dalton HR, et al. Comparison of risk scoring systems for patients presenting with upper gastrointestinal bleeding: international multicentre prospective study. BMJ. 2017;356:i6432.

    Article  Google Scholar 

  10. Laursen SB, Oakland K, Laine L, et al. ABC score: a new risk score that accurately predicts mortality in acute upper and lower gastrointestinal bleeding: an international multicentre study. Gut. 2021;70:707–16.

    Article  Google Scholar 

  11. Cook DJ, Fuller HD, Guyatt GH, et al. Risk factors for gastrointestinal bleeding in critically ill patients. Canadian Critical Care Trials Group. N Engl J Med. 1994;330:377–81.

    Article  CAS  Google Scholar 

  12. Muller T, Barkun AN, Martel M. Non-variceal upper GI bleeding in patients already hospitalized for another condition. Am J Gastroenterol. 2009;104:330–9.

    Article  Google Scholar 

  13. Jairath V, Thompson J, Kahan BC, et al. Poor outcomes in hospitalized patients with gastrointestinal bleeding: impact of baseline risk, bleeding severity, and process of care. Am J Gastroenterol. 2014;109:1603–12.

    Article  Google Scholar 

  14. Marmo R, Koch M, Cipolletta L, et al. Predicting mortality in patients with in-hospital nonvariceal upper GI bleeding: a prospective, multicenter database study. Gastrointest Endosc. 2014;79:741–9.

    Article  Google Scholar 

  15. Kondo Y, Hatta W, Koike T, et al. The use of higher dose steroids increases the risk of rebleeding after endoscopic hemostasis for peptic ulcer bleeding. Dig Dis Sci. 2018;63:3033–40.

    Article  CAS  Google Scholar 

  16. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–83.

    Article  CAS  Google Scholar 

  17. Akirov A, Masri-Iraqi H, Atamna A, et al. Low Albumin levels are associated with mortality risk in hospitalized patients. Am J Med. 2017;130(1465):e1411–9.

    Google Scholar 

  18. Marmo R, Koch M, Cipolletta L, et al. Predictive factors of mortality from nonvariceal upper gastrointestinal hemorrhage: a multicenter study. Am J Gastroenterol. 2008;103:1639–47.

    Article  Google Scholar 

  19. Ogata Y, Hatta W, Koike T, et al. Predictors of early and late mortality after endoscopic resection for esophageal squamous cell carcinoma. Tohoku J Exp Med. 2021;253:29–39.

    Article  CAS  Google Scholar 

  20. Steyerberg EW, Harrell FE Jr, Borsboom GJ, et al. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001;54:774–81.

    Article  CAS  Google Scholar 

  21. Steyerberg EW, Bleeker SE, Moll HA, et al. Internal and external validation of predictive models: a simulation study of bias and precision in small samples. J Clin Epidemiol. 2003;56:441–7.

    Article  Google Scholar 

  22. Rockall TA, Logan RF, Devlin HB, et al. Risk assessment after acute upper gastrointestinal haemorrhage. Gut. 1996;38:316–21.

    Article  CAS  Google Scholar 

  23. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–45.

    Article  CAS  Google Scholar 

  24. Hyett BH, Abougergi MS, Charpentier JP, et al. The AIMS65 Score compared with the Glasgow–Blatchford Score in predicting outcomes in upper GI bleeding. Gastrointest Endosc. 2013;77:551–7.

    Article  Google Scholar 

  25. Iino C, Mikami T, Igarashi T, et al. Evaluation of scoring models for identifying the need for therapeutic intervention of upper gastrointestinal bleeding: a new prediction score model for Japanese patients. Dig Endosc. 2016;28:714–21.

    Article  Google Scholar 

  26. Saeed ZA, Winchester CB, Michaletz PA, et al. A scoring system to predict rebleeding after endoscopic therapy of nonvariceal upper gastrointestinal hemorrhage, with a comparison of heat probe and ethanol injection. Am J Gastroenterol. 1993;88:1842–9.

    CAS  PubMed  Google Scholar 

  27. Sung JJ, Tsoi KK, Ma TK, et al. Causes of mortality in patients with peptic ulcer bleeding: a prospective cohort study of 10,428 cases. Am J Gastroenterol. 2010;105:84–9.

    Article  Google Scholar 

  28. Sanders DS, Perry MJ, Jones SG, et al. Effectiveness of an upper-gastrointestinal haemorrhage unit: a prospective analysis of 900 consecutive cases using the Rockall Score as a method of risk standardisation. Eur J Gastroenterol Hepatol. 2004;16:487–94.

    Article  Google Scholar 

  29. Altman DG, Vergouwe Y, Royston P, et al. Prognosis and prognostic research: validating a prognostic model. BMJ. 2009;338:b605.

    Article  Google Scholar 

  30. Marmo R, Koch M, Cipolletta L, et al. Predicting mortality in non-variceal upper gastrointestinal bleeders: validation of the Italian PNED Score and Prospective Comparison with the Rockall Score. Am J Gastroenterol. 2010;105:1284–91.

    Article  Google Scholar 

  31. Iwai N, Dohi O, Naito Y, et al. Impact of the Charlson Comorbidity Index and prognostic nutritional index on prognosis in patients with early gastric cancer after endoscopic submucosal dissection. Dig Endosc. 2018;30:616–23.

    Article  Google Scholar 

  32. Harimoto N, Yoshizumi T, Shimokawa M, et al. Sarcopenia is a poor prognostic factor following hepatic resection in patients aged 70 years and older with hepatocellular carcinoma. Hepatol Res. 2016;46:1247–55.

    Article  Google Scholar 

Download references

Acknowledgements

We thank Kenichi Negoro (Tohoku University Graduate School of Medicine) for his contribution to developing a mobile application for the CHAMPS Score. We also thank Naoki Nakaya (Tohoku Medical Megabank Organization) for his insightful comments and advice for statistical analyses in this study.

Funding

The current study was self-funded.

Author information

Author notes

  1. Tamotsu Matsuhashi and Waku Hatta are co-first authors.

Authors and Affiliations

  1. Department of Gastroenterology, Akita University Graduate School of Medicine, Akita, Japan

    Tamotsu Matsuhashi, Sho Fukuda & Katsunori Iijima

  2. Division of Gastroenterology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan

    Waku Hatta, Yohei Ogata, Atsushi Masamune & Yoichi Kakuta

  3. Department of Endoscopy, Fukushima Medical University Hospital, Fukushima, Japan

    Takuto Hikichi & Jun Nakamura

  4. Division of Endoscopy, Hirosaki University Hospital, Hirosaki, Japan

    Tatsuya Mikami

  5. Department of Gastroenterology and Hematology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan

    Tetsuya Tatsuta

  6. Division of Endoscopy, Yamagata University Hospital, Yamagata, Japan

    Yasuhiko Abe

  7. Department of Gastroenterology, Faculty of Medicine, Yamagata University Hospital, Yamagata, Japan

    Yusuke Onozato

  8. Department of Gastroenterology, Osaki Citizen Hospital, Osaki, Japan

    Motoki Ohyauchi & Hirotaka Ito

  9. Department of Gastroenterology, Aomori Prefectural Central Hospital, Aomori, Japan

    Norihiro Hanabata & Yasumitsu Araki

  10. Department of Gastroenterology, Ohta Nishinouchi Hospital, Kooriyama, Japan

    Takumi Yanagita & Hidemichi Imamura

  11. Department of Gastroenterology, Akita City Hospital, Akita, Japan

    Tsuyotoshi Tsuji & Kae Sugawara

  12. Department of Gastroenterology, Hiraka General Hospital, Yokote, Japan

    Yohei Horikawa

  13. Department of Gastroenterology, Tohoku Rosai Hospital, Sendai, Japan

    Shuichi Ohara & Yutaka Kondo

  14. Department of Gastroenterology, Yuri Kumiai General Hospital, Yurihonjou, Japan

    Takahiro Dohmen

  15. Department of Health Record Informatics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan

    Tomohiro Nakamura

Authors
  1. Tamotsu Matsuhashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Waku Hatta
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Takuto Hikichi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sho Fukuda
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tatsuya Mikami
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tetsuya Tatsuta
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jun Nakamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yasuhiko Abe
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yusuke Onozato
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Yohei Ogata
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Atsushi Masamune
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Motoki Ohyauchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Hirotaka Ito
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Norihiro Hanabata
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Yasumitsu Araki
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Takumi Yanagita
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Hidemichi Imamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Tsuyotoshi Tsuji
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Kae Sugawara
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Yohei Horikawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Shuichi Ohara
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Yutaka Kondo
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Takahiro Dohmen
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Yoichi Kakuta
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Tomohiro Nakamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Katsunori Iijima
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conception and design: WH and KI. Acquisition of data: TM, WH, TH, SF, TM, TT, JN, YA, YO, MO, HI, NH, YA, TY, HI, TT, KS, YH, SO, YK, and TD. Analysis and interpretation of data: TM, WH, and KI. Drafting of the manuscript: WH. Critical revision of the manuscript: AM, TN, and KI. Statistical analysis: WH and YO. Development of a mobile application: WH and YK. Study supervision: KI. All authors listed have contributed substantially to the design, data collection and analysis, and editing of the manuscript.

Corresponding author

Correspondence to Waku Hatta.

Ethics declarations

Conflict of interest

Atsushi Masamune declared that he received lecture honoraria from EA Pharma Co. Ltd., Takeda Pharmaceutical Co. Ltd., Daiichi Sankyo, Inc., and Mylan.co.jp and he received commercial research funding from Otsuka Pharmaceutical Co. Ltd., EA Pharma Co. Ltd., Gilead Sciences, Inc., Asahi Kasei Pharma Corp., Eisai Co. Ltd., AbbVie GK, Takeda Pharmaceutical Co. Ltd., and Daiichi Sankyo, Inc. outside the submitted work.

Patient consent for publication

Not required.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 338 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Matsuhashi, T., Hatta, W., Hikichi, T. et al. A simple prediction score for in-hospital mortality in patients with nonvariceal upper gastrointestinal bleeding. J Gastroenterol 56, 758–768 (2021). https://doi.org/10.1007/s00535-021-01797-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00535-021-01797-w

Keywords

Search

Navigation