Evidence map›Paper›PMID 31650434›Full record

ArticleInternal and emergency medicine2020

Comorbidity does not mean clinical complexity: evidence from the RePoSI register.

Salvatore Corrao, Giuseppe Natoli, Alessandro Nobili, Pier Mannuccio Mannucci, Antonello Pietrangelo, Francesco Perticone, Christiano Argano, RePoSI Investigators

Open access · greenAbstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Internal and emergency medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 29 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 1 country.

Salvatore CorraoDipartimento di Promozione della Salute, Materno Infantile, Medicina Interna e Specialistica di Eccellenza "G. D'Alessandro", PROMISE, University of Palermo, 90133, Palermo, Italy. s.corrao@tiscali.it.ORCID 0000-0001-5621-1374
Giuseppe NatoliDepartment of Organizational, Clinical, and Translational Research, I.E.ME.S.T., 90139, Palermo, Italy.
Alessandro NobiliDepartment of Neuroscience, IRCCS, Istituto Di Ricerche Farmacologiche Mario Negri, 20156, Milan, Italy.
Pier Mannuccio MannucciScientific Direction IRCCS Foundation Maggiore Policlinico Hospital, 20122, Milan, Italy.
Antonello PietrangeloDepartment of Internal Medicine II, Center for Hemochromatosis, University of Modena and Reggio Emilia Policlinico, 41100, Modena, Italy.
Francesco PerticoneDepartment of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, 88100, Catanzaro, Italy.
Christiano ArganoDepartment of Internal Medicine, National Relevance and High Specialization Hospital Trust ARNAS Civico, Di Cristina, Benfratelli, 90127, Palermo, Italy.
RePoSI Investigators
Mario Negri Institute for Pharmacological Research · ITUniversity of Modena and Reggio Emilia · ITAzienda di Rilievo Nazionale ed Alta Specializzazione · ITMagna Graecia University · ITUniversity of Palermo · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last 2-3 decades internists have confronted dramatic changes in the pattern of patients acutely admitted to hospital wards. Internists observed a shift from younger subjects affected by a single organ disease to more complex patients, usually older, with multiple chronic conditions, attended by different specialists, with poor integration and treated with multiple drugs. In this regard, the concept of complex patients is addressed daily in clinical practice even if there is no agreed definition of patient complexity. To try to evaluate clinical complexity different instruments have been proposed. Among these, the number of comorbidities (NoC) was considered a marker of clinical complexity. However, this instrument would not give information about the clinical relevance of each condition. On the contrary, cumulative illness rating scale (CIRS) addresses the problem calculating both CIRS severity index (CIRS-SI) and CIRS comorbidity index (CIRS-CI). In light of this, 4714 patients from the RePoSI register were retrospectively analyzed to show if CIRS assessment of comorbidity burden is different from the simple count of comorbidities in predicting the length of hospital stay (LOS) and all-cause of mortality in hospitalized elderly patients and if NoC could be a valid tool to measure patient's complexity. CIRS-SI resulted the best predictor of all-cause in-hospital mortality [OR: 2.66 (1.88-3.77)] in comparison with NoC that did not result statistically significant (p = 0.551). CIRS-SI was also the best predictor of all-cause of post-discharge mortality corrected for age and sex [OR: 2.12 (1.53-2.95)]. CIRS-SI (coefficient ± standard error: 1.23 ± 0.59; p < 0.0381) and CIRS-CI (coefficient ± standard error: 0.27 ± 0.10; p < 0.011) were strong predictors of LOS in comparison with NoC that did not result statistically significant (coefficient ± standard error: 0.04 ± 0.06 p < 0.0561). In conclusion, CIRS assessment of comorbidity burden is a better clinical tool in comparison with the simple count of comorbidities especially considering the length of hospital stay and all-cause mortality in hospitalized elderly patients.

Indexed as

Cause of DeathComorbidityGeriatric AssessmentAgedAged, 80 and overFemaleHospital MortalityHumansInternal MedicineItalyLength of StayMaleRegistriesRetrospective StudiesRisk FactorsSeverity of Illness IndexClinical complexityCumulative illness rating scaleMultimorbidityNumber of comorbidities

Identifiers

PMID31650434
OpenAlexW2981806287

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.