Evidence map›Paper›PMID 35705752›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2022

Fall predictors in hospitalized patients living with cancer: a case-control study.

Anita Zeneli, Sandra Montalti, Itria Masciangelo, Gloria Manieri, Monica Golinucci, Oriana Nanni, Maria Teresa Montella, Giovanni Martinelli, Elisabetta Petracci

Abstract read
PubMed Publisher
In one paragraph

Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

9 authors at 1 institution in 1 country.

Anita ZeneliIstituto Romagnolo Per Lo Studio Dei Tumori "Dino Amadori" IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy. anita.zeneli@irst.emr.it.ORCID http://orcid.org/0000-0002-8556-378X
Sandra MontaltiIstituto Romagnolo Per Lo Studio Dei Tumori "Dino Amadori" IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy.
Itria MasciangeloIstituto Romagnolo Per Lo Studio Dei Tumori "Dino Amadori" IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy.
Gloria ManieriIstituto Romagnolo Per Lo Studio Dei Tumori "Dino Amadori" IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy.
Monica GolinucciIstituto Romagnolo Per Lo Studio Dei Tumori "Dino Amadori" IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy.
Oriana NanniIstituto Romagnolo Per Lo Studio Dei Tumori "Dino Amadori" IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy.
Maria Teresa MontellaIstituto Romagnolo Per Lo Studio Dei Tumori "Dino Amadori" IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy.
Giovanni MartinelliIstituto Romagnolo Per Lo Studio Dei Tumori "Dino Amadori" IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy.
Elisabetta PetracciIstituto Romagnolo Per Lo Studio Dei Tumori "Dino Amadori" IRST IRCCS, via Maroncelli 40, 47014, Meldola, Italy.
Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo identify fall predictors and develop an assessment tool to be used for screening hospitalized cancer patients at risk for fall.

methodsA retrospective case-control study was conducted in 2018 at a cancer center in Northern Italy. The study participants were 448 adult cancer patients admitted to the oncology ward from 2009 to 2013. The case group consisted of 112 patients presenting at least one fall, while controls were randomly chosen by matching each case for age, sex, and admission period with three patients who did not fall. Data for the fall predictors were extracted from the electronic medical records. Conditional logistic regression was used to evaluate the association between patient's characteristics and fall risk.

resultsThe overall prevalence of patients having at least one candidate fall predictor was high (98%). Seven of the studied variables showed an independent association with fall risk at multivariate analysis. These were tumor site, the presence of neurologic diseases, gait imbalance disorders, fatigue, and the assumption of certain medications such as diuretics, hypnotics, and opioids (odds ratios and 95% confidence intervals in brackets were 3.78 (1.78-8.13), 2.26 (1.08-4.77), 4.22 (1.87-9.52), 2.76 (1.45-5.26), 2.66 (1.52-4.66), 2.41 (1.20-4.85), and 3.03 (1.68-5.45), respectively).

conclusionsIn this study, we identified falling risk factors in an Italian population of hospitalized cancer patients and developed a new risk assessment tool. An external validation is necessary before implementing our screening tool in clinical practice.

Indexed as

InpatientsNeoplasmsAdultCase-Control StudiesDiureticsHumansRetrospective StudiesRisk AssessmentRisk FactorsDiureticsFall predictorsFall risk evaluationHospitalized cancer patientsRisk assessment tool

Identifiers

PMID35705752
OpenAlexW4282963635

What OpenQuestion holds

Textmetadata
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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.