Background: Falls represent one of the most frequent and serious adverse events in hospital settings, with high incidence and significant clinical consequences. The main risk factors include age >65 years, female sex, comorbidities, cognitive deficits, reduced mobility, use of multiple medications, and unfavorable environmental conditions. Episodes occur more often at night, near the bed, in bathrooms, and in corridors, especially in medical and geriatric wards. Women are more likely to sustain fractures, while mortality is higher in men. Technologies such as environmental sensors and wearable devices can support staff in fall prevention. Objective: To assess the risk of falls in women >65 years old admitted to hospital and compare it with that of residents in a nursing home equipped with the digital Ancelia system. Fall risk was evaluated using the Conley Scale at two time points (T0 admission, T1 discharge), also analyzing related variables such as cognitive status and sleep quality. Materials and Methods: A prospective descriptive observational study with a case-control design, conducted from April to June 2025. A total of 64 women >65 years were included: 32 hospitalized patients and 32 nursing home residents with the Ancelia system. Data were collected through clinical records and nursing assessments. Cognitive status was assessed using the SPMSQ or Pfeiffer Scale, and fall risk was measured with the Conley Scale. Statistical analysis was performed using Jamovi 2.6.26 (p ≤ 0.05). Results: Conley Scale scores indicated a moderate-to-high risk already at T0, with a slight increase at T1. Sarcopenia and a history of previous falls were significantly associated with higher risk. Age, hypertension, cognitive status, and sleep quality showed only clinical trends. No significant differences emerged between the scores of the two groups. Discussion and Conclusion: Fall risk is mainly determined by clinical and functional factors rather than the care context. Sleep quality appears clinically relevant, even without statistical significance. The Ancelia system improves monitoring and response readiness, although it did not demonstrate a significant reduction in falls. The study confirms the usefulness of the Conley Scale and highlights the importance of a multifactorial approach in fall prevention. Keywords: Risk of fall in elderly, Risk factors, Hospital, Elderly home, Prevention of fall risk, Digital systems for fall risk
Background: le cadute rappresentano uno degli eventi avversi più frequenti e gravi in ambito ospedaliero, con elevata incidenza e importanti conseguenze cliniche. I principali fattori di rischio includono età >65 anni, sesso femminile, comorbilità, deficit cognitivi, ridotta mobilità, uso di più farmaci e condizioni ambientali sfavorevoli. Gli episodi si verificano più spesso di notte, vicino al letto, nei bagni e nei corridoi, soprattutto nei reparti medici e geriatrici. Le donne presentano più frequentemente fratture, mentre la mortalità è più alta negli uomini. Tecnologie come sensori ambientali e dispositivi indossabili possono supportare il personale nella prevenzione. Obiettivo: valutare il rischio di caduta in donne >65 anni ricoverate in ospedale e confrontarlo con quello di ospiti in una RSA dotata del sistema digitale Ancelia. Il rischio è stato rilevato tramite la Scala di Conley in due momenti (T0 ingresso, T1 dimissione), analizzando anche variabili correlate come stato cognitivo e qualità del sonno. Materiali e metodi: studio osservazionale descrittivo prospettico con disegno caso-controllo, condotto da aprile a giugno 2025. Sono state coinvolte 64 donne >65 anni: 32 ricoverate in ospedale e 32 ospiti di RSA con sistema Ancelia. I dati sono stati raccolti tramite cartelle cliniche e valutazioni infermieristiche. Per lo stato cognitivo si è utilizzata la Scala SPMSQ o Pfeiffer, e per il rischio di caduta la Scala di Conley. L’analisi è stata condotta con Jamovi 2.6.26 (p ≤ 0,05). Risultati: i punteggi della Scala di Conley indicano un rischio moderato-alto già al T0, con lieve aumento al T1. La sarcopenia e la storia di cadute pregresse risultano significativamente associate a un rischio maggiore. Età, ipertensione, stato cognitivo e qualità del sonno mostrano solo tendenze cliniche. Non sono emerse differenze significative tra i punteggi dei due gruppi. Discussione e conclusione: il rischio di caduta è determinato prevalentemente da fattori clinici e funzionali, più che dal contesto assistenziale. La qualità del sonno appare rilevante dal punto di vista clinico, pur senza significatività statistica. Il sistema Ancelia migliora monitoraggio e prontezza d’intervento, anche se non ha dimostrato una riduzione significativa delle cadute. Lo studio conferma l’utilità della Scala di Conley e l’importanza di un approccio multifattoriale nella prevenzione. Parole chiave: Risk of fall in elderly, Risk factors, Hospital, Elderly home, prevention of the risk of fall, digital systems for the risk of fall
CADUTE E FRAGILITA’. IL RISCHIO COME OPPORTUNITA’ DI MONITORAGGIO INFERMIERISTICO: CONFRONTO TRA RESIDENZA SANITARIA ED OSPEDALE
MANAO, ANNA
2024/2025
Abstract
Background: Falls represent one of the most frequent and serious adverse events in hospital settings, with high incidence and significant clinical consequences. The main risk factors include age >65 years, female sex, comorbidities, cognitive deficits, reduced mobility, use of multiple medications, and unfavorable environmental conditions. Episodes occur more often at night, near the bed, in bathrooms, and in corridors, especially in medical and geriatric wards. Women are more likely to sustain fractures, while mortality is higher in men. Technologies such as environmental sensors and wearable devices can support staff in fall prevention. Objective: To assess the risk of falls in women >65 years old admitted to hospital and compare it with that of residents in a nursing home equipped with the digital Ancelia system. Fall risk was evaluated using the Conley Scale at two time points (T0 admission, T1 discharge), also analyzing related variables such as cognitive status and sleep quality. Materials and Methods: A prospective descriptive observational study with a case-control design, conducted from April to June 2025. A total of 64 women >65 years were included: 32 hospitalized patients and 32 nursing home residents with the Ancelia system. Data were collected through clinical records and nursing assessments. Cognitive status was assessed using the SPMSQ or Pfeiffer Scale, and fall risk was measured with the Conley Scale. Statistical analysis was performed using Jamovi 2.6.26 (p ≤ 0.05). Results: Conley Scale scores indicated a moderate-to-high risk already at T0, with a slight increase at T1. Sarcopenia and a history of previous falls were significantly associated with higher risk. Age, hypertension, cognitive status, and sleep quality showed only clinical trends. No significant differences emerged between the scores of the two groups. Discussion and Conclusion: Fall risk is mainly determined by clinical and functional factors rather than the care context. Sleep quality appears clinically relevant, even without statistical significance. The Ancelia system improves monitoring and response readiness, although it did not demonstrate a significant reduction in falls. The study confirms the usefulness of the Conley Scale and highlights the importance of a multifactorial approach in fall prevention. Keywords: Risk of fall in elderly, Risk factors, Hospital, Elderly home, Prevention of fall risk, Digital systems for fall risk| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/99356