human
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Background : falls in hospitals are a major problem and contribute to substantial healthcare burden . Advances in sensor technology afford innovative approaches to reducing falls in acute hospital care . However , whether these are clinical ly effective and cost effective in the UK setting has not been evaluated . Methods : pragmatic , parallel-arm , individual r and omised controlled trial of bed and bedside chair pressure sensors using radio-pagers ( intervention group ) compared with st and ard care ( control group ) in elderly patients admitted to acute , general medical wards , in a large UK teaching hospital . Primary outcome measure number of in-patient bedside falls per 1,000 bed days . Results : 1,839 participants were r and omised ( 918 to the intervention group and 921 to the control group ) . There were 85 bedside falls ( 65 fallers ) in the intervention group , falls rate 8.71 per 1,000 bed days compared with 83 bedside falls ( 64 fallers ) in the control group , falls rate 9.84 per 1,000 bed days ( adjusted incidence rate ratio , 0.90 ; 95 % confidence interval [ CI ] , 0.66–1.22 ; P = 0.51 ) . There was no significant difference between the two groups with respect to time to first bedside fall ( adjusted hazard ratio ( HR ) , 0.95 ; 95 % CI : 0.67–1.34 ; P= 0.12 ) . The mean cost per patient in the intervention group was £ 7199 compared with £ 6400 in the control group , mean difference in QALYs per patient , 0.0001 ( 95 % CI : −0.0006–0.0004 , P= 0.67 ) . Conclusions : bed and bedside chair pressure sensors as a single intervention strategy do not reduce in-patient bedside falls , time to first bedside fall and are not cost-effective in elderly patients in acute , general medical wards in the UK . Trial registration : is rct n.org identifier : IS RCT N44972300 BACKGROUND Falls are a predominant problem in our aging society , often leading to severe somatic and psychological consequences , and having an incidence of about 30 % in the group of persons aged 65 years or above . In order to identify persons at risk , many assessment tools and tests have been developed , but most of these have to be conducted in a supervised setting and are dependent on an expert rater . OBJECTIVES The overall aim of our research work is to develop an objective and unobtrusive method to determine individual fall risk based on the use of motion sensor data . The aims of our work for this paper are to derive a fall risk model based on sensor data that may potentially be measured during typical activities of daily life ( aim # 1 ) , and to evaluate the result ing model with data from a one-year follow-up study ( aim # 2 ) . METHODS A sample of n = 119 geriatric in patients wore an accelerometer on the waist during a Timed ' Up & Go ' test and a 20 m walk .  Fifty patients were included in a one-year follow-up study , assessing fall events and scoring average physical activity at home in telephone interviews . The sensor data were processed to extract gait and dynamic balance parameters , from which four fall risk models -- two classification trees and two logistic regression models -- were computed : models CT#1 and SL#1 using accelerometer data only , models CT#2 and SL#2 including the physical activity score . The risk models were evaluated in a ten-times tenfold cross-validation procedure , calculating sensitivity ( SENS ) , specificity ( SPEC ) , positive and negative predictive values ( PPV , NPV ) , classification accuracy , area under the curve ( AUC ) and the Brier score . RESULTS Both classification trees show a fair to good performance ( models CT#1/CT#2 ) : SENS 74%/58 % , SPEC 96%/82 % , PPV 92%/ 74 % , NPV 77%/82 % , accuracy 80%/78 % , AUC 0.83/0.87 and Brier scores 0.14/0.14 . The logistic regression models ( SL#1/SL#2 ) perform worse : SENS 42%/58 % , SPEC 82%/ 78 % , PPV 62%/65 % , NPV 67%/72 % , accuracy 65%/70 % , AUC 0.65/0.72 and Brier scores 0.23/0.21 . CONCLUSIONS Our results suggest that accelerometer data may be used to predict falls in an unsupervised setting . Furthermore , the parameters used for prediction are measurable with an unobtrusive sensor device during normal activities of daily living . These promising results have to be vali date d in a larger , long-term prospect i ve trial Objective To determine the efficacy of a targeted multifactorial falls prevention programme in elderly care wards with relatively short lengths of stay . Design Cluster r and omised trial . Setting 24 elderly care wards in 12 hospitals in Sydney , Australia . Participants 3999 patients , mean age 79 years , with a median hospital stay of seven days . Interventions A nurse and physiotherapist each worked for 25 hours a week for three months in all intervention wards . They provided a targeted multifactorial intervention that included a risk assessment of falls , staff and patient education , drug review , modification of bedside and ward environments , an exercise programme , and alarms for selected patients . Main outcome measure Falls during hospital stay . Results Intervention and control wards were similar at baseline for previous rates of falls and individual patient characteristics . Overall , 381 falls  occurred during the study . No difference was found in fall rates during follow-up between intervention and control wards : respectively , 9.26 falls per 1000 bed days and 9.20 falls per 1000 bed days ( P=0.96 ) . The incidence rate ratio adjusted for individual lengths of stay and previous fall rates in the ward was 0.96 ( 95 % confidence interval 0.72 to 1.28 ) . Conclusion A targeted multifactorial falls prevention programme was not effective among older people in hospital wards with relatively short lengths of stay . Trial registration Australian New Zeal and Clinical Trials Registry ACTRNO 12605000467639 Background Falls are a major cause of morbidity and mortality in dementia , but there have been no prospect i ve studies of risk factors for falling specific to this patient population , and no successful falls intervention/prevention trials . This prospect i ve study aim ed to identify modifiable risk factors for falling in older people with mild to moderate dementia . Methods and Findings 179 participants aged over 65 years were recruited from outpatient clinics in the UK ( 38 Alzheimer 's disease ( AD ) , 32 Vascular dementia ( VAD ) , 30 Dementia with Lewy bodies ( DLB ) , 40 Parkinson 's disease with dementia ( PDD ) , 39 healthy controls ) . A multifactorial assessment of baseline risk factors was performed and fall diaries were completed prospect ively for 12 months . Dementia participants experienced nearly 8 times more incident falls ( 9118/1000 person-years ) than controls ( 1023/1000 person-years ; incidence density ratio : 7.58 , 3.11–18.5 ) . In dementia , significant univariate predictors of sustaining at least one fall included diagnosis of Lewy body disorder ( proportional hazard ratio ( HR ) adjusted for age and sex : 3.33 , 2.11–5.26 ) , and history of falls in the preceding 12 months ( HR : 2.52 , 1.52–4.17 ) . In multivariate analyses , significant potentially modifiable predictors were symptomatic orthostatic hypotension ( HR : 2.13 , 1.19–3.80 ) , autonomic symptom score ( HR per point 0–36 : 1.055 , 1.012–1.099 ) , and Cornell depression score ( HR per point 0–40 : 1.053 , 1.01–1.099 ) . Higher levels of physical activity were protective ( HR per point 0–9 : 0.827 , 0.716–0.956 ) . Conclusions The management of symptomatic orthostatic hypotension , autonomic symptoms and depression , and the encouragement of physical activity may provide the core elements for the most fruitful strategy to reduce falls in people with dementia . R and omised controlled trials to assess such a strategy are a priority CONTEXT Falls cause injury and death for persons of all ages , but risk of falls increases markedly with age . Hospitalization further increases risk , yet no evidence exists to support short-stay hospital-based fall prevention strategies to reduce patient  falls . OBJECTIVE To investigate whether a fall prevention tool kit ( FPTK ) using health information technology ( HIT ) decreases patient falls in hospitals . DESIGN , SETTING , AND PATIENTS Cluster r and omized study conducted January 1 , 2009 , through June 30 , 2009 , comparing patient fall rates in 4 urban US hospitals in units that received usual care ( 4 units and 5104 patients ) or the intervention ( 4 units and 5160 patients ) . INTERVENTION The FPTK integrated existing communication and workflow patterns into the HIT application . Based on a valid fall risk assessment scale completed by a nurse , the FPTK software tailored fall prevention interventions to address patients ' specific determinants of fall risk . The FPTK produced bed posters composed of brief text with an accompanying icon , patient education h and outs , and plans of care , all communicating patient-specific alerts to key stakeholders . MAIN OUTCOME MEASURES The primary outcome was patient falls per 1000 patient-days adjusted for site and patient care unit . A secondary outcome was fall-related injuries . RESULTS During the 6-month intervention period , the number of patients with falls differed between control ( n = 87 ) and intervention ( n = 67 ) units ( P=.02 ) . Site-adjusted fall rates were significantly higher in control units ( 4.18 [ 95 % confidence interval { CI } , 3.45 - 5.06 ] per 1000 patient-days ) than in intervention units ( 3.15 [ 95 % CI , 2.54 - 3.90 ] per 1000 patient-days ; P = .04 ) . The FPTK was found to be particularly effective with patients aged 65 years or older ( adjusted rate difference , 2.08 [ 95 % CI , 0.61 - 3.56 ] per 1000 patient-days ; P = .003 ) . No significant effect was noted in fall-related injuries . CONCLUSION The use of a fall prevention tool kit in hospital units compared with usual care significantly reduced rate of falls . TRIAL REGISTRATION clinical trials.gov Identifier : NCT00675935 The present study examined the clinical efficacy of a bed alarm system in reducing falls from bed on a geriatric evaluation and treatment unit . A nine-month case-controlled study was design ed , in which 70 patients ( 60 women , 10 men ; mean age 84 years , range 67 - 97 years ) at increased risk for bed falls were r and omly assigned to either an experimental or a control group . Subjects in the experimental group ( n = 35 ) received a bed alarm system and those in the control group ( n = 35 ) did not . Outcome measures included bed falls , performance of the bed alarm system , and staff attitudes toward the use of the system . Although results failed to demonstrate a statistical difference in bed falls between the experimental ( n = 1 ) and control ( n = 4 ) groups ( p = 1.00 ) , there was a clinical trend toward reduced falls in the experimental group . The system functioned properly , activating an alarm in all instances when patients were transferring from bed , and with the exception of one case , nurses could respond in a timely fashion to assist patients and prevent bed falls . The system did not produce any adverse effects in patients , nor did the device interfere with the rendering of medical care . The system was well accepted by patients , families , and nurses . These data suggest that bed alarm systems are beneficial in guarding against bed falls and are an acceptable method of preventing falls Background Falls are the leading cause of injury-related deaths in the aging population .  Electronic medical record ( EMR ) systems can identify at-risk patients and enable interventions to decrease risk factors for falls . Objective The objectives of this study were to evaluate an EMR-based intervention to reduce overall medication use , psychoactive medication use , and occurrence of falls in an ambulatory elderly population at risk for falls . Design Prospect i ve , r and omized by clinic site . Patients / Participants Six-hundred twenty community-dwelling patients over 70 at risk for falls based on age and medication use . Interventions A st and ardized medication review was conducted and recommendations made to the primary physician via the EMR . Measurements and Main Results Patients were contacted to obtain self reports of falls at 3-month intervals over the 15-month period of study . Fall-related diagnoses and medication data were collected through the EMR . A combination of descriptive analyses and multivariate regression models were used to evaluate differences between the 2 groups , adjusting for baseline medication patterns and comorbidities . Although the intervention did not reduce the total number of medications , there was a significant negative relationship between the intervention and the total number of medications started during the intervention period ( p < .01 , regression estimate −0.199 ) and the total number of psychoactive medications ( p < .05 , regression estimate −0.204 . ) The impact on falls was mixed ; with the intervention group 0.38 times as likely to have had 1 or more fall-related diagnosis ( p < 
    Output:
    
agent
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Background : falls in hospitals are a major problem and contribute to substantial healthcare burden . Advances in sensor technology afford innovative approaches to reducing falls in acute hospital care . However , whether these are clinical ly effective and cost effective in the UK setting has not been evaluated . Methods : pragmatic , parallel-arm , individual r and omised controlled trial of bed and bedside chair pressure sensors using radio-pagers ( intervention group ) compared with st and ard care ( control group ) in elderly patients admitted to acute , general medical wards , in a large UK teaching hospital . Primary outcome measure number of in-patient bedside falls per 1,000 bed days . Results : 1,839 participants were r and omised ( 918 to the intervention group and 921 to the control group ) . There were 85 bedside falls ( 65 fallers ) in the intervention group , falls rate 8.71 per 1,000 bed days compared with 83 bedside falls ( 64 fallers ) in the control group , falls rate 9.84 per 1,000 bed days ( adjusted incidence rate ratio , 0.90 ; 95 % confidence interval [ CI ] , 0.66–1.22 ; P = 0.51 ) . There was no significant difference between the two groups with respect to time to first bedside fall ( adjusted hazard ratio ( HR ) , 0.95 ; 95 % CI : 0.67–1.34 ; P= 0.12 ) . The mean cost per patient in the intervention group was £ 7199 compared with £ 6400 in the control group , mean difference in QALYs per patient , 0.0001 ( 95 % CI : −0.0006–0.0004 , P= 0.67 ) . Conclusions : bed and bedside chair pressure sensors as a single intervention strategy do not reduce in-patient bedside falls , time to first bedside fall and are not cost-effective in elderly patients in acute , general medical wards in the UK . Trial registration : is rct n.org identifier : IS RCT N44972300 BACKGROUND Falls are a predominant problem in our aging society , often leading to severe somatic and psychological consequences , and having an incidence of about 30 % in the group of persons aged 65 years or above . In order to identify persons at risk , many assessment tools and tests have been developed , but most of these have to be conducted in a supervised setting and are dependent on an expert rater . OBJECTIVES The overall aim of our research work is to develop an objective and unobtrusive method to determine individual fall risk based on the use of motion sensor data . The aims of our work for this paper are to derive a fall risk model based on sensor data that may potentially be measured during typical activities of daily life ( aim # 1 ) , and to evaluate the result ing model with data from a one-year follow-up study ( aim # 2 ) . METHODS A sample of n = 119 geriatric in patients wore an accelerometer on the waist during a Timed ' Up & Go ' test and a 20 m walk .  Fifty patients were included in a one-year follow-up study , assessing fall events and scoring average physical activity at home in telephone interviews . The sensor data were processed to extract gait and dynamic balance parameters , from which four fall risk models -- two classification trees and two logistic regression models -- were computed : models CT#1 and SL#1 using accelerometer data only , models CT#2 and SL#2 including the physical activity score . The risk models were evaluated in a ten-times tenfold cross-validation procedure , calculating sensitivity ( SENS ) , specificity ( SPEC ) , positive and negative predictive values ( PPV , NPV ) , classification accuracy , area under the curve ( AUC ) and the Brier score . RESULTS Both classification trees show a fair to good performance ( models CT#1/CT#2 ) : SENS 74%/58 % , SPEC 96%/82 % , PPV 92%/ 74 % , NPV 77%/82 % , accuracy 80%/78 % , AUC 0.83/0.87 and Brier scores 0.14/0.14 . The logistic regression models ( SL#1/SL#2 ) perform worse : SENS 42%/58 % , SPEC 82%/ 78 % , PPV 62%/65 % , NPV 67%/72 % , accuracy 65%/70 % , AUC 0.65/0.72 and Brier scores 0.23/0.21 . CONCLUSIONS Our results suggest that accelerometer data may be used to predict falls in an unsupervised setting . Furthermore , the parameters used for prediction are measurable with an unobtrusive sensor device during normal activities of daily living . These promising results have to be vali date d in a larger , long-term prospect i ve trial Objective To determine the efficacy of a targeted multifactorial falls prevention programme in elderly care wards with relatively short lengths of stay . Design Cluster r and omised trial . Setting 24 elderly care wards in 12 hospitals in Sydney , Australia . Participants 3999 patients , mean age 79 years , with a median hospital stay of seven days . Interventions A nurse and physiotherapist each worked for 25 hours a week for three months in all intervention wards . They provided a targeted multifactorial intervention that included a risk assessment of falls , staff and patient education , drug review , modification of bedside and ward environments , an exercise programme , and alarms for selected patients . Main outcome measure Falls during hospital stay . Results Intervention and control wards were similar at baseline for previous rates of falls and individual patient characteristics . Overall , 381 falls  occurred during the study . No difference was found in fall rates during follow-up between intervention and control wards : respectively , 9.26 falls per 1000 bed days and 9.20 falls per 1000 bed days ( P=0.96 ) . The incidence rate ratio adjusted for individual lengths of stay and previous fall rates in the ward was 0.96 ( 95 % confidence interval 0.72 to 1.28 ) . Conclusion A targeted multifactorial falls prevention programme was not effective among older people in hospital wards with relatively short lengths of stay . Trial registration Australian New Zeal and Clinical Trials Registry ACTRNO 12605000467639 Background Falls are a major cause of morbidity and mortality in dementia , but there have been no prospect i ve studies of risk factors for falling specific to this patient population , and no successful falls intervention/prevention trials . This prospect i ve study aim ed to identify modifiable risk factors for falling in older people with mild to moderate dementia . Methods and Findings 179 participants aged over 65 years were recruited from outpatient clinics in the UK ( 38 Alzheimer 's disease ( AD ) , 32 Vascular dementia ( VAD ) , 30 Dementia with Lewy bodies ( DLB ) , 40 Parkinson 's disease with dementia ( PDD ) , 39 healthy controls ) . A multifactorial assessment of baseline risk factors was performed and fall diaries were completed prospect ively for 12 months . Dementia participants experienced nearly 8 times more incident falls ( 9118/1000 person-years ) than controls ( 1023/1000 person-years ; incidence density ratio : 7.58 , 3.11–18.5 ) . In dementia , significant univariate predictors of sustaining at least one fall included diagnosis of Lewy body disorder ( proportional hazard ratio ( HR ) adjusted for age and sex : 3.33 , 2.11–5.26 ) , and history of falls in the preceding 12 months ( HR : 2.52 , 1.52–4.17 ) . In multivariate analyses , significant potentially modifiable predictors were symptomatic orthostatic hypotension ( HR : 2.13 , 1.19–3.80 ) , autonomic symptom score ( HR per point 0–36 : 1.055 , 1.012–1.099 ) , and Cornell depression score ( HR per point 0–40 : 1.053 , 1.01–1.099 ) . Higher levels of physical activity were protective ( HR per point 0–9 : 0.827 , 0.716–0.956 ) . Conclusions The management of symptomatic orthostatic hypotension , autonomic symptoms and depression , and the encouragement of physical activity may provide the core elements for the most fruitful strategy to reduce falls in people with dementia . R and omised controlled trials to assess such a strategy are a priority CONTEXT Falls cause injury and death for persons of all ages , but risk of falls increases markedly with age . Hospitalization further increases risk , yet no evidence exists to support short-stay hospital-based fall prevention strategies to reduce patient  falls . OBJECTIVE To investigate whether a fall prevention tool kit ( FPTK ) using health information technology ( HIT ) decreases patient falls in hospitals . DESIGN , SETTING , AND PATIENTS Cluster r and omized study conducted January 1 , 2009 , through June 30 , 2009 , comparing patient fall rates in 4 urban US hospitals in units that received usual care ( 4 units and 5104 patients ) or the intervention ( 4 units and 5160 patients ) . INTERVENTION The FPTK integrated existing communication and workflow patterns into the HIT application . Based on a valid fall risk assessment scale completed by a nurse , the FPTK software tailored fall prevention interventions to address patients ' specific determinants of fall risk . The FPTK produced bed posters composed of brief text with an accompanying icon , patient education h and outs , and plans of care , all communicating patient-specific alerts to key stakeholders . MAIN OUTCOME MEASURES The primary outcome was patient falls per 1000 patient-days adjusted for site and patient care unit . A secondary outcome was fall-related injuries . RESULTS During the 6-month intervention period , the number of patients with falls differed between control ( n = 87 ) and intervention ( n = 67 ) units ( P=.02 ) . Site-adjusted fall rates were significantly higher in control units ( 4.18 [ 95 % confidence interval { CI } , 3.45 - 5.06 ] per 1000 patient-days ) than in intervention units ( 3.15 [ 95 % CI , 2.54 - 3.90 ] per 1000 patient-days ; P = .04 ) . The FPTK was found to be particularly effective with patients aged 65 years or older ( adjusted rate difference , 2.08 [ 95 % CI , 0.61 - 3.56 ] per 1000 patient-days ; P = .003 ) . No significant effect was noted in fall-related injuries . CONCLUSION The use of a fall prevention tool kit in hospital units compared with usual care significantly reduced rate of falls . TRIAL REGISTRATION clinical trials.gov Identifier : NCT00675935 The present study examined the clinical efficacy of a bed alarm system in reducing falls from bed on a geriatric evaluation and treatment unit . A nine-month case-controlled study was design ed , in which 70 patients ( 60 women , 10 men ; mean age 84 years , range 67 - 97 years ) at increased risk for bed falls were r and omly assigned to either an experimental or a control group . Subjects in the experimental group ( n = 35 ) received a bed alarm system and those in the control group ( n = 35 ) did not . Outcome measures included bed falls , performance of the bed alarm system , and staff attitudes toward the use of the system . Although results failed to demonstrate a statistical difference in bed falls between the experimental ( n = 1 ) and control ( n = 4 ) groups ( p = 1.00 ) , there was a clinical trend toward reduced falls in the experimental group . The system functioned properly , activating an alarm in all instances when patients were transferring from bed , and with the exception of one case , nurses could respond in a timely fashion to assist patients and prevent bed falls . The system did not produce any adverse effects in patients , nor did the device interfere with the rendering of medical care . The system was well accepted by patients , families , and nurses . These data suggest that bed alarm systems are beneficial in guarding against bed falls and are an acceptable method of preventing falls Background Falls are the leading cause of injury-related deaths in the aging population .  Electronic medical record ( EMR ) systems can identify at-risk patients and enable interventions to decrease risk factors for falls . Objective The objectives of this study were to evaluate an EMR-based intervention to reduce overall medication use , psychoactive medication use , and occurrence of falls in an ambulatory elderly population at risk for falls . Design Prospect i ve , r and omized by clinic site . Patients / Participants Six-hundred twenty community-dwelling patients over 70 at risk for falls based on age and medication use . Interventions A st and ardized medication review was conducted and recommendations made to the primary physician via the EMR . Measurements and Main Results Patients were contacted to obtain self reports of falls at 3-month intervals over the 15-month period of study . Fall-related diagnoses and medication data were collected through the EMR . A combination of descriptive analyses and multivariate regression models were used to evaluate differences between the 2 groups , adjusting for baseline medication patterns and comorbidities . Although the intervention did not reduce the total number of medications , there was a significant negative relationship between the intervention and the total number of medications started during the intervention period ( p < .01 , regression estimate −0.199 ) and the total number of psychoactive medications ( p < .05 , regression estimate −0.204 . ) The impact on falls was mixed ; with the intervention group 0.38 times as likely to have had 1 or more fall-related diagnosis ( p < 
    Output:
    