scholarly journals Predictive Model of Gait Recovery at One Month after Hip Fracture from a National Cohort of 25,607 Patients: The Hip Fracture Prognosis (HF-Prognosis) Tool

2021 ◽  
Vol 18 (7) ◽  
pp. 3809
Author(s):  
Cristina González de Villaumbrosia ◽  
Pilar Sáez López ◽  
Isaac Martín de Diego ◽  
Carmen Lancho Martín ◽  
Marina Cuesta Santa Teresa ◽  
...  
Keyword(s):  
Hip Fracture ◽  
Predictive Model ◽  
Weight Bearing ◽  
Individual Characteristics ◽  
Predicted Probability ◽  
National Cohort ◽  
Probability Threshold ◽  
Anesthetic Risk ◽  
Validation Set ◽  
Operative Delay

The aim of this study was to develop a predictive model of gait recovery after hip fracture. Data was obtained from a sample of 25,607 patients included in the Spanish National Hip Fracture Registry from 2017 to 2019. The primary outcome was recovery of the baseline level of ambulatory capacity. A logistic regression model was developed using 40% of the sample and the model was validated in the remaining 60% of the sample. The predictors introduced in the model were: age, prefracture gait independence, cognitive impairment, anesthetic risk, fracture type, operative delay, early postoperative mobilization, weight bearing, presence of pressure ulcers and destination at discharge. Five groups of patients or clusters were identified by their predicted probability of recovery, including the most common features of each. A probability threshold of 0.706 in the training set led to an accuracy of the model of 0.64 in the validation set. We present an acceptably accurate predictive model of gait recovery after hip fracture based on the patients’ individual characteristics. This model could aid clinicians to better target programs and interventions in this population.

scholarly journals Identification of hip fracture patients at risk for postoperative mobilisation complications via handgrip strength assessment

2021 ◽  
Author(s):  
Johannes Gleich ◽  
Daniel Pfeufer ◽  
Alexander M. Keppler ◽  
Stefan Mehaffey ◽  
Julian Fürmetz ◽  
...  
Keyword(s):  
Hip Fracture ◽  
Gait Speed ◽  
Handgrip Strength ◽  
Weight Bearing ◽  
Proximal Femur Fracture ◽  
Term Outcome ◽  
Long Term Outcome ◽  
Strength Assessment ◽  
Positive Correlation ◽  
Prospective Study Design

Abstract Introduction Treatment of older adult hip fracture patients can be challenging and requires early postoperative mobilisation to prevent complications. Simple clinical tools to predict mobilisation/weight-bearing difficulties after hip fracture surgery are scarcely available and analysis of handgrip strength could be a feasible approach. In the present study, we hypothesised that patients with reduced handgrip strength show incapability to follow postoperative weight-bearing instructions. Materials and methods Eighty-four patients aged ≥ 65 years with a proximal femur fracture (trochanteric, n = 45 or femoral neck, n = 39), who were admitted to a certified orthogeriatric center, were consecutively enrolled in a prospective study design. Five days after surgery (intramedullary nailing or arthroplasty), a standardised assessment of handgrip strength and a gait analysis (via insole forcesensors) was performed. Results Handgrip strength showed positive correlation with average peak force during gait on the affected limb (0.259), postoperative Parker Mobility Score (0.287) and Barthel Index (0.306). Only slight positive correlation was observed with gait speed (0.157). These results were congruent with multivariate regression analysis. Conclusion Assessment of handgrip strength is a simple and reliable tool for early prediction of postoperative mobilisation complications like the inability to follow weight-bearing instructions in older hip fracture patients. Follow-up studies should evaluate if these findings also match with other fracture types and result in personalised adjustment of current aftercare patterns. In addition, efforts should be made to combine objectively collected data as handgrip strength or gait speed in a prediction model for long-term outcome of orthogeriatric patients.

Predictive Models for Post-operative Nausea and Vomiting in Patients Using Patient-controlled Analgesia

2007 ◽  
Vol 35 (4) ◽  
pp. 497-507 ◽  
Author(s):  
YY Lee ◽  
KH Kim ◽  
YH Yom
Keyword(s):  
Predictive Model ◽  
Oral Fluid ◽  
Individual Characteristics ◽  
Nausea And Vomiting ◽  
Patient Controlled Analgesia ◽  
Related Data ◽  
Post Operative Pain ◽  
Post Operation ◽  
History Of ◽  
Post Operative Nausea

This study identified predictive factors for post-operative nausea and vomiting (PONV) in patients using patient-controlled analgesia (PCA) and developed five predictive model pathways to calculate the probability of PONV using decision tree analysis. The sample consisted of 1181 patients using PCA. Data were collected using: a specifically designed check-off form to collect patient-, surgery-, anaesthesia- and post-operation-related data; the Beck Anxiety Inventory® to measure pre-operative anxiety; and a visual analogue scale, to measure post-operative pain. The incidence of PONV was 27.7%. Nine factors were highly predictive of PONV in our five model pathways: gender, obesity, anxiety, history of previous PONV, history of motion sickness, inhalation of nitrous oxide during operation, use of inhalational agents, starting oral fluid/food intake after operation, and post-operative pain. With these five predictive model pathways, we can predict the probability of PONV in an individual patient according to their individual characteristics.

scholarly journals A model for predicting carotid instability plaque in high risk group of stroke individuals

2019 ◽  
Author(s):  
Junxiong Yin ◽  
Chuanyong Yu ◽  
Hongxing Liu ◽  
Mingyang Du ◽  
Feng Sun ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Predictive Model ◽  
Doppler Ultrasound ◽  
Scoring System ◽  
Risk Group ◽  
High Risk Group ◽  
High Risk Population ◽  
Auc Value ◽  
Validation Set

Abstract Objective: To establish a predictive model of carotid vulnerable plaque through systematic screening of high-risk population for stroke.Patients and methods: All community residents who participated in the screening of stroke high-risk population by the China National Stroke Screening and Prevention Project (CNSSPP). A total of 19 risk factors were analyzed. Individuals were randomly divided into Derivation Set group and Validation Set group. According to carotid ultrasonography, the derivation set group patients were divided into instability plaque group and non-instability plaque group. Univariate and multivariable logistic regression were taken for risk factors. A predictive model scoring system were established by the coefficient. The AUC value of both derivation and validation set group were used to verify the effectiveness of the model.Results: A total of 2841 high-risk stroke patients were enrolled in this study, 266 (9.4%) patients were found instability plaque. According to the results of Doppler ultrasound, Derivation Set group were divided into instability plaque group (174 cases) and non-instability plaque group (1720 cases). The independent risk factors for carotid instability plaque were: male (OR 1.966, 95%CI 1.406-2.749)，older age (50-59, OR 6.012, 95%CI 1.410-25.629; 60-69, OR 13.915, 95%CI 3.381-57.267;≥70, OR 31.267, 95%CI 7.472-130.83) , married(OR 1.780, 95%CI 1.186-2.672)，LDL-c(OR 2.015, 95%CI 1.443-2.814), and HDL-C(OR 2.130, 95%CI 1.360-3.338). A predictive scoring system was created, range 0-10. The cut-off value of prediction model score is 6.5. The AUC value of derivation and validation set group were 0.738 and 0.737.Conclusion：For a high risk group of stroke individual, We provide a model that could distinguishing those who have a high probability of having carotid instability plaque. When resident’s predictive model score exceeds 6.5, the incidence of carotid instability plaque is high, carotid artery Doppler ultrasound would be checked immediately. This model can be helpful in the primary prevention of stroke.

scholarly journals The A-test: Assessment of functional recovery during early rehabilitation of patients in an orthopedic ward - content, criterion and construct validity

2014 ◽  
Vol 71 (8) ◽  
pp. 715-722 ◽  
Author(s):  
Aleksandra Vukomanovic ◽  
Aleksandar Djurovic ◽  
Zoran Popovic ◽  
Vesna Pejovic
Keyword(s):  
Hip Fracture ◽  
Construct Validity ◽  
Functional Recovery ◽  
Test Score ◽  
Weight Bearing ◽  
Hip Osteoarthritis ◽  
Early Rehabilitation ◽  
Ordinal Scale ◽  
Test Results ◽  
Orthopedic Ward

Background/Aim. The A-test was designed for assessment of functional recovery during early rehabilitation of patients in an orthopedic ward. This performance-based test consists of 10 items for assessing basic activities by a six level ordinal scale (0-5). Total scores can range from 0 to 50, i.e. from inability to perform any activity despite the help of therapists to complete independence and safety in performing all activities. The aim of this study was to examine the A-test validity. Methods. This prospective study was conducted in an orthopedic ward and included 120 patients [60 patients with hip osteoarthritis that underwent arthroplasty and 60 surgically treated patients with hip fracture (HF)] during early inpatient rehabilitation (1st-5th day). Validity was examined through 3 aspects: content validity - floor and ceiling effect, range, skewness; criterion validity - concurrent validity [correlation with the University of Iowa Level of Assistance Scale (ILAS) for patients with hip osteoarthritis, and with the Cumulated Ambulation Score (CAS) for patients with HF, Spearman rank correlation] and predictive validity [the New Mobility Score (NMS) 4 weeks after surgery, Mann-Whitney U test]; construct validity - 4 hypotheses: 1) on the fifth day of rehabilitation in patients underwent arthroplasty due to hip osteoarthritis, the A-test results will strongly correlate with those of ILAS, while the correlation with the Harris hip score will be less strong; 2) in patients with HF, the A-test results will be significantly better in those with allowed weight bearing as compared to patients whom weight bearing is not allowed while walking; 3) results of the A-test will be significantly better in patients with hip osetoarthritis than in those with HF; 4) the A-test results will be significantly better in patients younger than 65 years than in those aged 65 years and older. Results. The obtained results were: low floor (1%) and ceiling (2%) effect, range 0-50, skewness 0.57, strong correlation with ILAS for the patients with hip osteoarthritis (r = -0.97, p = 0.000) and with CAS for the patients with hip fracture (r = 0.91, p = 0.000) The patients with the A-test score 35 and more on the fifth day of rehabilitation (n = 46, Md = 4) had significantly higher NMS rank 4 weeks after surgery than the patients with the A-test score less than 35 (n = 59, Md = 2), (U = 379, z = -6.47, p = 0.000, r = 0.63). All 4 hypotheses were confirmed. Conclusion. The A-test is simple and valid instrument for everyday evaluation of pace and degree of functional recovery during early rehabilitation of patients surgically treated in an orthopedic ward.

Operative delay and mortality in elderly patients with hip fracture: an observational study

2013 ◽  
Vol 24 (5) ◽  
pp. 783-788 ◽  
Author(s):  
Luigi de Palma ◽  
Marco Torcianti ◽  
Leonard Meco ◽  
Alessandro Catalani ◽  
Mario Marinelli
Keyword(s):  
Hip Fracture ◽  
Observational Study ◽  
Elderly Patients ◽  
Operative Delay

Inability of Older Adult Patients with Hip Fracture to Maintain Postoperative Weight-Bearing Restrictions

2018 ◽  
Vol 100 (11) ◽  
pp. 936-941 ◽  
Author(s):  
Christian Kammerlander ◽  
Daniel Pfeufer ◽  
Leonard Adolf Lisitano ◽  
Stefan Mehaffey ◽  
Wolfgang Böcker ◽  
...  
Keyword(s):  
Hip Fracture ◽  
Older Adult ◽  
Weight Bearing ◽  
Adult Patients

scholarly journals Development and Validation of a Risk Prediction Model of Linezolid-induced Thrombocytopenia in Elderly Patients

2021 ◽  
Author(s):  
Yan Qin ◽  
Zhe Chen ◽  
Shuai Gao ◽  
Ming Kun Pan ◽  
Yu Xiao Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Elderly Patients ◽  
Predictive Model ◽  
Bacterial Infections ◽  
Demographic Data ◽  
Multivariate Logistic Regression Analysis ◽  
Platelet Counts ◽  
Linezolid Therapy ◽  
Validation Set ◽  
Development And Validation

Abstract Background Linezolid is an oxazolidinone antimicrobial agent developed for treating multi-drug-resistant gram-positive bacterial infections. Objective This study aimed at investigating risk factors of linezolid (LI)-induced thrombocytopenia (LI-TP) and establishing a risk predictive model for LI-TP.Setting ZhongShan Hospital, FuDan University, China. Method A retrospective study was performed in patients aged ≥ 65 years receiving linezolid therapy from January 2015 to April 2021. Clinical characteristics and demographic data were collected and compared between patients with LI-TP and those without.Main outcome measures Incidence and risk factors of LI-TP in elderly patients.Results A total of 343 inpatients were included as the train set from January 2015 to August 2020. Among them, 67 (19.5%) developed LI-TP. Multivariate logistic regression analysis revealed that baseline platelet counts < 150×109·L-1 (OR=3.576; P< 0.001), age ≥ 75 years (OR=2.258; P=0.009), eGFR< 60 mL·(min·1.73m2)-1 (OR=2.553; P=0.002), duration of linezolid therapy ≥ 10 d (OR=3.218; P<0.001), ICU admittance (OR=2.682; P=0.004), and concomitant with piperacillin-tazobactam (PTZ) (OR=3.863; P=0.006) were independent risk factors for LI-TP. The risk predictive model was established and exhibited a moderate discriminative power, with an AUC of 0.795 [95%CI 0.740-0.851] and 0.849 [95%CI 0.760-0.939] in train set (n=343) and validation set (n=90), respectively.Conclusion The risk factors of LI-TP in elderly patients were duration of linezolid therapy, age, eGFR, ICU admittance, baseline platelet counts, and concomitant with PTZ. A risk predictive model based on these risk factors may be useful to identify patients with high risk of LI-TP.

Weight Bearing After Hip Fracture: A Prospective Series of 596 Geriatric Hip Fracture Patients

1996 ◽  
Vol 10 (8) ◽  
pp. 526-530 ◽  
Author(s):  
Kenneth J. Koval ◽  
Kevin D. Friend ◽  
Gina B. Aharonoff ◽  
Joseph D. Zuckerman
Keyword(s):  
Hip Fracture ◽  
Weight Bearing ◽  
Geriatric Hip Fracture
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