Abstract
Objective
This study aims to assess the incidence of postoperative delirium in elderly patients with hip fractures under the Unaccompanied- Care model and to explore its risk factors.
Methods
This retrospective observational study prospectively included elderly patients with hip fractures who were admitted to the Trauma Department of our hospital from November 2024 to May 2025, managed under the Unaccompanied-Care nursing model, and underwent surgical treatment. We retrospectively analyzed the patients’ baseline data, blood indicators, and surgery-related data for data analysis. Univariate and multivariate logistic regression analyses were used to identify risk factors associated with delirium in the perioperative period.
Results
A total of 138 patients were included, of whom 35 (25.36%) developed delirium. The incidence of delirium was 2.17% (3 cases) preoperatively, 6.52% (9 cases) within 6 h postoperatively, 10.14% (14 cases) within 1 day postoperatively, 4.35% (6 cases) on postoperative day 2, and 2.17% (3 cases) on postoperative day 3. Multivariate analysis showed that mild visual impairment (OR = 15.74, 95% CI: 2.53–97.29, p = 0.003), severe visual impairment (OR = 9.68, 95% CI: 5.20–18.30, p = 0.002); mild hearing impairment (OR = 7.09, 95% CI: 1.23–40.74, p = 0.028), moderate hearing impairment (OR = 6.43, 95% CI: 1.80–51.41, p = 0.031), severe hearing impairment (OR = 16.59, 95% CI: 1.76–156.61, p = 0.014), and hemoglobin (OR = 1.95, 95% CI: 1.91–5.99, p = 0.037) were independent risk factors for delirium.
Conclusion
Although the Unaccompanied-Care model shows specific effects in the nursing of elderly patients with hip fractures, the incidence of delirium remains high. Sensory dysfunction and low hemoglobin levels are important risk factors for delirium.
Keywords: Unaccompanied Care, Delirium, Hip fractures, Risk factors
Introduction
Hip fractures represent a prevalent and severe traumatic injury among the elderly, with nearly 90% occurring in individuals aged 65 years and above [1]. Driven by global population aging, the incidence is expected to rise steadily, with projections estimating up to 7.3 million cases by 2050, and potentially as many as 21.3 million [2]. Previous studies have shown that the mortality rate of elderly patients with hip fractures within one year after surgery is as high as 15.7 − 36% [3–5]. Although surgical treatment is the preferred option for this disease [6], delirium in the perioperative period, as the most common neuropsychiatric complication, can significantly affect the prognosis of patients [7]. Notably, geriatric hip fracture patients typically present with multiple comorbidities [8, 9]. This population inherently carries elevated delirium risk, which surgical intervention may further exacerbate. Clinical observations have found that hip fracture patients with delirium often show more extended hospital stays, poorer functional recovery, and higher complication rates.
As an acute disturbance of consciousness, delirium after hip fracture in the elderly is mainly characterized by attention deficits and fluctuations in cognitive function, with its incidence in hip fracture surgery reaching 15-56% [10], which is significantly higher than that in the general hospitalized elderly population. A large number of clinical studies have confirmed that the occurrence of delirium in the perioperative period of elderly patients with hip fractures not only significantly hinders their postoperative functional recovery and reduces their ability to live independently but also prolongs the bedridden time, thereby increasing the risk of death [11–13]. The occurrence of delirium in the perioperative period of elderly patients with hip fractures not only significantly hinders their postoperative functional recovery and reduces their ability to live independently but also prolongs the bedridden time, thereby increasing the risk of death. Therefore, clinicians need to be highly vigilant and actively intervene, providing comprehensive perioperative treatment to reduce the occurrence of mortality and complications [14]. Despite decades of extensive research, the prognostic significance of perioperative delirium for the long-term survival of elderly patients remains an unresolved issue [15].
In recent years, the Unaccompanied-Care model, as an innovative nursing model, has increasingly become the focus of clinical research. The core of this model is that after the patient is admitted to the hospital, all medical, nursing, and daily care needs are undertaken by professional medical staff and nursing aides, completely replacing family accompaniment. The aim is to provide a standardized, high-quality nursing service. The implementation of this innovative nursing model is in line with the development trend of the aging society.
Existing studies have shown that applying the Unaccompanied-Care model has positive effects in reducing the risk of cross-infection in hospitals, optimizing the allocation of human resources, and improving patient and family satisfaction [16]. However, the potential drawbacks of this model cannot be ignored, especially the possibility that patients may experience negative emotions due to the lack of emotional support from family members, which may be a potential inducement for perioperative delirium. At the same time, the standardized nursing procedures and early systematic rehabilitation interventions that are unique to this model may also indirectly affect the occurrence of delirium by changing the perioperative management pathway. It is worth noting that current domestic and international research on perioperative delirium mainly focuses on exploring the risk factors under the traditional accompaniment model [17, 18], and there is no clear consensus on how the Unaccompanied-Care model affects the occurrence of delirium. Existing studies lack high-quality, evidence-based medical evidence to systematically evaluate the impact of the Unaccompanied-Care model on the incidence and risk factors of perioperative delirium. This limits the standardized application and promotion of this model in clinical practice to some extent.
Research on this model in our country is still exploratory, and its application in clinical nursing is gradually being promoted. As patients transition from the traditional model with family accompaniment to the model without family accompaniment, the impact of this shift in nursing models on the occurrence of perioperative delirium is still unclear. Therefore, this study aims to retrospectively analyze patients who received the Unaccompanied-Care nursing model from November 2024 to May 2025 to assess the incidence of perioperative delirium and further explore the key factors affecting the occurrence of perioperative delirium through multivariate logistic regression analysis, with the hope of providing a scientific basis for the clinical application of the Unaccompanied-Carenursing model.
Materials and methods
Research design
This study is a retrospective observational study that included elderly patients with hip fractures who were admitted to the Department of Trauma of our hospital from November 2024 to May 2025, managed under the Unaccompanied-Care nursing model, and underwent surgical treatment. The study followed the STROBE reporting guidelines [19] and was approved by the Ethics Committee of Fuzhou Second General Hospital (approval number: 2025197). According to the revised Declaration of Helsinki in 2013, the data in this study was anonymized. Due to its retrospective nature and the absence of additional harm to participants, informed consent was not required.
Inclusion and exclusion criteria
Inclusion Criteria:1. Age ≥ 65 years;2. A clear diagnosis of unilateral hip fracture (including femoral neck fracture or intertrochanteric fracture);3. Those who had trauma within ≤ 2 weeks and underwent surgical treatment;4. Patients with complete clinical data and conditions for follow-up (outpatient or telephone follow-up).
Exclusion Criteria:1. Previous diagnosis of neurological or psychiatric diseases, including but not limited to severe mental disorders (such as schizophrenia) and patients with pre-injury diagnosed delirium;2. Severe dysfunction of the heart, liver, or kidneys;3. Presence of alcohol or drug dependence;4. Incomplete clinical data or inability to complete follow-up.
Nursing procedures under the Unaccompanied Care model
The Unaccompanied -Caremodel innovatively adopts a dual management mechanism involving the hospital and a professional nursing company. Establishing a standardized nursing team comprising “one nurse + one nursing aide” achieves professional and standardized Unaccompanied Care management. The core process of this model covers seamless full-process management from admission to discharge.
During the admission preparation phase, the physician completes the explanation of the service model and obtains informed consent. The nursing team prepares personalized beds in advance and implements a “triple verification” system (patient information, medical orders, and items). The inpatient service phase includes basic care and perioperative management: the nursing aide executes standardized daily care (guided by ADL scores), implements the “three checks and seven verifications” nursing system, and establishes a dual-person cross-patrol mechanism (level one care once per hour, level two care once every two hours). In perioperative management, the preoperative phase implements the “five elements of prehabilitation” (nutrition, exercise, psychology, smoking, alcohol cessation, sleep), the intraoperative phase executes the surgical safety checklist (Time-out system), and the postoperative phase initiates the “early rehabilitation trilogy” (in-bed activities, sitting-up training, and out-of-bed walking). The discharge transition phase implements the “1 + 1 + 1” discharge plan (one health education session, one follow-up plan, and one satisfaction survey). It executes the “triple inventory” system for items (personal belongings, medical items, and medications). This model ensures high-quality nursing services throughout the process by establishing standardized operating procedures (SOPs), clarifying graded nursing standards, and implementing a quality monitoring system (Fig. 1).
Fig. 1.
Standardized operating procedures under the Unaccompanied-Caremodel
Observation indicators
Data collection methods
Data in this study were prospectively collected. The general information included demographic characteristics such as gender, age, body mass index (BMI), education level, marital status, living situation, and financial status. Clinical factors involved pre-existing medical conditions, side of the fracture, mechanism of injury, surgical duration, blood loss, type of surgery, and fracture type. Laboratory test indicators included white blood cells, red blood cells, hemoglobin, platelets, sodium, potassium, chloride, creatinine, blood urea nitrogen, alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin, fasting blood glucose, pH value, arterial oxygen partial pressure (PaO₂), arterial carbon dioxide partial pressure (PaCO₂), lactate level, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and serum albumin.
Primary observation indicators
Delirium Assessment: The Nursing Delirium Screening Scale (Nu-DESC) [20] is a rapid, straightforward delirium screening tool suitable for perioperative and intensive care patients. The scale consists of five assessment items: disorientation, abnormal behavior, abnormal verbal communication, illusions/hallucinations, and psychomotor retardation. Each item is scored from 0 to 2 based on the severity of symptoms, with a total score ranging from 0 to 10. A score of ≥ 1–2 is generally used as the positive screening criterion for delirium.
Secondary observation indicators
These include the Activity of Daily Living Scale, Snellen chart, and audiovisual assessment.
The Activity of Daily Living Scale (ADL) is used to standardize the assessment of activities of daily living [21]. The scale comprises 10 basic items of daily living activities, each scored from 0 to 5, 0 to 10, or 0 to 15 points based on the patient’s performance, with a total score ranging from 0 to 100. The specific scoring criteria are as follows: 100 indicates complete self-care, 61–99 indicates mild dependency, 41–60 indicates moderate dependency, and ≤ 40 indicates severe dependency. The assessment should be conducted in the patient’s daily living environment and completed by medical staff who have undergone unified training through direct observation or reliable reports from family members.
Visual acuity was assessed using the international standard logarithmic visual acuity chart (Snellen chart) at a testing distance of 5 m, with the patient’s best-corrected visual acuity (with glasses) being recorded. According to the World Health Organization (WHO) criteria, visual acuity is classified as follows: ≥0.8 (or 20/25) is considered normal vision, 0.6 − 0.4 (20/30 − 20/50) is mild visual impairment, and ≤ 0.3 (20/60) is severe visual impairment. All examinations were conducted under standard lighting conditions (200–300 lx) and excluded the impact of organic eye diseases such as cataracts.
Hearing assessment was conducted using the standardized Hearing Handicap Inventory for Adults - Screening version (HHIA-S) [22]. This scale comprises 10 questions and evaluates the degree of hearing impairment in social situations through a questionnaire format. The scoring criteria are as follows: 0–8 points for normal hearing, 10–24 points for mild hearing impairment, 26–40 points for moderate hearing impairment, and 42 points or above for severe hearing impairment. The test was performed in a quiet environment (background noise < 40 dB) and was completed by the patient under the guidance of a trained professional.
Statistical analysis
Statistical analysis was performed using SPSS version 29. The occurrence of delirium was designated as the dependent variable, while the observed measurements were treated as independent variables. Continuous variables are reported as mean ± standard deviation and categorical variables are presented as percentages. Univariate analysis was conducted for each factor, and variables with a p-value < 0.05 were included in the multivariate analysis. In the multivariate model, variables with a p-value ≤ 0.05 were considered statistically significant and identified as potential complication risk factors. A 95% confidence interval was calculated, and the null hypothesis that the odds ratio (OR) equals one was tested using the Wald test.
Results
Baseline data
From November 2024 to May 2025, 145 elderly patients with hip fractures were screened, of whom seven were excluded, and 138 were included in the study(Fig. 2). There were 36 males (26.09%) and 102 females (73.91%), with a mean age of 80.21 ± 8.21 years. The average BMI was 21.69 ± 3.81 kg/m²; 62 cases (44.93%) had femoral neck fractures, and 76 cases (55.07%) had intertrochanteric fractures. There were no statistically significant differences between the two groups in terms of age (t = 0.30, P = 0.766), BMI (t = -0.44, P = 0.661), gender (χ² = 1.63, P = 0.201), education level (χ² = 0.628, P = 0.628), marital status (χ² = 0.182, P = 0.182), living situation (χ² = 1.000, P = 1.000), financial status (χ² = 0.268, P = 0.268), pre-existing chronic diseases (χ² = 5.63, P = 0.018), and medication use (χ² = 0.88, P = 0.348). These results indicate that the baseline characteristics of the two groups were balanced and comparable (Table 1).
Fig. 2.
Flowchart
Table 1.
Baseline data
| Variable | Total (n = 138) | No delirium (n = 103) | Delirium (n = 35) | Statistical value | P | |||
|---|---|---|---|---|---|---|---|---|
| Age, Mean ± SD | 80.21 ± 8.21 | 80.25 ± 8.29 | 79.00 ± 6.73 | t = 0.30 | 0.766 | |||
| BMI, Mean ± SD | 21.69 ± 3.81 | 21.60 ± 3.54 | 21.93 ± 4.57 | t=-0.44 | 0.661 | |||
| Gender, n(%) | χ²=1.63 | 0.201 | ||||||
| Female | 102 (73.91) | 79 (76.70) | 23 (65.71) | |||||
| Male | 36 (26.09) | 24 (23.30) | 12 (34.29) | |||||
| Educational level, n(%) | - | 0.628 | ||||||
| Illiterate | 60 (43.48) | 44 (42.72) | 16 (45.71) | |||||
| Primary school | 40 (28.99) | 30 (29.13) | 10 (28.57) | |||||
| Junior high school | 16 (11.59) | 13 (12.62) | 3 (8.57) | |||||
| Senior high school | 16 (11.59) | 13 (12.62) | 3 (8.57) | |||||
| University and above | 6 (4.35) | 3 (2.91) | 3 (8.57) | |||||
| Marital status, n(%) | - | 0.182 | ||||||
| Unmarried | 1 (0.72) | 1 (0.97) | 0 (0.00) | |||||
| Married | 121 (87.68) | 93 (90.29) | 28 (80.00) | |||||
| Widowed | 16 (11.59) | 9 (8.74) | 7 (20.00) | |||||
| Living situation, n(%) | - | 1.000 | ||||||
| Living alone | 1 (0.72) | 1 (0.97) | 0 (0.00) | |||||
| Living with family | 137 (99.28) | 102 (99.03) | 35 (100.00) | |||||
| Financial situation, n(%) | - | 0.268 | ||||||
| Low | 16 (11.59) | 14 (13.59) | 2 (5.71) | |||||
| Medium | 120 (86.96) | 88 (85.44) | 32 (91.43) | |||||
| High | 2 (1.45) | 1 (0.97) | 1 (2.86) | |||||
| Chronic diseases, n(%) | χ²=5.63 | 0.018 | ||||||
| NO | 32 (23.19) | 29 (28.16) | 3 (8.57) | |||||
| Yes | 106 (76.81) | 74 (71.84) | 32 (91.43) | |||||
| Type of fracture, n(%) | χ²=5.07 | 0.024 | ||||||
| Femoral neck fracture | 62 (44.93) | 52 (50.49) | 10 (28.57) | |||||
| Intertrochanteric fracture | 76 (55.07) | 51 (49.51) | 25 (71.43) | |||||
| Concomitant medications, n(%) | χ²=0.88 | 0.348 | ||||||
| NO | 132 (95.65) | 100 (97.09) | 32 (91.43) | |||||
| Yes | 6 (4.35) | 3 (2.91) | 3 (8.57) | |||||
t: t-test, χ²: Chi-square test, -: Fisher exact
SD: standard deviation
Regarding blood test parameters, the mean white blood cell count (WBC) was 10.00 ± 2.97 × 10⁹/L, the mean red blood cell count (RBC) was 3.70 ± 0.61 × 10¹²/L, the mean hemoglobin (Hb) level was 112.51 ± 17.96 g/L, and the mean platelet count (PLT) was 217.55 ± 71.11 × 10⁹/L. Comparative statistical analysis between the two patient groups revealed no significant differences in the following laboratory parameters: sodium (Na⁺) (t = 0.01, P = 0.991), potassium (K⁺) (t = -0.38, P = 0.704), chloride (Cl⁻) (t = -0.36, P = 0.723), creatinine (Cr) (t = -0.10, P = 0.922), blood urea nitrogen (BUN) (t = -1.12, P = 0.264), alanine aminotransferase (ALT) (t = -0.19, P = 0.847), aspartate aminotransferase (AST) (t = -0.74, P = 0.463), total bilirubin (TBIL) (t = -1.80, P = 0.074), fasting blood glucose (FBG) (t = 0.83, P = 0.410), blood pH (t = -1.50, P = 0.135), partial pressure of oxygen (Pa O₂) (t = 1.41, P = 0.160), and partial pressure of carbon dioxide (Pa CO₂) (t = 1.60, P = 0.112).These results indicate that there were no statistically significant differences between the two groups in these blood test parameters (Table 2).
Table 2.
Blood indicators
| Variable | Total (n = 138) | No delirium (n = 103) | Delirium (n = 35) | Statistical value | P |
|---|---|---|---|---|---|
| White blood cells, Mean ± SD | 10.00 ± 2.97 | 9.80 ± 2.79 | 10.58 ± 3.40 | t=-1.36 | 0.177 |
| Red blood cells, Mean ± SD | 3.70 ± 0.61 | 3.72 ± 0.62 | 3.64 ± 0.59 | t = 0.69 | 0.489 |
| Hemoglobin, Mean ± SD | 112.51 ± 17.96 | 112.97 ± 18.43 | 111.14 ± 16.71 | t = 0.52 | 0.605 |
| Platelets, Mean ± SD | 217.55 ± 71.11 | 212.10 ± 62.93 | 233.60 ± 90.21 | t=-1.55 | 0.123 |
| Sodium, Mean ± SD | 138.42 ± 3.47 | 138.42 ± 3.48 | 138.42 ± 3.50 | t = 0.01 | 0.991 |
| Potassium, Mean ± SD | 3.77 ± 0.50 | 3.76 ± 0.51 | 3.79 ± 0.46 | t=-0.38 | 0.704 |
| Chloride, Mean ± SD | 103.93 ± 5.05 | 103.84 ± 3.93 | 104.20 ± 7.52 | t=-0.36 | 0.723 |
| Creatinine, Mean ± SD | 69.66 ± 46.96 | 69.43 ± 50.43 | 70.33 ± 35.47 | t=-0.10 | 0.922 |
| Blood urea nitrogen, Mean ± SD | 7.77 ± 5.74 | 7.45 ± 5.03 | 8.71 ± 7.45 | t=-1.12 | 0.264 |
| ALT, Mean ± SD | 19.24 ± 16.07 | 19.09 ± 17.85 | 19.70 ± 9.20 | t=-0.19 | 0.847 |
| AST, Mean ± SD | 22.12 ± 13.37 | 21.64 ± 14.70 | 23.56 ± 8.31 | t=-0.74 | 0.463 |
| Total bilirubin, Mean ± SD | 13.67 ± 11.41 | 12.65 ± 6.34 | 16.64 ± 19.80 | t=-1.80 | 0.074 |
| Fasting blood glucose, Mean ± SD | 8.86 ± 4.44 | 9.05 ± 4.79 | 8.33 ± 3.21 | t = 0.83 | 0.410 |
| pH value, Mean ± SD | 7.45 ± 0.04 | 7.45 ± 0.04 | 7.46 ± 0.04 | t=-1.50 | 0.135 |
| PaO₂, Mean ± SD | 87.89 ± 32.08 | 90.13 ± 35.85 | 81.29 ± 15.16 | t = 1.41 | 0.160 |
| PaCO₂, Mean ± SD | 35.35 ± 4.95 | 35.74 ± 4.95 | 34.20 ± 4.83 | t = 1.60 | 0.112 |
| Lactate, Mean ± SD | 1.52 ± 1.42 | 1.54 ± 1.55 | 1.44 ± 0.95 | t = 0.36 | 0.718 |
| CRP, Mean ± SD | 36.55 ± 40.69 | 34.21 ± 38.31 | 43.41 ± 46.96 | t=-1.16 | 0.250 |
| ESR, Mean ± SD | 41.68 ± 30.35 | 40.52 ± 30.57 | 45.09 ± 29.86 | t=-0.77 | 0.444 |
| Serum albumin, Mean ± SD | 35.87 ± 4.07 | 36.13 ± 3.92 | 35.10 ± 4.45 | t = 1.30 | 0.195 |
| Serum albumin 45, Mean ± SD | 31.45 ± 3.63 | 31.75 ± 3.59 | 30.55 ± 3.66 | t = 1.70 | 0.091 |
| Hemoglobin 46, Mean ± SD | 99.70 ± 17.16 | 102.54 ± 16.10 | 91.34 ± 17.67 | t = 3.47 | < 0.001 |
t: t-test, χ²: Chi-square test, -: Fisher exact
SD: standard deviation
In this study, among all elderly patients who underwent surgery for hip fractures, 57.97% (80 cases) underwent internal fixation, while 42.03% (58 cases) underwent joint replacement surgery. Regarding intraoperative complications, 2.17% (3 cases) of patients experienced complications. Regarding postoperative complications, the proportion was 5.07% (7 cases). Additionally, the average pain index of patients after surgery was 2.56 ± 1.08. These data are detailed in Table 3.
Table 3.
Surgical-related data
| Variable | Total (n = 138) | No delirium (n = 103) | Delirium (n = 35) | Statistical value | P |
|---|---|---|---|---|---|
| Postoperative pain, Mean ± SD | 2.56 ± 1.08 | 2.37 ± 0.98 | 3.11 ± 1.18 | t=-3.36 | 0.654 |
| Type of surgery, n(%) | χ²=3.49 | 0.062 | |||
| Internal fixation | 80 (57.97) | 55 (53.40) | 25 (71.43) | ||
| Arthroplasty | 58 (42.03) | 48 (46.60) | 10 (28.57) | ||
| Intraoperative complications, n(%) | - | 1.000 | |||
| NO | 135 (97.83) | 101 (98.06) | 34 (97.14) | ||
| Yes | 3 (2.17) | 2 (1.94) | 1 (2.86) | ||
| Postoperative complications, n(%) | χ²=17.75 | < 0.001 | |||
| NO | 131 (94.93) | 103 (100.00) | 28 (80.00) | ||
| Yes | 7 (5.07) | 0 (0.00) | 7 (20.00) |
t: t-test, χ²: Chi-square test, -: Fisher exact
SD: standard deviation
Mental status assessment and prognosis
A total of 138 elderly patients with hip fractures were included in this study, of whom 35 (25.36%) developed delirium, with an average duration of delirium of 0.69 ± 1.66 days. The distribution of delirium occurrence was as follows: 2.17% (3 cases) preoperatively, 6.52% (9 cases) within 6 h postoperatively, 10.14% (14 cases) within 1 day postoperatively, 4.35% (6 cases) on postoperative day 2, and 2.17% (3 cases) on postoperative day 3.
Regarding sensory ability assessment, 87 patients (63.04%) had normal vision, 42 (30.43%) had mild visual impairment, and 9 (6.52%) had severe visual impairment; 95 patients (68.84%) had normal hearing, 17 (12.32%) had mild hearing impairment, 11 (7.97%) had moderate hearing impairment, and 15 (10.87%) had severe hearing impairment.
In terms of prognosis, the postoperative mortality rate was 2.17% (3 cases), with a delirium group mortality rate of 2.86% (1 case) and a non-delirium group mortality rate of 1.94%% (2 cases). Quality of life assessment showed that the average ADL score for all patients was 31.85 ± 6.28, with the delirium group scoring 32.38 ± 6.52 and the non-delirium group scoring 30.29 ± 5.28 (Table 4).
Table 4.
Mental status assessment and prognosis
| Variable | Total (n = 138) | No delirium (n = 103) | Delirium (n = 35) | Statistical value | P |
|---|---|---|---|---|---|
| ADL score, Mean ± SD | 31.85 ± 6.28 | 32.38 ± 6.52 | 30.29 ± 5.28 | t = 1.72 | 0.089 |
| Duration of delirium, Mean ± SD | 0.69 ± 1.66 | 0.00 ± 0.00 | 2.72 ± 2.31 | t=-6.97 | < 0.001 |
| Visual assessment, n(%) | χ²=69.53 | < 0.001 | |||
| Normal | 87 (63.04) | 85 (82.52) | 2 (5.71) | ||
| Mildly impaired | 42 (30.43) | 17 (16.50) | 25 (71.43) | ||
| Severely impaired | 9 (6.52) | 1 (0.97) | 8 (22.86) | ||
| Hearing assessment, n(%) | - | < 0.001 | |||
| Normal | 95 (68.84) | 90 (87.38) | 5 (14.29) | ||
| Mildly impaired | 17 (12.32) | 7 (6.80) | 10 (28.57) | ||
| Moderately impaired | 11 (7.97) | 4 (3.88) | 7 (20.00) | ||
| Severely impaired | 15 (10.87) | 2 (1.94) | 13 (37.14) | ||
| Deceased, n(%) | - | 0.158 | |||
| NO | 135 (97.83) | 102 (99.03) | 33 (94.29) | ||
| Yes | 3 (2.17) | 1 (0.97) | 2 (5.71) | ||
| Time of delirium onset, n(%) | - | < 0.001 | |||
| No delirium | 103 (74.64) | 103 (100.00) | 0 (0.00) | ||
| Preoperative | 3 (2.17) | 0 (0.00) | 3 (8.57) | ||
| Within 6 h postoperative | 9 (6.52) | 0 (0.00) | 9 (25.71) | ||
| One day postoperative | 14 (10.14) | 0 (0.00) | 14 (40.00) | ||
| Two days postoperative | 6 (4.35) | 0 (0.00) | 6 (17.14) | ||
| Three days postoperative | 3 (2.17) | 0 (0.00) | 3 (8.57) |
t: t-test, χ²: Chi-square test, -: Fisher exact
SD: standard deviation
Risk factor analysis of delirium
In the univariate analysis, this study identified five potential risk factors, including chronic diseases (P = 0.026), fracture type (P = 0.027), visual acuity assessment (P < 0.001), hearing assessment (P < 0.001), and hemoglobin (P < 0.001) (Table 5). Subsequently, multivariate logistic regression analysis was performed on variables with a p-value less than 0.05 in the univariate model. The results showed that in the visual acuity assessment, mild impairment (OR = 15.74, 95% CI: 2.53–97.92, p = 0.003) and severe impairment (OR = 9.68, 95% CI: 5.20–18.30, p = 0.002); in the hearing assessment, mild impairment (OR = 7.09, 95% CI: 1.23–40.74, p = 0.028), moderate impairment (OR = 6.43, 95% CI: 1.80–51.41, p = 0.031), and severe impairment (OR = 16.59, 95% CI: 1.76–156.61, p = 0.014); and hemoglobin (OR = 1.95, 95% CI: 1.91–5.99, p = 0.037) were statistically significant predictors of postoperative complications (Table 6).
Table 5.
Univariate analysis of delirium risk factors
| Variable | β | S.E | Z | P | OR (95%CI) |
|---|---|---|---|---|---|
| Gender | |||||
| Female | 1.00 (Reference) | ||||
| Male | 0.54 | 0.43 | 1.27 | 0.204 | 1.72 (0.75 ~ 3.95) |
| Educational level | |||||
| Illiterate | 1.00 (Reference) | ||||
| Primary school | -0.09 | 0.47 | -0.19 | 0.852 | 0.92 (0.37 ~ 2.29) |
| Junior high school | -0.45 | 0.70 | -0.65 | 0.518 | 0.63 (0.16 ~ 2.52) |
| Senior high school | -0.45 | 0.70 | -0.65 | 0.518 | 0.63 (0.16 ~ 2.52) |
| University and above | 1.01 | 0.87 | 1.17 | 0.243 | 2.75 (0.50 ~ 15.05) |
| Marital status | |||||
| Unmarried | 1.00 (Reference) | ||||
| Married | 14.37 | 1455.40 | 0.01 | 0.992 | 17.06 (0.01 ~ 22.34) |
| Widowed | 15.31 | 1455.40 | 0.01 | 0.992 | 44.90 (0.20 ~ 36.53) |
| Living situation | |||||
| Living alone | 1.00 (Reference) | ||||
| Living with family | 14.50 | 1455.40 | 0.01 | 0.992 | 19.12 (0.00 ~ 85.36 |
| Financial situation | |||||
| Low | 1.00 (Reference) | ||||
| Medium | 0.93 | 0.78 | 1.19 | 0.233 | 2.55 (0.55 ~ 11.82) |
| High | 1.95 | 1.60 | 1.21 | 0.225 | 7.00 (0.30 ~ 162.20) |
| Chronic diseases | |||||
| NO | 1.00 (Reference) | ||||
| Yes | 1.43 | 0.64 | 2.23 | 0.026 | 4.18 (1.19 ~ 14.72) |
| Type of fracture | |||||
| Femoral neck fracture | 1.00 (Reference) | ||||
| Intertrochanteric fracture | 0.94 | 0.42 | 2.21 | 0.027 | 2.55 (1.11 ~ 5.84) |
| Psychiatric disorders | |||||
| NO | 1.00 (Reference) | ||||
| Depression | -14.47 | 1455.40 | -0.01 | 0.992 | 0.00 (0.00 ~ Inf) |
| Anxiety | 16.66 | 1455.40 | 0.01 | 0.991 | 17273438.58 (0.00 ~ Inf) |
| Visual assessment | |||||
| Normal | 1.00 (Reference) | ||||
| Mildly impaired | 4.14 | 0.78 | 5.29 | < 0.001 | 62.50 (13.51 ~ 289.07) |
| Severely impaired | 5.83 | 1.28 | 4.56 | < 0.001 | 340.00 (27.70 ~ 4173.17) |
| Hearing assessment | |||||
| Normal | 1.00 (Reference) | ||||
| Mildly impaired | 3.25 | 0.67 | 4.82 | < 0.001 | 25.71 (6.87 ~ 96.31) |
| Moderately impaired | 3.45 | 0.78 | 4.44 | < 0.001 | 31.50 (6.87 ~ 144.48) |
| Severely impaired | 4.76 | 0.89 | 5.36 | < 0.001 | 117.00 (20.54 ~ 666.50) |
| Type of surgery | |||||
| Internal fixation | 1.00 (Reference) | ||||
| Arthroplasty | -0.78 | 0.42 | -1.84 | 0.065 | 0.46 (0.20 ~ 1.05) |
| Intraoperative complications | |||||
| NO | 1.00 (Reference) | ||||
| Yes | 0.40 | 1.24 | 0.32 | 0.750 | 1.49 (0.13 ~ 16.90) |
| Concomitant medications | |||||
| NO | 1.00 (Reference) | ||||
| Yes | 1.14 | 0.84 | 1.35 | 0.176 | 3.12 (0.60 ~ 16.26) |
| Postoperative complications | |||||
| NO | 1.00 (Reference) | ||||
| Yes | 18.87 | 1495.30 | 0.01 | 0.990 | 1.05 (11.00 ~ 20.36) |
| Age | -0.02 | 0.06 | -0.30 | 0.764 | 0.98 (0.87 ~ 1.11) |
| ADL score | -0.05 | 0.03 | -1.68 | 0.094 | 0.95 (0.89 ~ 1.01) |
| White blood cells | 0.09 | 0.06 | 1.34 | 0.179 | 1.09 (0.96 ~ 1.24) |
| Red blood cells | -0.22 | 0.32 | -0.70 | 0.487 | 0.80 (0.43 ~ 1.50) |
| Hemoglobin 18 | -0.01 | 0.01 | -0.52 | 0.602 | 0.99 (0.97 ~ 1.02) |
| Platelets | 0.00 | 0.00 | 1.52 | 0.128 | 1.00 (1.00 ~ 1.01) |
| Sodium | -0.00 | 0.06 | -0.01 | 0.991 | 1.00 (0.89 ~ 1.12) |
| Potassium | 0.15 | 0.39 | 0.38 | 0.702 | 1.16 (0.54 ~ 2.49) |
| Chloride | 0.01 | 0.04 | 0.36 | 0.722 | 1.01 (0.94 ~ 1.09) |
| Creatinine | 0.00 | 0.00 | 0.10 | 0.922 | 1.00 (0.99 ~ 1.01) |
| CRP | 0.01 | 0.00 | 1.15 | 0.250 | 1.01 (1.00 ~ 1.01) |
| ESR | 0.00 | 0.01 | 0.77 | 0.443 | 1.00 (0.99 ~ 1.02) |
| BMI | 0.02 | 0.05 | 0.44 | 0.659 | 1.02 (0.93 ~ 1.13) |
| Serum albumin | -0.06 | 0.05 | -1.30 | 0.195 | 0.94 (0.85 ~ 1.03) |
| Surgery duration | 0.00 | 0.01 | 0.56 | 0.576 | 1.00 (0.99 ~ 1.02) |
| Serum albumin | -0.09 | 0.06 | -1.68 | 0.094 | 0.91 (0.82 ~ 1.02) |
| Hemoglobin | -0.04 | 0.01 | -3.22 | 0.001 | 0.96 (0.94 ~ 0.98) |
| Blood loss | 0.00 | 0.00 | 0.56 | 0.576 | 1.00 (1.00 ~ 1.01) |
| Blood urea nitrogen | 0.03 | 0.03 | 1.07 | 0.284 | 1.03 (0.97 ~ 1.10) |
| ALT | 0.00 | 0.01 | 0.19 | 0.846 | 1.00 (0.98 ~ 1.03) |
| AST | 0.01 | 0.01 | 0.73 | 0.468 | 1.01 (0.98 ~ 1.04) |
| Total bilirubin | 0.03 | 0.02 | 1.52 | 0.129 | 1.03 (0.99 ~ 1.07) |
| Fasting blood glucose | -0.04 | 0.05 | -0.82 | 0.411 | 0.96 (0.86 ~ 1.06) |
| PaO₂ | -0.01 | 0.01 | -1.37 | 0.172 | 0.99 (0.97 ~ 1.00) |
| PaCO₂ | -0.07 | 0.04 | -1.58 | 0.115 | 0.94 (0.86 ~ 1.02) |
| Lactate | -0.06 | 0.16 | -0.36 | 0.718 | 0.94 (0.69 ~ 1.29) |
OR: Odds Ratio, CI: Confidence Interval
Table 6.
Multivariate analysis of delirium risk factors
| Variable | β | S.E | Z | P | OR (95%CI) |
|---|---|---|---|---|---|
| -1.66 | 2.55 | -0.65 | 0.514 | 0.19 (0.00 ~ 28.14) | |
| Chronic diseases | |||||
| NO | 1.00 (Reference) | ||||
| Yes | 1.87 | 1.13 | 1.66 | 0.098 | 6.49 (0.71 ~ 59.31) |
| Type of fracture | |||||
| Femoral neck fracture | 1.00 (Reference) | ||||
| Intertrochanteric fracture | 0.78 | 0.75 | 1.03 | 0.304 | 2.17 (0.50 ~ 9.55) |
| Visual assessment | |||||
| Normal | 1.00 (Reference) | ||||
| Mildly impaired | 2.76 | 0.93 | 2.95 | 0.003 | 15.74 (2.53 ~ 97.92) |
| Severely impaired | 4.57 | 1.49 | 3.06 | 0.002 | 9.68 (5.20 ~ 18.30) |
| Hearing assessment | |||||
| Normal | 1.00 (Reference) | ||||
| Mildly impaired | 1.96 | 0.89 | 2.19 | 0.028 | 7.09 (1.23 ~ 40.74) |
| Moderately impaired | 1.86 | 1.06 | 1.75 | 0.031 | 6.43 (1.80 ~ 51.41) |
| Severely impaired | 2.81 | 1.15 | 2.45 | 0.014 | 16.59 (1.76 ~ 15.61) |
| Hemoglobin | -0.05 | 0.02 | -2.08 | 0.037 | 1.95 (1.91 ~ 5.99) |
OR: Odds Ratio, CI: Confidence Interval
Discussion
This study found that the incidence of postoperative delirium in elderly patients with hip fractures was 25.36%, with delirium events mostly occurring in the postoperative period. Through multivariate logistic regression analysis, we found that sensory dysfunction (visual and hearing impairment) and low hemoglobin levels were independent predictors of delirium occurrence. These findings provide new supplementary evidence to the existing traditional risk assessment system, which mainly considers patient age and anesthesia methods [23, 24], and are worth further validation in subsequent studies.
New characteristics of delirium occurrence under the Unaccompanied-Care” model
The results of this study show that even with the standardized configuration of “one nurse + one nursing aide,” the incidence of delirium was still as high as 25.36%. This indicates that although the Unaccompanied-Care model has implemented several innovative measures in admission preparation, standardized inpatient care, and perioperative management, there is still room for optimization in meeting patients’ sensory adaptation needs. In particular, the support effect of the professional nursing team for patients with visual or hearing impairments needs to be further improved.
Risk factors and potential mechanisms of delirium in elderly patients with hip fractures
This study explored the risk factors for perioperative delirium in elderly patients with hip fractures under the Unaccompanied-Care model. The results showed that sensory dysfunction (visual and hearing impairment) and low hemoglobin levels were significant risk factors for delirium.
Mechanisms of delirium associated with sensory dysfunction
This study confirmed that sensory dysfunction (including visual and hearing impairment) is a significant independent risk factor for delirium in elderly patients with hip fractures. This finding can be explained from the neuroscience perspective: regular sensory input from the environment is crucial for maintaining cognitive brain function. Thomson et al. [25]demonstrated in their cohort study that patients with sensory dysfunction have an eightfold increased risk of developing cognitive impairment compared to the general population. Lv et al. [26] showed in a functional magnetic resonance imaging (fMRI) study that patients with hearing loss have significantly reduced neuronal activity in multiple brain regions, including the temporal, occipital, and parietal lobes.
This deprivation of sensory input can trigger a series of pathological and physiological cascades. A study by Julia et al. [27] found that when sensory input is reduced, the efficiency of information transmission in the thalamocortical projection pathway decreases, leading to prolonged integration time of sensory information.
Kirova et al. [28] patients with perceptual impairments showed cortical thinning in the anterior cingulate and middle frontal gyrus and suppression of the executive control network. They reduced working memory capacity when performing working memory tasks. In the clinical setting, these neurofunctional abnormalities are manifested as typical symptoms of delirium, including a significant increase in the error rate of time-space orientation tests and a marked shortening of attention maintenance time. It is particularly noteworthy that this sensory deprivation effect may be further amplified in an unfamiliar medical environment. Research data show that in an environmental intervention study [29], the duration of delirium was significantly reduced from 14.4 days to 7.7 days after the implementation of environmental interventions. This indicates that an unfamiliar environment not only exacerbates the effects of sensory deprivation but also increases the risk of delirium by increasing patient anxiety and restlessness.
Dual impact of hemoglobin levels
Anemia, exceptionally moderate to severe anemia, has been confirmed by several studies as an independent risk factor for postoperative delirium and cognitive impairment. First, anemia may lead to insufficient oxygen supply to the brain, thereby causing cognitive dysfunction. A study [30]conducted cognitive function tests on 61 patients undergoing surgery for uterine fibroids and found that the incidence of postoperative cognitive impairment in the moderate anemia group was significantly higher than that in the no-anemia and mild-anemia groups, at 40%, 9.52%, and 14.75%, respectively. This indicates a positive correlation between the degree of anemia and the incidence of delirium. Another Meta study [31]included 37 studies to explore the risk factors for perioperative delirium in elderly patients with hip fractures and found that preoperative anemia is one of the independent risk factors for delirium. A retrospective study by Han et al. [32]. involving 622 patients indicated that preoperative health status is a key predictor of postoperative outcomes in elderly patients with fragility intertrochanteric fractures.
Secondly, tissue hypoxia caused by anemia may activate hypoxia-inducible factors, triggering the expression of oxidative stress and inflammatory factors. The accompanying inflammatory response produces many pro-inflammatory cytokines (such as IL-6 and TNF-α). These factors can disrupt the integrity of the blood-brain barrier. This hypoxia-inflammation double hit can lead to significant brain metabolic disorders, including reduced synaptic plasticity, abnormal activation of microglia, and increased blood-brain barrier permeability. These pathological changes make it easier for peripheral inflammatory factors to enter the central nervous system. Several studies have pointed out [33, 34]that the abnormal expression of specific inflammatory factors, such as interleukin-6 (IL-6), C-reactive protein (CRP), IL-8, and IL-10, may disrupt the blood-brain barrier and activate neuroinflammatory pathways, thereby affecting neural function.
The integrative effect of the biopsychosocial model
Based on the above analysis, this study proposes that the mechanism of delirium in elderly patients with hip fractures can be explained through the biopsychosocial model in a multidimensional way. At the biological level, insufficient hemoglobin leads to a decrease in basic brain reserve. At the same time, the hypoxia in the hippocampal area and the increase in inflammatory markers caused by low hemoglobinemia constitute the pathological basis of metabolic disorders [35]. Psychological assessments indicate that patients with sensory deprivation exhibit significant cognitive impairment, with increased error rates in time-space orientation tests and shortened attention maintenance time. Sociological factor analysis reveals that although professional care can fully meet the physiological needs of patients, the intensity of emotional support it provides is weaker than that of family accompaniment. The frequency of non-verbal communication is reduced. This “social sensory deprivation” phenomenon amplifies the biological vulnerability of patients [28]. This integrative model can explain the apparent limitations of traditional single-dimensional biomedical interventions. Future delirium prevention and treatment need to break through the conventional biomedical model and shift towards a more multidimensional intervention strategy that focuses more on the overall condition of patients [36].
Sensory nursing intervention strategy based on the time window concept
Since the severity of delirium increases over time and becomes increasingly challenging to treat, prevention is the best strategy [37]. The sensory nursing intervention strategy based on the time windowconcept provides a targeted solution for delirium prevention in elderly patients with hip fractures. Given the high incidence of perioperative delirium and the high risk of sensory impairment found in this study, it is recommended to implement phased intervention measures. During the emergency admission phase (the golden 24 h), rapid sensory function screening (using the Snellen chart and Whisper test) and environmental adaptability adjustments (such as noise reduction measures and orientation aid packages) should be conducted. In the preoperative phase (24–72 h), multisensory stimulation (such as personalized labeling and preferred music playback) and sleep-wake cycle management should be implemented. In the postoperative phase (0–72 h), dynamic sensory support (using the CAM scale for screening and 1:1 sensory companionship) and early mobilization combined with sensory stimulation should be carried out. Before discharge, emphasis should be placed on pre-adaptation to the home environment, providing sensory rehabilitation guidelines and smart wearable devices. This comprehensive intervention strategy, which integrates biological, psychological, and social multidimensional factors, not only targets precise interventions for the risk characteristics of each stage but also effectively compensates for the sensory support deficiencies under the Unaccompanied-Care” model. Other aspects that need attention include maintaining patient hygiene, meeting nutritional needs, and preventing hospital-acquired conditions such as pressure ulcers. Nursing staff must provide professional support for patients with altered mental status, just as they would for other patients who cannot express their needs independently. Health education for patients and their families, social support, and meeting the spiritual needs of family members should also be included in the primary responsibilities of nursing staff [38].
Limitations
This study has several limitations. First, due to the retrospective observational design and the lack of a control group directly comparing the Unaccompanied-Care model with the traditional accompaniment model, it is impossible to determine the extent of the impact of the Unaccompanied-Caremodel on the incidence of perioperative delirium. Although the data in this study were prospectively collected, the nature of the retrospective research inevitably introduced potential selection and information bias. Second, although this study analyzed various possible risk factors, there may still be other unidentified or unmeasured factors that influence the occurrence of delirium. In addition, the study’s sample size was relatively small and limited to a single medical center, which may affect the generalizability and external validity of the results. Finally, although the Unaccompanied-Care model showed specific effects in this study, its applicability and effectiveness in different regions and medical environments still need further validation.
Summary
This study retrospectively analyzed elderly patients with hip fractures who received the Unaccompanied-Carenursing model from November 2024 to May 2025 to explore the incidence and risk factors of perioperative delirium. The results showed that the incidence of delirium was as high as 25.36%. Multivariate logistic regression analysis indicated that sensory dysfunction (visual and hearing impairment) and low hemoglobin levels were independent risk factors for delirium. The sensory nursing intervention strategy based on the time window concept provides a targeted solution for delirium prevention, effectively reducing the incidence of delirium through the phased implementation of intervention measures.
Acknowledgements
The dataset was retrieved from HIPMED database. We sincerely thank the patients who participated in this study and the Department of Orthopedics at Fuzhou Second General Hospital staff for their invaluable support in patient recruitment and data collection.
Author contributions
Fengfei Lin and Dongze Lin is the correspondence author and led the research project, providing strategic guidance and finalizing the manuscript. XiaoLing Chen, Yixin Huang, Fengxiang Chen were instrumental in data collection and analysis. Xiaole Jiang offered critical insights into the study design and clinical relevance. All authors participated in the manuscript preparation and have reviewed and approved the final version of this manuscript.
Funding
This study was supported by the Fujian Provincial Clinical Medical Research Center for First Aid and Rehabilitation in Orthopedic Trauma (Grant No. 2020Y2014), the Natural Science Foundation of Fujian Province (Grant No. 2023J011514), the Medical Innovation Project of Fujian Province (Grant No. 2022CXA054), and the Youth Research Project of Fujian Provincial Health Commission (Grant No. 2022QNA086).
Data availability
No datasets were generated or analysed during the current study.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
XiaoLing Chen, Yixin Huang, and Fengxiang Chen are co-first authors and contributed equally to this work.
Change history
1/16/2026
The equal contribution note was added.
Contributor Information
Dongze Lin, Email: lindongze2018@163.com.
Fengfei Lin, Email: 596558644@qq.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analysed during the current study.