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. 2025 Jul 1;15:20957. doi: 10.1038/s41598-025-05625-6

Incidence and predictors of extubation failure among adult intensive care unit patients in Northwest Amhara comprehensive specialized hospitals

Meseret Sitotaw Engidaw 1, Berhan Tekeba 2,✉, Hailu Tazebew Amare 3, Kalkidan Ambachew Belay 1, Yezbalem Ayana 1, Bikis Liyew 1
PMCID: PMC12215632  PMID: 40594652

Abstract

Extubation failure occurs in mechanically ventilated patients after planned extubation. It can cause increased mortality, length of intensive care unit stays, prolonged mechanical ventilation use, increased hospital costs, and increased need for tracheostomy. In Ethiopia, extubation failure is limitedly studied among adult patients admitted to intensive care units. Therefore, this study aimed to assess the incidence and predictors of extubation failure among adult patients in intensive care units. A multicenter retrospective follow-up study was conducted among 380 extubated patients from mechanical ventilation at the intensive care unit in northwest Amhara comprehensive specialized hospitals from May 1, 2021, to April 30, 2024. The data was collected randomly from patient cards using a simple random method with a pretested checklist. The data was entered using Epi-Data 4.6 and analyzed using STATA 17. The Kaplan–Meier curve was used to estimate the median extubation failure time. The Cox proportional hazard regression model analyzes the relationship between independent and outcome variables. The overall incidence of extubation failure was 2.64 (95% CI: 1.97–3.54) per 1000 person-hour observations. Forty-five (12.33%) of participants had developed extubation failure. Comorbidities (AHR: 3.92, 95% CI: 1.41–10.81), prolonged mechanical ventilation duration (AHR: 4.69, 95% CI: 2.04–10.80), GCS ≤ 8 with tracheal intubation (AHR: 4.10, 95% CI: 2.10–7.97), and positive fluid balance (AHR: 2.39, 95% CI: 1.23–4.62) were independent predictors of extubation failure. Extubation failure among adult patients admitted to the intensive care unit was high in the first 24 h after extubation. The risk of extubation failure was higher for those patients with comorbidities, prolonged mechanical ventilation, GCS ≤ 8 with tracheal intubation, and positive fluid balance. Therefore, clinicians should prioritize patients who have comorbid conditions, require extended mechanical ventilation, have a Glasgow Coma Scale score of 8 or lower with tracheal intubation, or exhibit a positive fluid balance.

Keywords: Extubation failure, Incidence, Predictors, Intensive care unit, Northwest Ethiopia

Subject terms: Cardiology, Health occupations, Molecular medicine, Signs and symptoms, Urology

Introduction

Extubation failure (EF) is defined as the inability to continue spontaneous breathing after the removal of an endotracheal tube or tracheostomy tube and requiring re-intubation within 24–72 h1,2, although the exact timeframe varies widely among guidelines and the literature. EF occurs in 10–20% of patients who meet al.l weaning criteria and pass the readiness test3. This percentage is even higher, exceeding 20%, in high-risk patients. Such outcomes are associated with significant challenges, including poor prognosis and a mortality rate ranging between 25% and 50%4,5.

Patients requiring re-intubation face higher hospital mortality, increased risk of ventilator-associated pneumonia, longer intensive care unit (ICU) and hospital stays, prolonged duration of mechanical ventilation, higher hospital costs, and an increased need for tracheostomy1,6. Extubation failure is associated with a seven-fold increase in mortality and a 31-fold increase in ICU stay compared to successful extubation7.

Extubation failure has been associated with several predictors, such as old age patients (over 65 years old) with persistent cardiac or respiratory disease, sex, low hemoglobin, abnormal creatinine, cough strength, and oxygen saturation1,8–10. Extubation failure rates are higher in patients with heart failure or positive fluid balance the day before extubation11. Extubation failure causes include respiratory failure, prolonged trans-laryngeal intubation, excessive secretion, and neurological impairment12.

Extubation failure rates globally vary across countries due to differences in measurement criteria, patient diagnosis, and other factors, with rates ranging from 3 to 30%6,13,14. However, in Africa, data on the overall extubation failure rate in ICUs is limited. Studies from South Africa (16.7%) and Ethiopia have reported rates of 16.7% and 34.15%, respectively, in adult ICU patients15,16.

Recent clinical guidelines recommend using preventive noninvasive ventilation17 for more than 24 h immediately after extubation to improve patient outcomes18. There is no fixed standard rule to prevent extubation failure, but much literature recommends that post-extubation management be effective for low- to high-risk populations. To prevent post-extubation airway complications, it is essential to optimize patients’ conditions beforehand, carefully choose the timing of extubation, ensure the presence of skilled personnel trained in advanced airway management, and ensure the availability of the necessary equipment and appropriate post-extubation monitoring19,20.

In Ethiopia, few studies were conducted on extubation failure and its predictors, and reintubation was assessed as a risk factor for mortality among mechanically ventilated patients and the incidence of ventilator-associated pneumonia21–23. Therefore, studying incidence and predictors is crucial for patient care and outcome. This study aimed to assess the incidence and predictors of extubation failure among adult extubated patients from mechanical ventilation in northwest Amhara comprehensive specialized hospitals. This study’s results will help health professionals identify predictors of time to extubation failure and implement interventions accordingly.

Methods and materials

Study design and period

An institution-based retrospective follow-up study was conducted from May 1, 2021, to April 30, 2024, and the data extraction period was from May 15, 2024, to June 30, 2024.

Study area

The study was carried out in adult intensive care units in comprehensive specialized referral hospitals in northwest Amhara, Ethiopia. This region is home to five Comprehensive Specialized Referral Hospitals24.

The five Comprehensive Specialized Referral Hospitals were University of Gondar Comprehensive Specialized Referral Hospital (UoGCSRH), Felege Hiwot Comprehensive Specialized Hospital, Debre Markos Comprehensive Specialized Referral Hospital (DMCSRH), Tibebe Gihon Comprehensive Specialized Hospital (TGCSRH), and Debre Tabor Comprehensive Specialized Hospital (DTCSRH).

The catchment area for each comprehensive hospital is thought to contain 5–7 million people25. Tibeb Gihon is located in Bahirdar City, and there are two intensive care units (pediatric and adult). The adult ICU is equipped with 9 beds, 4 functioning mechanical ventilators, 7 patient monitors, and one bedside ultrasound. This unit is staffed with two anesthesiologists, internal medicine specialists and subspecialists, trained nurses, and medical and surgical residents26. Felege Hiwot is also the other comprehensive hospital in Bahirdar City. The adult ICU is one of the 13 wards it has, where critically ill patients are admitted22. Currently, it has ten beds and 4 MVs.

The Gondar University Hospital was founded in Gondar town. It started critical care service in 2011 with a four-bed ICU capacity, two motorized ventilators, one defibrillator, four noninvasive hemodynamic monitoring devices, and one ultrasound machine27,28, and now it has four ICU departments divided based on specialty: medical ICU, surgical ICU, pediatrics ICU, and neonatal ICU. The adult medical and surgical ICUs of Gondar have 22 beds, 11 MVs, 22 monitors, one portable X-ray machine, two ultrasound machines, and one dialyzer machine. Debretabor is found in Debre Tabor town, and it has three ICUs: one adult, one pediatric, and one neonatal. The adult ICU has six beds. Debre Markos is located in East Gojam29. The adult ICU has 4 beds, 3 functional mechanical ventilators, and 3 functional monitors.

Source and study population

Source population

The source population consisted of all adult patients admitted to the adult intensive care units for mechanical ventilation in comprehensive specialized hospitals located in northwest, Amhara.

Study population

All adult patients admitted to the adult ICUs and extubated from mechanical ventilation from May 1, 2021, to April 30, 2024, in northwest Amhara comprehensive specialized hospitals were study populations.

Inclusion and exclusion criteria

Inclusion criteria

The study included all adult patients who were on mechanical ventilation and extubated in the ICU from May 1, 2021, to April 30, 2024, in the northwest Amhara comprehensive specialized hospital. During the study period, a total of 3,081 adult patients admitted to ICU were on mechanical ventilation. Out of this, 380 patients were extubated based on the discharge criteria.

Exclusion criteria

Incomplete records were excluded from the study.

Sample size calculation and sampling procedure

Sample size calculation

There is a lack of research on survival analysis in Ethiopia; a single population proportion formula was used to estimate the sample size.

P = the proportion of extubation failure among mechanically ventilated patients admitted to ICU, 34.15% from a study done in SPMMC Ethiopia16.

z α/2 = the resultant Z score of 95% CI and α = 0.05 d = a tolerable margin of error (5%) and.

n = the minimum sample size required.

Inline graphic

Inline graphic

n = 345.

By considering lost and incomplete patient records, 10% of the initial sample size was added, and the final sample size was 380.

Sampling technique and procedure

The sampling process included all patients on mechanical ventilation at the ICU (N = 3081) in the northwest comprehensive specialized hospital. Proportional allocation of study participants to each hospital, i.e., UOGCSH (N = 1128, n = 139), DMCSH (N = 288, n = 35), TGSCH (N = 720, n = 89), FHSCH (N = 600, n = 74), and DTCSH (N = 345, n = 43), was done. After identifying the patients who fulfilled the inclusion criteria, the medical registration number of the patient was used as a sampling frame and was used to choose patient charts. Then, study participants were selected by a simple random sampling technique using computer-generated random numbers (Fig. 1).

Fig. 1.

Fig. 1

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Schematic presentation of the sampling procedure used to select adult mechanically ventilated patients at ICUs in northwest Amhara comprehensive specialized hospitals.

Variables of the study

Dependent variable

Incidence of positive ventilation pressure-assisted extubation failure (yes or no).

Independent variable

The independent variables were socio-demographic, clinical, and laboratory-related factors and treatment-related factors. Socio-demographic factors include age, sex, and residence of the patient. Clinical and laboratory-related factors include the diagnosis of extubation failure during ICU admission, indication to MV, duration of MV, presence of comorbidities, baseline patient vital signs (PR, RR, TO), patient random glucose level, GCS, fluid balance, hemoglobin level, creatinine level, WBC count, and oxygen saturation. Treatment-related factors include diuretics, vasopressors, inotropes, sedatives, and corticosteroid use.

Operational definition

Censored cases are patients who did not develop extubation failure, such as those who re-intubated after 72 h, had unplanned extubation, died, left against medical advice (LAMA), or were transferred out and recovered during the follow-up period.

Event

Extubation failure occurs in extubated patients during the follow-up time (re-intubated within 72 h).

Follow-up time

The time from extubation until either extubation failure or censorship occurs within 72 h starting from May 1, 2021 until April 2024.

Survival status

outcome of extubated patients; either extubation failure or censored.

Survival time:

from extubation to extubation failure (reintubation).

Planned extubation is defined as extubation after a successful spontaneous breathing trial in a patient fulfilling all weaning criteria30.

Unplanned extubation is defined as the removal of the endotracheal tube by the patients (self-extubation) or accidental removal of an endotracheal tube during nursing care or transportation30.

Data collection tool and procedure

A data extraction checklist was developed from related literature15,16. The data extraction tool consists of sociodemographic, clinical laboratory, and treatment factors. Four trained BSc nurses working in the emergency wards of the respective hospitals collected the data using the checklist. Two trained BSc nurses, working in wards other than the adult ICU, supervised the data collection process. The patient’s charts were found by taking the medical record number (MRN) from the logbook at the ICU. Then, the charts were extracted from the card rooms of the corresponding hospitals. All randomly selected charts were reviewed, and relevant data was extracted.

Data quality controls

To control the data quality, one-day training was given to supervisors and data collectors about the objective of the study, data collection techniques, and confidentiality. Before the actual data collection, a pre-test was conducted on 19 (5%) randomly selected charts at UoGCSH to check the accessibility of variables. Accordingly, variables that were not recorded (cough strength and secretion amount) and not well investigated (BUN and albumin) were excluded from the checklist. During data collection, each filled checklist was cross-checked and revised daily by the principal investigator and supervisors for completeness. Data cleaning was performed before analysis.

Data processing and analysis

After data collection, the data were entered using Epi-Data version 4.6.0 for data cleaning and coded before analysis, and then it was exported to STATA 17 software for analysis. Categorical data were calculated using frequency distribution. Then, the outcome of each participant was dichotomized into events or censored. Incidence rates were estimated for the entire study period and specified hour intervals after extubation. Consequently, the extubation failure rate within the study period was divided by the total hours from extubation to 72 h at hazard on follow-up and reported per 1000 person-hours. Kaplan Meier was used to estimate the failure time after extubation, and log-rank tests were used to compare the failure curve after extubation from mechanical ventilation. The incidence of extubation failure probability at certain time intervals was estimated using the Kaplan-Meier failure table. The Cox proportional hazard regression model was used to analyze the relationship between independent and outcome variables. Bivariable analysis was done for all variables, and variables with a p-value ≤ 0.25 were transferred to multivariable analysis. Before multivariable analysis, multicollinearity was tested using the VIF command to check the variable inflation factor (mean VIF = 1.09). Then proportional hazard assumptions were checked using Schoenfeld residual tests (global test) with a value of P > chi2 = 0.7211. Also, Cox proportional hazard model fitness to the data was checked using Cox-Snell residuals, in which the hazard function follows the 45-degree baseline (Fig. 4). In conclusion, the final model fit the data successfully. In the multivariable analysis, a P < 0.05 was considered statistically significant. Then, associations were summarized using an adjusted hazard ratio, and statistical significance was tested at 95% CI. Lastly, the results were presented using texts, tables, and graphs.

Ethical approval

Ethical clearance was obtained from the University of Gondar on behalf of the ethical review committee from the School of Nursing with reference number S/N/128/2016. Permission was also obtained from the Amhara Public Health Institute through a formal letter request from the University of Gondar with ECCND/343/2016 reference number. The Amhara Public Health Institute issued a support letter to Debremarkos, Debretabor, and Felegehiwot Comprehensive Specialized Hospitals with the reference number Inline graphic03/2279. After the permission was obtained by showing the letter to the medical directors, ICU heads, and chart room heads of each hospital, data was collected from the patient chart. Verbal or written consent was not obtained from the study participants since the data were collected from the patients’ medical charts and there was no direct contact between the patient and data collector. During the data collection period, the data collector, the investigator, and the supervisor followed “codes of ethics” and obeyed the rules and regulations of the hospital. All methods were carried out in accordance with Declaration of Helsinki guidelines and regulations.

Result

Socio-demographic characteristics of included participants

After reviewing 380 extubated adult patients from mechanical ventilation records, with a completeness rate of 96% (365), they were finally analyzed. More than half of the 220 study participants (60.3%) were males, and half of the participants, 184 (50.4%), were from rural areas. The baseline mean age of the participants was, at the time of the follow-up, 46 years (SD = 46 ± 17 years)(Table 1).

Table 1.

Baseline socio-demographic characteristics of extubated adult patients at ICU in Northwest Amhara comprehensive specialized hospital from May 2021 to April 2024.

Variable Category of variable Outcome status Frequency (N = 365) Percent (%)
Event
(Count, %)		 Censored
(Count, %)
Age of the patient in the year < 40 year 7 (5.43%) 122 (94.57%) 129 35.34%
40–60 year 16 (11.43%) 124 (88.57%) 140 38.36%
> 60 year 22 (22.92%) 77 (77.08%) 96 26.30%
Sex of the patient Male 28 (12.73%) 192 (87.27%) 220 60.27%
Female 17 (11.72%) 128 (88.28%) 145 39.73%
Residence Urban 23 (12.71%) 158 (87.29%) 181 49.59%
Rural 22 (11.96%) 162 (88.04%) 184 50.41%
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Baseline clinical, laboratory, and treatment-related characteristics

Of the 365 adult extubated patients from mechanical ventilation, one-fourth of the study participants, 28.5%, had a diagnosis of respiratory origin for ICU admission. For more than half of the study participants, 54.8%, and only 18.4% of the study participant’s indications for mechanical ventilation were respiratory problems and altered mentation, respectively. Almost half of the study participants, 52.6%, had comorbidities, with one-fourth, 25%, and around one-fourth, 21.9%, having hypertensive and diabetic mellitus, respectively. Around half of the study participants, 47.4%, were on mechanical ventilation for ≥ 10 days, and throughout the follow-up time, 131 (35.9%) developed complications encountered during mechanical ventilation. More than one-thrid of the study participants, 38.93%, had ventilator-associated pneumonia (VAP) (Table 2).

Table 2.

Baseline clinical, laboratory, and treatment-related characteristics of adult patients at ICU in Northwest Amhara comprehensive specialized hospital from May 2021 to April 2024.

Variable Category variable Outcome status Frequency (N) Percent (%)
Event (count %) Censored (count %)
Diagnosis during ICU admission Respiratory in origin 14 (13.46%) 90 (86.54) 104 28.49%
Cardiac in origin 6 (11.32%) 47 (88.68%) 53 14.52%
Neurologic in origin 13 (21.31%) 48 (78.69%) 61 16.71%
Trauma 4 (6.15%) 61 (93.85%) 65 17.81%
Postoperative 3 (8.11%) 34 (91.89%) 37 10.14%
Others* 5 (11.11%) 40 (88.89%) 45 12.33%
Indication for mechanical ventilation Respiratory problem 32 (16%) 168 (84%) 200 54.79%
Postoperative 2 (8.33%) 22 (91.67%) 24 6.57%
Altered meditation 6 (8.96%) 61 (91.0%) 67 18.36%
Trauma 1 (5%) 19 (95%) 20 5.48%
CVS 3 (7.14%) 39 (92.86%) 42 11.51%
Neurologic disease 1 (8.33%) 11 (91.67%) 12 3.29%
Comorbidities Yes 39 (20.31%) 153 (79.69%) 192 52.6%
No 6 (3.47%) 167 (96.53%) 173 47.4%
Type of Comorbidities Hypertension 10 (20.83%) 38 (79.17%) 48 25%
Diabetes mellitus 6 (14.29%) 36 (85.71) 42 21.88%
Heart diseases 4 (12.12%) 29 (87.88%) 33 17.19%
Pulmonary disease 5 (17.86%) 23 (82.14%) 28 14.59%
Chronic kidney disease 1 (20%) 4 (80%) 5 2.61%
Stroke 9 (81.81%) 2 (18.19%) 11 5.73%
Others** 4 (16%) 21 (84%) 25 13%
Mechanical ventilation duration

Not prolonged

(< 10 days)

 7 (3.65%) 185 (96.35%) 192 52.6%
Prolonged (≥ 10days) 38 (21.97%) 135 (78.3%) 173 47.4%
Complications encountered during Mechanical ventilation Yes 36 (27.48%) 95 (72.52%) 131 35.89%
No 9 (3.85%) 225 (96.15%) 234 64.11%
Types of complications encountered during Mechanical ventilation VAP 16 (31.37%) 35 (68.63%) 51 38.93%
Sepsis 9 (23.08%) 30 (76.92%) 39 29.77%
Shock 4 (20%) 16 (80%) 20 15.27%
Acute kidney injury 6 (33.3%) 12 (66.67%) 18 13.74%
Others*** 1 (33.33%) 2 (66.67%) 3 2.29%
RR Normal (12-24 bpm) 27 (11.16%) 215 (88.84) 242 66.3%
High (> 24 bpm) 18 (16.63) 105 (85.37) 123 33.7%
SO2 ≤ 90% 3 (42.86%) 4 (57.14%) 7 1.92%
> 90% 42 (11.73%) 316 (88.27%) 358 98.08%
PR Normal(60-100 bpm) 29 (14.08%) 177 (85.92%) 206 56.44%
High (> 100 bpm) 16 (10.06%) 143 (89.94%) 159 43.56%
Temperature (0c) Low (< 36.5) 24 (16.22%) 124 (83.78%) 148 40.55%
Normal (36.5–37.5) 16 (8.56%) 171 (91.44%) 187 51.23%
High (> 37.5) 5 (16.67%) 25 (83.33%) 30 8.22%
SBP Low(< 90mmHg) 7 (97.5%) 1 (12.5%) 8 2.19%
Normal(90-139mmHg) 42 (12.65%) 290 (87.35%) 332 90.96%
High(≥ 140mmHg) 2 (8%) 23 (92%) 25 6.85%
DBP Low(< 60mmHg) 1 (25%) 3 (75%) 4 1.1%
Normal(60-89mmHg) 40 (12.16%) 289 (87.84%) 329 90.13%
High(≥ 90mmHg) 4 (12.5) 28 (87.5%) 32 8.77%
RBS 70-140 mg/dl 16 (12.5%) 112 (87.5%) 128 35.07%
> 140 mg/dl 29 (12.24%) 208 (87.76%) 237 64.93%
GCS with T ≤ 8T 20 (30.3%) 46 (69.7%) 66 18.08%
9-10T 25 (8.36%) 274 (91.64%) 299 81.92%
Fluid balance Positive 26 (16.88%) 128 (83.12%) 154 42.19%
Negative 19 ((9%) 192 (91%) 211 57.81%
Hemoglobin < 10 g/dl 21(16.28) 108 (83.72%) 129 35.34%
≥ 10 g/dl 24 (10.17%) 212 (89.83%) 236 64.66%
Creatinine ≤ 1.2 mg/dl 28 (9.93%) 254 (90.0%) 282 77.26%
> 1.2 mg/dl 17 (20.48%) 66 (79.52%) 83 22.74%
WBC Low(< 4 × 10/MCL) 2 (14.29%) 12 (85.71%) 14 3.83%
Normal(4-11 × 10/MCL) 27 (13.99%) 166 (86.01%) 193 52.88%
High(> 11 × 10/MCL) 16 (10.13%) 142 (89.87%) 158 43.29%
Diuretics use Yes 16 (13.45%) 103 (86.5%) 119 32.6%
No 29 (11.79% 217 (88.21%) 246 67.4%
Vasopressor/ inotrope use Yes 14 (12.5%) 98 (87.5%0 112 30.68%
No 31 (12.25%) 222 (87.75%) 253 69.32%
Corticosteroid use Yes 30 (13.76%) 188 (86.24%) 218 59.73%
No 15 (10.2) 132 (89.8%) 147 40.27%
Sedatives use Yes 42 (12.28%) 300 (87.72%) 342 93.7%
No 3 (13.04%) 20 (86.96%) 23 6.3%
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*Others during ICU admission-shock, poisoning, acute kidney injury, retroviral infection.

**Others for types of comorbidities -cancer, retroviral infection, epilepsy, and chronic kidney disease.

***Others for complications encountered during MV- pneumothorax and tension pneumothorax.

Incidences of extubation failure

A total of 365 adult patients admitted to the ICU after extubation from mechanical ventilation, with follow-up periods ranging from a minimum of 4 h to a maximum of 72 h, were examined to determine the incidence of extubation failure. Accordingly, five (12.3%) participants developed extubation failure (event), and 320 (87.7%) did not develop extubation failure (censored) (Fig. 3). The total duration at risk was 17,005 h, and the incidence rate of extubation failure was 2.64 per 1000 person-hours (95% CI: 1.97–3.54) observed among follow-ups of the extubated patient from mechanical ventilation. Overall, of 45 extubation failures, 25 (55.56%) were re-intubated within 24 h after extubation, 19 (42.22%) at 24–48 h after extubation, and 1 (2.22%) at 48–72 h after extubation follow-up time (Fig 2).

Fig. 2.

Fig. 2

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Incidence of extubation failure among adult patients at ICU in northwest Amhara comprehensive specialized hospital from May 1, 2021 to April 30, 2024.

Multicollinearity test

Multicollinearity was checked by calculating each predictor variable using the variance inflation factor (VIF) based on the binary Cox regression outcome. The overall VIF in the final multivariable analysis was 1.09.

Assessing the proportional hazard assumption

Based on binary and multicollinearity outcome testing, proportional hazard assumptions are vital for interpreting, using fitted proportional hazard models, and accepting multivariable results. In this study, the Schoenfeld residual proportional hazard assumption test for individual covariates was done, and the global test was 0.7211. The proportional assumption is rejected if the p-value < 0.05.

Model goodness of fit test

Snell residuals were used to check the goodness of fit test. The hazard function follows 45˚ closest to the baseline hazard, which showed that the model was well-fitted (Fig. 3).

Fig. 3.

Fig. 3

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Cox-Snell residual allover goodness of fit test among adult extubated patients from MV in northwest Amhara comprehensive specialized hospital May 2021 to April 2024.

Failure function

The cumulative probability of failure was 6, 12, 24, 48, and 72 h: 1.64%, 4.1%, 10.6%, 12.9%, and 13.6%, respectively. The overall KM failure function showed that most extubation failures occur within 24 h after extubation and become declining through follow-up time (Fig. 4).

Fig. 4.

Fig. 4

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Kaplan Meier failure function of adult extubated patients from mechanical ventilation admitted to ICUs in northwest Amhara comprehensive specialized hospitals from May 1, 2021, to April 30, 2024.

Test of equality of failure function of predictors

The failure curve showed significant differences in the failure function of different categorical variables. The variables were comorbidities, mechanical ventilation duration, GCS ≤ 8, and positive fluid balance. In this study, patients with comorbidities had a high extubation failure rate. The extubation failure rate at the end of the follow-up period was higher among patients with comorbidities compared to patients without comorbidities (Fig 5).

Fig. 5.

Fig. 5

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Kaplan-Meier failure curve for comorbidities among adult extubated patients at ICU in northwest Amhara comprehensive specialized hospitals from May 1, 2021, to April 30, 2024.

Another important predictor was prolonged mechanical ventilation duration. Patients who had been on mechanical ventilation for 10 days and above had a higher risk of extubation failure compared to those who had been on mechanical ventilation for a short time (Fig. 6).

Fig. 6.

Fig. 6

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Kaplan-Meier failure function curve for the duration of mechanical ventilation among adult extubated patients at ICU in northwest Amhara comprehensive specialized hospitals from May 1, 2021, to April 30, 2024.

Patients who had pre-extubation GCS ≤ 8 with tracheal intubation had a highly significant difference for extubation failure than patients who had GCS > 8 with tracheal intubation (Fig. 7).

Fig. 7.

Fig. 7

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Kaplan-Meier failure curve for GCS among adult extubated patients at ICU in northwest Amhara comprehensive specialized hospitals from May 1, 2021, to April 30, 2024.

Positive fluid balance during the pre-extubation period has shown a significant difference in the extubation failure rates of patients extubated with negative fluid balance, respectively (Fig. 8).

Fig. 8.

Fig. 8

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Kaplan-Meier failure curve for fluid balance adult extubated patients at ICU in northwest Amhara comprehensive specialized hospitals from May 1, 2021, to April 30, 2024.

Predictors of extubation failure among adult extubated patients

The Cox proportional hazard regression model analyzed the relationship between the independent and outcome variables. In bivariable Cox regression analysis, the age of the patient, indication for mechanical ventilation, comorbidities, mechanical ventilation duration, oxygen saturation, pulse rate, GCS with tracheal intubation, hemoglobin, and creatinine were found to have a P-value of ≤ 0.25, which was a candidate for multivariable Cox-proportional hazard analysis. From the final multivariable Cox proportional regression analysis, comorbidities, prolonged MV duration, ≤8T GCS, and positive fluid balance were predictors of extubation failure at a 5% significance level.

Mechanically ventilated patients with comorbidities have 3.92 times the hazard of developing extubation failure (AHR: 3.92 (95% CI: 1.41, 10.81)) compared with those without comorbidities. Extubated patients from mechanically ventilated on prolonged (≥ 10 days) mechanical ventilation duration had a hazard of risk of developing extubation failure 4.69 times that of patients on short mechanical ventilation duration (< 10 days) (AHR: 4.69 (95% CI: 2.04, 10.80).

The Glasgow Coma Scale also had a significant difference in extubation failure; patients who have GCS ≤ 8T have a hazard of 4.1 (AHR: 4.10 (CI95%: 2.10, 7.97)) times higher than patients who have GCS > 8. The hazard of extubation failure was 2.39 times higher among extubated patients from mechanical ventilation with positive fluid balance (AHR: 2.39 (95% CI: 1.23, 4.62) during extubation) compared to those with negative fluid balance (Table 3).

Table 3.

Bivariable and multivariable Cox regression analysis of predictors of extubation failure among adult extubated patients at ICU in Northwest Amhara comprehensive specialized hospitals from May 2021 to April 2024.

Variable Category
of variable		 Outcome status CHR[95%CI] AHR[95%CI] P-value
Event censored
Age of the patient < 40 7 122 1
40–60 16 124 2.17(0.89,5.29) 1.60(0.59,4.32) 0.348
> 60 22 77 4.47(1.91,10.46) 1.91(0.71,5.13) 0.199
Indication for MV Respiratory problem 32 168 3.40(0.46,24.94) 2.07(0.24,17.76) 0.505
Postoperative 2 22 1.66(0.15,18.33) 2.48(0.19,32.01) 0.486
Altered mentation 6 61 1.77(0.21,14.73) 0.89(0.09,8.53) 0.920
Trauma 1 19 1
CVS 3 39 1.46(0.15,14.05) 1.79(0.16,19.07) 0.884
Neurologic disease 1 11 1.67(0.10,26.81) 1.28(0.07,23.23) 0.605
Comorbidities Yes 39 153 6.08(2.57,14.38) 3.92(1.41,10.87) 0.009*
No 6 167 1
MV duration in days Not prolonged 7 185 1
Prolonged 38 135 6.34(2.83,14.20) 4.69(2.04,10.80) < 0.001*
SO2 ≤ 90% 3 4 4.73(1.46,15.29) 3.13(0.67,14.60) 0.146
> 90% 42 316 1
PR Normal 29 177 1
High 16 143 0.68(0.37,1.26) 0.58(0.29,1.15) 0.119
GCS with T ≤ 8T 20 46 4.24(2.35,7.65) 4.10(2.10,7.97) < 0.001*
9-10T 25 274 1
Fluid balance Positive 26 128 1.88(1.04,3.40) 2.39(1.23,4.62) 0.010*
Negative 19 192 1
Hemoglobin ≤ 10 21 108 1.74(0.97,3.13) 1.26(0.66,2.41) 0.469
> 10 24 212 1
Creatinine level ≤ 1.2 28 254 1
> 1.2 17 66 2.21(1.21,4.05) 1.70(0.86,3.35) 0.122
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* Statistically significant at multivariable with a 5% level of significance, CI- confidence interval.

Discussion

This study reveals that the overall incidence rate of extubation failure among adult extubated patients admitted to the ICU in the northwest Amhara comprehensive specialized hospital was 2.64 per 1000 person-hour observation (95% CI: 1.97–3.54). The overall extubation failure of extubated adult patients was 12.33% (95% CI: 9.32–16.13). This aligns with the previous study conducted in France (10.4%)8, Thailand (11.8%)17, and Nepal (12%)31. This similarity may be attributed to comparable ICU environments across different countries, where factors such as prolonged mechanical ventilation-induced airway injuries, muscle weakness, and comorbidities consistently contribute to extubation failure among these patients even in different countries32.

Our findings, when compared locally, were lower than those of the study conducted in Gondar (21.29%)21 and Addis Ababa (34.15%)16 and a study conducted abroad in Kenya (37.5%)20, South Africa (16.7%)15, the USA (19%)13, Argentina (17%)33, France (31%)34, Australia (20.2%)35, South Korea (24.4%)36, and an international study done in 18 countries (19.4%)37. However, the extubation failure proportion observed in this study is higher than in prior study conducted in Ethiopia (8.6%)38, Thailand (4.88%)39, Brazil (8.2%)10, and Japan (6.4%)40. These variations may be due to the availability of skilled personnel, like critical care subspecialists and anthologists, with well-equipped ICUs in Japan. Another reason for this discrepancy in the prior Ethiopian study might be methodological differences like the use of the purposive sampling selection method and one-year single-centered study. Another reason for this discrepancy across different countries might be differences in the study period, including the Covid-19 pandemic time; study population differences (planned and unplanned extubation and age variation); and patients with specific diagnoses, such as neurocritical patients in Kenya, brain-injured patients in France, spinal cord injury patients in Austria, and reduced skeletal muscle mass in South Korea. In addition, the study setting is only in surgical ICUs and trauma centers.

The Kaplan-Meier failure function revealed that most extubation failures occur within 24 h. This is supported by other studies41–44.This is due to the fact that, during this time, the patients are more vulnerable to complications such as respiratory instability, including laryngeal edema, airway obstruction, inadequate cough, excess respiratory secretion, encephalopathy, and inadequate oxygenation, which often manifest sooner after extubation and necessitate re-intubation41.

In this study, the hazard of extubation failure among patients with comorbidities was 3.92 times higher than among patients without comorbidities. In contrast to this finding, studies in Ethiopia SPMMC16 and South Africa15 show no significant association. This might be because patients with underlying chronic diseases, as well as respiratory and preexisting chronic kidney or neurological diseases, were unable to maintain adequate oxygenation and ventilation due to decreased physiologic reserve and function due to comorbidities, which leads to extubation failure6.

Patients with prolonged mechanical ventilation duration (≥ 10 days) were at a 4.67 times higher hazard of extubation failure as compared to those who had short mechanical ventilation duration. This finding is supported by studies conducted in Ethiopia, SPMMC16, Kenya13, and France8. This prolonged mechanical ventilation causes chronic airway injuries such as laryngeal injury leading to ventilator diaphragmatic dysfunction or muscle weakness, reduced airway patency due to edema, and increased secretion, contributing to the risk of extubation failure3.

Mechanically ventilated patients extubated with GCS ≤ 8 with tracheal intubation had 4.1 times the hazard of extubation failure as compared to those patients without GCS > 8 during extubation. A similar result has been recorded in South Africa12 and Brazil among neurocritical patients15 and Brazil among neurocritical patients45. The possible scientific justification might be that reduced consciousness level causes extubation failure because of large amounts of respiratory secretions and the inability to clear them effectively (52) and also increases the occurrence of stridor and laryngeal edema (53). In addition, it may be a decreased level of consciousness due to persistent effects of sedatives and analgesics and critical illness polyneuropathy leading to extubation failure.

Moreover, our study’s findings revealed that patients with a positive fluid balance were 2.39 times more at hazard of extubation failure than those with a negative fluid balance. This result is similar to a study conducted in Brazil46. This study finding suggests that maintaining a negative fluid balance at pre-extubation may reduce the risk of extubation failure. The potential justification can be that patients with a positive fluid balance lead to increased capillary leak, an increase in extravascular lung water, and a decrease in lung compliance, which may result in respiratory failure in the spontaneous breathing trial and the immediate post-extubation period. Positive fluid balance results in pulmonary congestion, which impairs the diffusion process across the alveolar-capillary membrane, causes hypoxemia, and increases the work of breathing, then leads to extubation failure47.

Limitations of the study

This study is not far from limitations. The study was conducted using a secondary data source and missing some significant predictors of extubation failure, such as the APACHE score, cough strength, and the section amount. As a result, a confounding bias might be introduced and may distort the observed association. The retrospective nature of the study also may introduce information bias through error in data collection and measurement that results in over- or underestimation of the outcome. In addition, exclusion of patients with incomplete information in the data collection might introduce selection bias. Furthermore, the lack of references about the incidence of extubation failure makes comparison harder with existing literature.

Conclusion

This study revealed that a significant proportion of patients in adult ICU need re-intubation after planned extubation. The risk of extubation failure was higher for those patients with comorbidities, prolonged mechanical ventilation, GCS ≤ 8 with tracheal intubation, and positive fluid balance. Therefore, clinicians should perform pre-extubation assessment and implement readiness criteria specific for patients with comorbidities, prolonged mechanical ventilation, low GCS, and positive fluid balance. Policy makers should develop and implement evidence-based guidelines for patients with comorbidities. Policymakers should also promote research to find out the best predictive model and extubation protocol to better address risk factors.

Hospitals should prepare and develop ventilator weaning and extubation protocols. Healthcare providers should give special attention to high-risk groups like those who are patients with comorbidities, prolonged MV duration, GCS ≤ 8T, and positive fluid balance. Putting patients on non-invasive ventilation and high-flow oxygen administered by face mask to support respiratory function, prevent re-intubation, and closely monitor vital signs and signs of airway obstruction are essential.

Healthcare providers should prioritize assessing patients’ Glasgow Coma Scale (GCS) status with an emphasis on motor function rather than eye-opening. Generally, extubation should be avoided in patients with motor scores below 5/6, as this suggests inadequate airway protection. Additionally, efforts should be made to minimize the use of sedatives whenever possible to enhance patient responsiveness.

Fluid management before and after extubation should be carefully monitored and restricted unless necessary for maintaining hemodynamic stability. The goal should be to achieve a neutral or negative fluid balance to reduce the risk of extubation failure. Patients with a positive fluid balance should be administered diuretics, with continuous monitoring of fluid intake and output to optimize post-extubation outcomes.

Upcoming researchers shall conduct a prospective cohort study to incorporate missed variables in the retrospective chart review, like secretion amount, APACHE score, post-extubation stridor, cough strength, and mechanical ventilator factors in a similar study setting. Additionally, upcoming studies will focus on comparing extubation failure rates between the COVID-19 era and the period beyond it.

Abbreviations

AHR

Adjusted Hazarded Ratio

AOR

Adjusted Odds Ratio

DMCSH

Debre Markos Comprehensive Specialized Hospital

DTCSH

Debre Tabor Comprehensive Specialized hospital

EF

Extubation Failure

FHCSH

Felege Hiwot Comprehensive Specialized Hospital

GCS

Glasgow Coma Scale

ICU

Intensive Care Unit

IMV

Invasive Mechanical Ventilation

MV

Mechanical ventilation

NIV

Noninvasive Ventilation

PI

Principal Investigator

SBT

Spontaneous Breathing Trial

SPHMMC

Saint Paul’s Hospital Millennium Medical College

TGCSH

Debre Tabor Comprehensive Specialized Hospital

UOGCSH

University of Gondar Comprehensive Specialized Hospital

VAP

Ventilator-associated pneumonia

WBC

White Blood Count

Author contributions

Meseret Sitotaw made the conceptualization and wrote the original and the final manuscript. Berhan Tekeba made the analysis, reviewed the design of the study, and critically reviewed the final manuscript. Dr. Hailu Tazebew Amare: made formal analysis, validation, and supervision. Kalkidan Ambachew Belay conceived the topic, wrote the original draft, and made a formal analysis. Yezbalem Ayana: performs data collection, performs methodology, and interprets results. Bikis Liyew critically reviewed the manuscript for important intellectual content and contributed to the final approval of the version to be submitted. All authors reviewed the results and approved the final version of the manuscript.

Funding

University of Gondar.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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.

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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

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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