Abstract
Abstract
Objectives
To evaluate emergency patient care from a chronophysiological perspective, examining circadian variations in symptom presentations and physiological parameters.
Single-centre retrospective analysis.
Design
Setting
Department of Emergency Medicine, Clinical Centre, University of Pécs, Hungary (August 2022 to August 2023).
Participants
Patient data including symptom categories, time of presentation (divided into eight 3-hour intervals), sex and age were collected. A total of 32 977 patient records were analysed. Symptoms were classified using the International Classification of Diseases, 10th Revision. For hypertension, random proportionally stratified sampling was performed (n=120).
Primary and secondary outcome measures
Primary outcomes were the circadian distribution of emergency presentations across 14 symptom categories and their variation by time of day, age and sex. Secondary outcomes included diurnal variation in hypertension-related cases, examining blood pressure, pulse rate, triage time and medication use.
Results
Cardiovascular cases peaked between 09:00 and 12:00 (p<0.001), toxicological emergencies between 18:00 and 21:00 (p<0.001) and endocrine–metabolic cases between 12:00 and 15:00 (p<0.001). In hypertensive patients, the lowest systolic pressure occurred between 12:00 and 15:00 (p=0.037). More patients presented on weekdays than weekends (p=0.013).
Conclusions
Symptom presentations in emergency care follow distinct circadian patterns, highlighting the influence of biological rhythms on clinical demand. Recognition of these temporal trends may support more effective ED scheduling and resource allocation.
Keywords: Emergency Service, Hospital; EPIDEMIOLOGIC STUDIES; Physiology
STRENGTHS AND LIMITATIONS OF THIS STUDY.
This study examined circadian patterns in a large emergency department population using real-world clinical data from over 32 000 visits, providing strong external validity.
The analysis applied an uncommon yet informative 3-hour interval approach, allowing a more fine-grained assessment of diurnal symptom variation than the broader time blocks typically used in similar studies.
The combination of retrospective database analysis and a focused hypertension subgroup enabled both population-level and condition-specific insights.
Standardised statistical methods were used, with tests selected according to variable type and data distribution, ensuring methodological transparency and reproducibility.
Limitations include the single-centre retrospective design, potential residual confounding and missing data for certain variables, which may modestly affect generalisability.
Introduction
The emergency department (ED) operates 24/7, every day of the year. It is an environment characterised by an unpredictable pace and volume of work. Nevertheless, the frequency of most symptoms exhibits a diurnal pattern, influenced by both the circadian rhythm of physiological functions and external factors. At present, there is no comprehensive body of literature summarising circadian patterns in relation to patient care. Understanding the physiological basis of the diurnal rhythm of specific symptoms is essential.
The human circadian rhythm is regulated by the internal biological clock in conjunction with external stimuli known as zeitgebers and internal states, including peripheral clock oscillators. Melatonin plays a central role in regulating glucocorticoid synthesis in the adrenal glands, which in turn influences blood pressure control, immune function and oxidative balance. Beyond its well-established function in synchronising the circadian clock, melatonin has also been associated with beneficial effects on mood regulation and the cardiovascular, gastrointestinal and skeletal systems.1 Recent studies have identified the presence of peripheral clocks in cardiovascular cells.2 3 Cardiovascular parameters—including blood pressure, heart rate, stroke volume, cardiac contractility, ECG waveforms and endothelial function—follow distinct circadian rhythms.4,6 Moreover, several endocrine factors also exhibit daily oscillations: adrenocorticotropic hormone, cortisol, orexin and prolactin typically peak in the morning (eg, cortisol between 07:00 and 08:00), whereas melatonin, growth hormone, antidiuretic hormone, thyroid-stimulating hormone and leptin reach their highest levels at night (eg, melatonin between 00:00 and 03:00). These rhythmic fluctuations reflect complex neurohumoral mechanisms that coordinate peripheral metabolic organs with the central circadian clock.
The objective of this study is to evaluate emergency patient care from a chronophysiological perspective. We summarise the diurnal pattern of symptoms in patients arriving at the ED and the circadian changes in parameters of hypertensive patients. Within the large database of ED presentations, we chose to examine hypertension as a distinct subgroup for several reasons.
Methods
Study design, setting and ethical approval
A retrospective chart analysis was conducted at the Department of Emergency Medicine, University of Pécs, Hungary. The department functions as a high-volume tertiary care unit with an annual patient volume of approximately 46 000. It operates as a multidisciplinary adult emergency department covering medical, surgical, neurological and trauma care, while paediatrics, obstetrics and gynaecology are managed in separate specialty units. Patient management follows European emergency care standards, employing the modified Canadian Triage and Acuity Scale (mCTAS). The facility comprises five examination rooms, two resuscitation bays and a dedicated, fully equipped resuscitation room, alongside a 14-bed observation area and a three-bed intensive care area. The hospital admission rate averages approximately 10% of the daily patient volume. The unit also serves as a regional academic training centre supported by a clinical simulation facility.
Data were obtained from the hospital’s electronic database (e-MedSol). Only anonymised patient data were used, and no identifiable information was accessible to the researchers.
Sample
Circadian pattern of emergency cases
Data from a total of 46 362 patients were collected from the Department of Emergency Medicine at the University of Pécs between August 2022 and August 2023. Patients were categorised by symptoms, time of day (00:00–03:00, 03:00–06:00, 06:00–09:00, 09:00–12:00, 12:00–15:00, 15:00–18:00, 18:00–21:00, 21:00–00:00), gender and age. The International Classification of Diseases, 10th Revision (ICD-10),7 was used to categorise symptoms, with patients assigned to groups based on the first recorded ICD code. ICD codes were grouped into 14 categories according to the Hungarian healthcare service classification (code 46, emergency outpatient care). Cases coded as R68.8 (other general symptoms and signs) were excluded from the analysis, resulting in a final sample of 32 977 cases. Of them, 52% were female, and the mean age was 62±8 years.
Characteristics of hypertension cases
Within the large database of ED presentations, we chose to examine hypertension as a distinct subgroup for several reasons. First, the selection was based on only two ICD-10 codes, allowing for a relatively homogeneous patient cohort and reducing diagnostic heterogeneity. Second, hypertension is one of the most prevalent chronic conditions worldwide, and it represents a frequent reason for ED visits, underscoring its clinical and public health relevance. Since hypertension affects more than 150 million adults in Europe, with a prevalence of 35–40% in the adult population, it is one of the most frequent admission criteria in the ED.8 Finally, blood pressure regulation is strongly influenced by circadian mechanisms, with daily rhythms in melatonin, cortisol secretion and physical activity contributing to characteristic diurnal patterns. These features make hypertension particularly well-suited for investigating circadian variation in emergency presentations.
Random and proportional stratified sampling was performed, resulting in a sample of 120 patients. During stratification, the female-to-male ratio (female: 65%, male: 35%) and the mean age by gender (female: 71±3 years; male: 62±4 years) were determined based on data from all patients in the hypertension group (n=966). Patients whose ages fell within ±2 SD of the mean age were included. For random selection, every second patient from the database was chosen (figure 1).
Figure 1. Patient selection. ICD-10, International Classification of Diseases, 10th Revision.
Statistical analysis
We report values as mean±SD for normally distributed continuous variables, as median (25th–75th percentile) for non-normally distributed variables, and as frequencies with percentages (n (%)) for categorical variables.
Normality of distributions was tested using the Shapiro-Wilk test, and homogeneity of variances with Levene’s test. For continuous variables with a normal distribution (eg, systolic and diastolic blood pressure, triage time), one-way analysis of variance (ANOVA) was applied, followed by Bonferroni-corrected post hoc comparisons when overall significance was observed. For non-normally distributed continuous variables (eg, number of patient presentations), the Kruskal-Wallis test was used, with pairwise Mann-Whitney U tests and Bonferroni adjustment for multiple comparisons. To control for multiple comparisons across the eight-time intervals, Bonferroni correction was applied, setting the adjusted level of significance at p<0.0018 (0.05/28). Categorical variables (eg, symptoms, medications) were analysed using Pearson’s χ² test. When more than 20% of cells had an expected count <5, Fisher’s exact test with Monte Carlo correction (two-sided) was applied.
In the hypertension subgroup, missing values were excluded listwise for each variable, resulting in slightly varying sample sizes across analyses. This approach ensured that only complete cases were analysed, but it may introduce bias if data were not missing completely at random.
All analyses were conducted using IBM SPSS Statistics V.29.0 (IBM, Armonk, New York, USA). Statistical significance was defined as two-tailed p<0.05.
Patient and public involvement
Patients or members of the public were not involved in the design, conduct, reporting or dissemination of this study.
Results
Circadian pattern of emergency cases
Significant circadian variations were observed across all major symptom categories (Kruskal-Wallis tests: all p<0.001).
The median number of chest pain and arrhythmia cases per month was 395 (IQR 46; range: 297–463 cases). The highest number of patients presented between 09:00 and 12:00 (23%; median: 85; IQR 25; range: 70–120 cases), while the fewest patients presented between 03:00 and 06:00 (4%; median: 15; IQR 7; range: 10–19 cases; Kruskal-Wallis: p<0.001).
The median number of patients presenting with hypertension per month was 73 (IQR 19; range: 50–97 cases). Most patients arrived between 09:00 and 12:00 (18%; median: 14; IQR 5; range: 7–25 cases), while the fewest presented between 03:00 and 06:00 (4%; median: 3; IQR 4; range: 1–5 cases; Kruskal-Wallis: p<0.001) (figure 2).
Figure 2. Median number of hypertension cases by time of day per month (n=966). Note: Kruskal-Wallis test followed by Bonferroni-adjusted pairwise Mann-Whitney U tests revealed significant differences between the 9:00 and 12:00 interval and all other time periods (p<0.001).
The median number of vascular disease cases per month was 45 (IQR 13; range: 31–53 cases). Most patients presented between 09:00 and 12:00 (28%; median: 12; IQR 2; range: 7–19 cases), while the fewest presented between 03:00 and 06:00 (1%; median: 0; IQR 1; range: 0–2 cases; Kruskal-Wallis: p<0.001).
The median number of patients presenting to the ED due to generalised epilepsy seizures per month was 36 (IQR 7; range: 25–47 cases). Most patients arrived between 09:00 and 12:00 (21%; median: 8; IQR 5; range: 1–13 cases), while the fewest presented between 00:00 and 03:00 (4%; median: 1; IQR 2; range: 0–3 cases; Kruskal-Wallis: p<0.001).
The median number of patients presenting with balance disorders and headaches per month was 41 (IQR 17; range: 24–63 cases). The majority of cases were recorded between 09:00 and 12:00 (25%; median: 10; IQR 6; range: 7–18 cases), while the fewest were reported between 03:00 and 06:00 (3%; median: 1; IQR 2; range: 0–4 cases; Kruskal-Wallis: p<0.001).
The median number of stroke cases per month was 94 (IQR 17; range: 81–113 cases). Most cases occurred between 09:00 and 12:00 (27%; median: 26; IQR 10; range: 12–37 cases), while the fewest were reported between 00:00 and 03:00 (2%; median: 2; IQR 2; range: 0–4 cases; Kruskal-Wallis: p<0.001).
The median number of trauma cases per month was 874 (IQR 116; range: 751–962 cases). The highest number occurred between 09:00 and 12:00 (21%; median: 144; IQR 15; range: 121–158 cases), while the fewest were recorded between 03:00 and 06:00 (2%; median: 12; IQR 4; range: 3–14 cases; Kruskal-Wallis: p<0.001) (figure 3).
Figure 3. Median number of trauma cases by parts of the day per month (n=11 229). Note: Kruskal-Wallis test followed by Bonferroni-adjusted pairwise Mann-Whitney U tests revealed significant differences between the 9:00 and 12:00 interval and all other time periods (p<0.001).
The median number of patients presenting with toxic effects of alcohol and overdose of antiepileptic and sedative–hypnotic drugs per month was 151 (IQR 25; range: 113–220 cases). Most patients presented between 18:00 and 21:00 (23%; median: 36; IQR 7; range: 29–44 cases), while the fewest arrived between 06:00 and 09:00 (4%; median: 6; IQR 4; range: 1–15 cases; Kruskal-Wallis: p<0.001) (figure 4).
Figure 4. Median number of toxicological emergencies by parts of the day per month (n=2026). Note: Kruskal-Wallis test followed by Bonferroni-adjusted pairwise Mann-Whitney U tests revealed significant differences between the 18:00 and 21:00 interval and all other time periods (p<0.001).
The median number of respiratory cases per month was 145 (IQR 60; range: 93–202 cases). Most of them were reported between 09:00 and 12:00 (23%; median: 32; IQR 15; range: 20–52 cases), while the fewest presented between 03:00 and 06:00 (4%; median: 6; IQR 5; range: 1–12 cases; Kruskal-Wallis: p<0.001).
The median number of gastrointestinal cases per month was 401 (IQR 79; range: 261–454 cases). The majority of cases occurred between 09:00 and 12:00 (24%; median: 51; IQR 9; range: 40–59 cases), while the fewest were reported between 03:00 and 06:00 (4%; median: 15; IQR 7; range: 10–26 cases; Kruskal-Wallis: p<0.001).
The median number of urogenital conditions cases per month was 122 (IQR 24; range: 80–153 cases). Most cases occurred between 09:00 and 12:00 (22%; median: 27; IQR 7; range: 14–35 cases), while the fewest were recorded between 00:00 and 03:00 (5%; median: 5; IQR 4; range: 2–12 cases; Kruskal–Wallis: p<0.001).
The median number of endocrine and metabolic emergencies per month was 58 (IQR 18; range: 28–84 cases). Most cases occurred between 12:00 and 15:00 (23%; median: 11; IQR 9; range: 7–26 cases), while the fewest were reported between 03:00 and 06:00 (4%; median: 2; IQR 2; range: 0–3 cases; Kruskal-Wallis: p<0.001).
The median number of infectious cases per month was 65 (IQR 17; range: 48–95 cases). Most cases presented between 09:00 and 12:00 (25%; median: 17; IQR 8; range: 11–25 cases), while the fewest occurred between 03:00 and 06:00 (3%; median: 2; IQR 1; range: 0–3 cases; Kruskal-Wallis: p<0.001).
The median number of dehydration cases per month was 63 (IQR 30; range: 41–91 cases). Most of these were reported between 09:00 and 12:00 (23%; median: 13; IQR 11; range: 7–25 cases), while the fewest were recorded between 03:00 and 06:00 (3%; median: 1; IQR 3; range: 0–4 cases; Kruskal-Wallis: p<0.001).
For the majority of conditions—including cardiac arrhythmia, hypertension, vascular disorders, epilepsy seizures, balance disorders and headaches, stroke, trauma, respiratory, gastrointestinal, urogenital, infectious and dehydration-related cases—the number of emergency presentations showed a clear morning peak between 09:00 and 12:00. In contrast, toxicological emergencies (including alcohol intoxication and overdose of sedative or antiepileptic drugs) showed a distinct pattern, with the highest frequency between 18:00 and 21:00. Endocrine and metabolic emergencies also tended to peak slightly later, between 12:00 and 15:00. Bonferroni-adjusted post hoc Mann-Whitney U tests confirmed that these peak intervals (09:00–12:00 or 12:00–15:00 or 18:00–21:00, depending on the condition) differed significantly from most other time periods (all p<0.001) (table 1, online supplemental material S1).
Table 1. Demographic and clinical characteristics of patients (n=32 977).
| Demographic and clinical characteristics of patients (n=32 977) | ||||||||
|---|---|---|---|---|---|---|---|---|
| Symptoms, diseases | Sex(n(%)) | Age (years) | Common diagnoses (ICD-10 code) | Most cases (time) | Fewest cases (time) | All cases | ||
| Female | Male | Female | Male | |||||
| Cardiac arrhythmia | 2753 (54) | 2312 (46) | 66±5 | 61±4 | Angina pectoris, unspecified (I20.9), atrial fibrillation and atrial flutter, unspecified (I48.9), cardiac arrhythmia, unspecified (I49.9), congestive heart failure (I50.0), chest pain (R07.3), bradycardia (R00.0) and tachycardia (R00.1) | 9:00–12:00 | 03:00–06:00 | 5065 |
| Hypertension | 626 (65) | 340 (35) | 71±3 | 61±3 | Essential hypertension (I10) and hypertensive crisis (I16.9) | 9:00–12:00 | 03:00–06:00 | 966 |
| Vascular disorder | 271 (49) | 279 (51) | 62±4 | 57±3 | Venous thrombosis and embolism (I82), aortic aneurysm (I72), phlebitis and thrombophlebitis (I80) and haemorrhoids (K64) | 9:00–12:00 | 03:00–06:00 | 550 |
| Epilepsy seizure | 175 (37) | 301 (63) | 59±6 | 55±6 | Generalised epilepsy seizure (G40) | 9:00–12:00 | 00:00–03:00 | 476 |
| Balance disorder and headache | 299 (54) | 257 (46) | 62±5 | 57±4 | Balance disorder (H81) and headache (R51) | 9:00–12:00 | 03:00–06:00 | 556 |
| Stroke | 645 (51) | 629 (49) | 73±6 | 68±5 | Cerebrovascular diseases (I60-I69) | 9:00–12:00 | 00:00–03:00 | 1274 |
| Traumas | 5812 (52) | 5417 (48) | 64±6 | 51±5 | Wounds and fractures (S00-S99) | 9:00–12:00 | 03:00–06:00 | 11 229 |
| Toxicological emergencies | 535 (26) | 1491 (74) | 52±5 | 50±3 | Toxic effect of alcohol (T51) and poisoning by antiepileptic and sedative–hypnotic drugs (T42.6) | 18:00–21:00 | 6:00–9:00 | 2026 |
| Respiratory symptoms | 945 (52) | 880 (48) | 62±5 | 56±4 | Pneumonia (J18), pneumothorax (J93), chronic obstructive pulmonary disease acute exacerbation (J44.1) and asthma (J45) | 9:00–12:00 | 03:00–06:00 | 1825 |
| Gastrointestinal symptoms | 2789 (56) | 2183 (44) | 62±6 | 56±5 | Abdominal pain (R10), nausea and vomiting (R11), constipation (K59.0), ascites (R18.0) and diseases of biliary tract (K83) | 9:00–12:00 | 03:00–06:00 | 4972 |
| Urogenital tract symptoms | 865 (55) | 710 (45) | 63±4 | 56±3 | Cystitis (N30), chronic kidney disease (N18) and nephrolithiasis (N20) | 9:00–12:00 | 00:00–03:00 | 1575 |
| Endocrine, metabolic symptoms | 445 (59) | 304 (41) | 73±5 | 63±4 | Hypoglycaemia (E16) and hypo-osmolality and hyponatraemia (E87.1) | 12:00–15:00 | 03:00–06:00 | 749 |
| Infections and sepsis | 485 (54) | 411 (46) | 63±6 | 60±5 | Bacterial infection (A49), infectious gastroenteritis and colitis (A09), erysipelas (A46) and sepsis (A41) | 9:00–12:00 | 03:00–06:00 | 896 |
| Dehydration | 487 (60) | 331 (40) | 80±4 | 74±3 | Dehydration (E86.0) | 9:00–12:00 | 03:00–06:00 | 818 |
| All symptoms, diseases | 17 132 (52) | 15 845 (48) | 65±8 | 59±7 | All cases | 9:00–12:00 | 03:00–06:00 | 32 977 |
Note: ICD codes were grouped into 14 categories according to the Hungarian healthcare service classification (code 46, emergency outpatient care). Values represent descriptive statistics only (frequency, percentage, mean±SD). No inferential tests were performed for these data.
ICD-10, International Classification of Diseases, 10th Revision.
Detailed characterisation of hypertensive emergencies
A greater number of patients presented on weekdays (76%; median: 3; IQR 7; range: 2–4 cases) compared with weekend days (24%; median: 2; IQR 8; range: 2–3 cases; Mann-Whitney U test: p=0.013). We analysed whether the number of hypertensive cases showed a seasonal variation, but we did not find it significant (Kruskal-Wallis test: p=0.159).
For further analysis, 78 women (aged 65–77 years) and 42 men (aged 54–70 years) were included in the sample (n=120) using proportionally stratified random sampling.
The mean systolic blood pressure was 184.5±18.4 mm Hg, the mean diastolic pressure was 94.4±13.2 mm Hg and the mean pulse on arrival was 88±16.1 bpm. In the case of systolic pressure, a significant decrease was observed between 12:00 and 15:00 (174.1±20.3 mm Hg; ANOVA: p=0.037). There were no significant differences in diastolic pressure and pulse rate between the different times of day.
The most common symptoms were dizziness (n=41; 34%), headache (n=41; 34%) and chest pain (n=40; 33%). We observed that 50% of patients reported dizziness in the morning, 60% of them reported headaches at dawn, while 42% of them reported chest pain between 21:00 and 0:00, with these problems occurring at a lower rate at other times of the day (χ² test: p>0,05).
The most frequently used medications included captopril (n=61; 50.8%), amlodipine (n=43; 35.8%) and alprazolam (n=43; 35.8%). Between 0:00 and 3:00, 75% of the patients received captopril and alprazolam, and 50% of them received amlodipine, while during the other times of the day fewer of them received the above medications (χ² test: p>0,05).
The triage time showed a modest circadian variation, with a shorter median duration between 09:00 and 12:00 (0:06±0:08) compared with other intervals (ANOVA: p=0.084) (online supplemental material S2).
Discussion
We summarised the circadian patterns of patient symptoms in a busy tertiary ED. Among the cardiovascular symptoms we investigated, most patients with cardiac arrhythmia, hypertension and vascular disease presented to the ED between 09:00 and 12:00. This pattern is presumably linked to the circadian rhythms of cortisol and melatonin levels, as well as morning activity.9,12 Several pathophysiological mechanisms can explain the increase in blood pressure associated with cortisol, including enhanced vascular tone through increased responsiveness to catecholamines and angiotensin II, as well as increased sodium reabsorption via activation of mineralocorticoid receptors. Typical morning behaviour leads to increases in sympathetic tone, vasoconstriction, blood pressure, heart rate, peripheral arterial resistance and platelet aggregability, while decreasing parasympathetic tone, thrombolytic activity and vascular endothelial function.13 The risk of thromboembolism and myocardial infarction is heightened in the morning.14
More hypertension cases were reported on weekdays. It is thought that weekday blood pressure tends to be higher than on weekends, likely due to work stress, commuting, shorter sleep and less recovery time, with some studies showing a Monday ‘spike’ in cardiovascular strain.15 A circadian pattern was also observed in the onset, nature of the symptoms and the medications used. In the case of patients arriving for hypertension, the lowest systolic pressure was measured between 12:00 and 15:00.13 14 Most patients with neurological symptoms arrived between 09:00 and 12:00. The incidence of stroke exhibits an uneven circadian pattern, with a major peak occurring in the morning between 06:00 and 12:00 and a smaller peak in the evening. This may be attributed to the fact that stroke symptoms are often recognised on awakening.16 Circadian genes may influence stroke evolution, incidence and recovery. Clock genes modulate neuroinflammation and microglial activation, thereby regulating the brain’s tolerance and vulnerability to injury.16,19 The circadian rhythm appears to influence both the severity and timing of epileptic seizures.20 Patients with epilepsy commonly experience comorbid major sleep disorders, and poor sleep quality is associated with increased seizure frequency and disease progression.21 Study results indicate that individuals with early chronotypes predominantly experience migraines during the early hours, whereas those with late chronotypes report more cases during the late hours.22
Most patients with trauma arrived between 09:00 and 12:00, which can be attributed to morning activities.23 The risk of road traffic accidents is ten times higher between 02:00 and 03:00; additionally, there is a smaller increase in risk between 14:00 and 16:00.24,26
The majority of patients with toxicological emergencies presented between 18:00 and 21:00, while the fewest arrived between 06:00 and 09:00. Similar temporal trends have been observed in studies of younger populations, where ED visits related to alcohol misuse peaked during evening and night hours.27 Our data align with studies suggesting that the risk of attempting suicide by self-poisoning is greatest in the early evening. Self-poisoning may exhibit a circadian rhythm because various physiological phenomena follow circadian patterns. Lowered serotonergic activity and increased adrenergic activity in the afternoon might contribute to mood changes.28 29
Most patients with respiratory symptoms arrived between 09:00 and 12:00, with the lowest number presenting between 03:00 and 06:00. In cases of chronic obstructive pulmonary disease, patients experience more problems in the morning and during the day.30
Most endocrine and metabolic emergency cases were recorded between 12:00 and 15:00, suggesting a possible influence of circadian variations in hormonal and metabolic regulation during the early afternoon hours. Glucose intake and identical meals result in a significantly higher elevation of plasma glucose in the evening compared with the morning. The insulin response to oral glucose is also affected, with the increase generally being higher and of shorter duration in the morning than in the evening.31 Endocrine and metabolic emergencies may cluster in the afternoon because circadian hormone fluctuations (declining cortisol, altered insulin sensitivity, waning counter-regulatory reserve) create greater metabolic vulnerability later in the day.
Most patients with urogenital and gastrointestinal symptoms, as well as those with infections, sepsis and dehydration, arrived between 09:00 and 12:00, which can be attributed to morning activity.
Taking the above into account, it is recommended that medications be administered at different times throughout the day.12 Circadian medicine, which examines the interactions between the circadian system, sleep and the balance of health and disease, is becoming increasingly significant, highlighting the growing importance of personalised medicine. Chronotherapy optimises medical treatments by considering the body’s circadian rhythms. It is practised in three ways: (1) restoring the proper circadian pattern of the sleep–wake cycle (training the clock); (2) taking patients’ circadian rhythms into account to enhance therapy (clocking the medications) and (3) pharmacologically targeting components of the circadian clock (drugging the clock).9 32
While biological circadian phenomena undoubtedly shape patterns of disease onset and progression, social and behavioural factors are often underestimated. Daily routines such as commuting during rush hours, morning habits, leisure activities (eg, pub attendance) and cultural attitudes toward seeking care (eg, delaying calls until ‘office hours’ to avoid disturbing physicians) also exert a significant influence on the timing of healthcare demand.
While each symptom can be explained by distinct pathophysiological processes and supported by clinical observations, they all share a common denominator in circadian rhythm disruption. This central timing system not only governs the sleep–wake cycle but also integrates hormonal, autonomic and immune functions. Therefore, the individual symptom categories should not be regarded in isolation but rather as parts of a broader, unifying framework in which circadian dysregulation serves as the connecting mechanism. Emphasising this perspective enhances the coherence of the clinical picture and provides a more integrated basis for therapeutic approaches. Understanding the times of day when patients present with specific problems in EDs is crucial for effective resource allocation and clinical preparedness.
The study has limitations due to the non-representative nature of the sample. During data analysis, the database included only a few variables: symptoms, time of arrival, gender and age. In this study, we only have precise data on the time of arrival at the clinic, not on the onset of symptoms, except for a subset of hypertensive patients. In the cases of hypertension, we aimed for representativeness and the examination of several parameters, but the number of cases was low. In the hypertension subgroup, missing data were handled by excluding incomplete cases for each variable. While this approach provided clear comparisons, it may have introduced bias and reduced statistical power, as missingness was not systematically controlled.
Conclusion
Our analysis identified a diurnal variation in symptom presentation, symptom nature and the medications used, suggesting a potential association with circadian rhythms. This pattern indicates that biological clocks may influence symptom onset, leading to increased emergency visits during late morning hours. A better understanding of these rhythms could inform more effective staffing and resource management strategies, ultimately improving departmental efficiency and patient care. Moreover, if patients and physicians are aware of the circadian pattern of symptoms and the circadian rhythm of physiological processes, they may better understand symptom fluctuations and chronotherapeutic principles.
Future research should further investigate the relationship between circadian rhythms and specific symptoms to optimise ED operations and improve patient outcomes.
Supplementary material
Footnotes
Funding: This research was supported by the Research Fund of the University of Pécs (Pécsi Tudományegyetem Kutatási Alap Pályázat), grant number 015_2024_PTE_RK/20. The funder did not influence the results/outcomes of the study despite author affiliations with the funder.
Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2025-101295).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Ethics approval: The study was performed in accordance with the principles of the Declaration of Helsinki. Ethical approval was granted by the Hungarian National Centre for Public Health and Pharmacy (NNGYK/31233-7/2024). This retrospective study involved anonymised data only; individual consent was therefore not required.
Data availability statement
Data are available upon reasonable request.
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